The Chronology of the Texts in the Holy Quran According … Arabic word of a verse, which is the...

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The Chronology of the Texts in the

Holy Quran According to NLP

Techniques

Sameer Mabrouk A Alrehaili

MSc Advanced Computer Science

2011/2012

i

Summary

Text analysis has helped in a number of computational linguistics matters and

has been improved recently by providing a number of methods for analyzing the

texts. The parts of a text that have been arranged in a chronological order might

help in understanding the text much better, especially if the content includes

important topics. Moreover, the interpretation of that text with consideration of

the underlying circumstances as well as related events might be more sensible

than just looking to the literal interpretation.

The aim of this project is to investigate a number of chronological arrangements

of the Holy Quran as depicted in previous researches, focusing on the

arrangements that divide into 7 phases that were proposed by [1] and trying to

find other markers of styles supporting it.

In this project, I find that most features supporting this 7-phases chronology are

depending on the feature’s word count. Other features such as conceptual

occurrence of “Allah” and related verses give a slightly similar number to the

independent markers.The most significant results were when I obtained a

reverse order with relative markers such as the 11th most-frequent Part-of-

speech tags and the 28th most-frequent morphemes.

I also found a way to evaluate these orders using the agreements’ criterion with

the well-known studied chronology called Mecca-Medina. This project provides a

solution to some of these problems by building a database that contains a

number of arrangements of texts, with features of each time period or phase. In

Addition, a web user interface developed on http://www.salrehaili.com/quran, in

order to make the expirements done during this project, are avialble for

researches who are interested in the chronological order of the Quran.

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Acknowledgements

First and foremost, I would like to express my gratitude to Allah (God) for

blessing me and providing the opportunity to complete this project. I pray that

this project be successful and useful.

Secondly, I would like to thank my parents for their endless support during this

work in my entire MSc course and my academic life. I would also like to thank

my family brothers, sisters and those who have helped me, especially my wife

and my daughter “Mayar”, to be patient during my work on this project.

I would also like to thank my project supervisor, Dr Muller. He has given positive

comments during the hard times of this project. He has provided eternal

encouragement during long meeting and provided useful advices to avoid

difficulties in the project. I have now realised every advice that he suggested

me.

I would also like to thank my project assessor, Eric Atweel, for his feedback on

both the interim report and at progress meeting. Without his expertise and

advice, this project would have not been where it is today. It has been a great

experience working with him.

Thank you also to Benham for providing me a copy of the corpus used in his

research as well as his feedback on my work.

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Contents

Summary .................................................................................................................................................. i

Acknowledgements ................................................................................................................................. ii

Contents ................................................................................................................................................. iii

List of Figures ......................................................................................................................................... v

List of Tables ......................................................................................................................................... vi

Glossary ................................................................................................................................................ vii

1. Introduction ..................................................................................................................................... 1

1.1 Understanding the problem ............................................................................................................... 1

1.2 The overall aim ................................................................................................................................. 2

1.3 Objectives ......................................................................................................................................... 2

1.4 Minimum Requirements ................................................................................................................... 3

1.5 Degree Relevance ............................................................................................................................. 3

1.6 Deliverables ...................................................................................................................................... 4

1.7 Research methodology ...................................................................................................................... 4

1.8 Report Layout ................................................................................................................................... 5

2. Background ..................................................................................................................................... 6

2.1 Computational linguistics ................................................................................................................. 6

2.2 What is the Holy Quran .................................................................................................................. 10

2.3 Traditional order of the Holy Quran ............................................................................................... 11

2.4 Quran Divisions .............................................................................................................................. 12

2.5 Previous works ................................................................................................................................ 13

2.6 Two phases...................................................................................................................................... 14

2.7 Four phases ..................................................................................................................................... 15

2.8 Evaluation techniques ..................................................................................................................... 16

2.9 Historical information ..................................................................................................................... 16

2.10 Similar Researches ........................................................................................................................ 18

2.11 Feedback from interested scholars ................................................................................................ 18

2.12 Evaluation data .............................................................................................................................. 18

2.13 Tools used in this project: ............................................................................................................. 19

3. Project Management ..................................................................................................................... 20

3.1 Project management approach .................................................................................................... 20

3.2 Development tasks ...................................................................................................................... 22

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3.3 Initial Schedule ........................................................................................................................... 23

3.4 Revised schedule ......................................................................................................................... 26

3.5 Minimum requirements changing ............................................................................................... 27

4. Implementations ............................................................................................................................ 28

4.1 Design ......................................................................................................................................... 28

4.2 Collecting the corpus .................................................................................................................. 29

4.3 Pre-processing ............................................................................................................................. 30

4.4 Design and create a database ...................................................................................................... 33

4.5 Basic Markers ............................................................................................................................. 37

4.6 Occurences of Allah names......................................................................................................... 39

4.7 Conceptual markers .................................................................................................................... 39

4.8 Related verse ............................................................................................................................... 40

4.9 Relative frequencies of Part-of-Speech tagset in the Quran ....................................................... 41

4.10 28th most frequent morphemes in the Quran ............................................................................ 44

4.11 Relative frequencies of vowels ................................................................................................. 45

5. Results and Evaluation .................................................................................................................. 46

5.1 Results ....................................................................................................................................... 46

5.2 Experiment One: arrangements of 194 blocks ............................................................................ 46

5.3 Experiment number two: Groups ................................................................................................ 50

5.4 Experiment number three: Passages, or 7 phases........................................................................ 54

5.1 Relative frequencies of 11 most frequent tags ...................................................................... 57

6. Conclusions ................................................................................................................................... 59

6.1 Future works ......................................................................................................................... 60

Bibliography ............................................................................................................................................ i

Appendix A: Personal Reflection .......................................................................................................... iv

Appendix B: Interim Report ................................................................................................................... v

Appendix C: Feedback ........................................................................................................................... vi

Appendix D: Figures ............................................................................................................................. vii

Appendix E: Text arrangements used in the project ............................................................................ viii

Chronological Order of Suras from Tanzil project ........................................................ xiii

Appendix F: Initial minimum requirements ........................................................................................ xviii

Appendix G: Web user interface ........................................................................................................... xix

v

List of Figures

Figure 1: shows the traditional order of the Holy Quran order, Suras arrangement not according to

Mecca-Medina. ..................................................................................................................................... 11

Figure 2 shows the previous Quranic chronologies (1) ........................................................................ 13

Figure 3, shows the iterative approach life cycle .................................................................................. 21

Figure 4, the project in detailed tasks ................................................................................................... 22

Figure 5, shows the Gantt chart of this project ..................................................................................... 24

Figure 6, shows the revised Gantt chart ................................................................................................ 26

Figure 7, ERD diagram for the database ............................................................................................... 34

Figure 8, shows several different order and markers for each verse. .................................................... 34

Figure 9, taken from (http://www.textminingthequran.com/apps/referents.php?con=1 ) shows a list of

the concept of Allah from , there are 3061 word related to Allah in the Quran according to Tafsir Ibn

Khathir. ................................................................................................................................................. 39

Figure 10, shows the Mean Verse Length for 194 blocks according to scheme of blocks described in

Sadeghi paper ........................................................................................................................................ 46

Figure 11, represents blocks from 108 to 137 using MVL with three vowel symbols as well as the

number of morphemes in the block. ...................................................................................................... 47

Figure 12, represents blocks from 176 to last block using five markers. .............................................. 47

Figure 13, the frequencies of most frequent word in the Holy Quran “ Allah “. .................................. 48

Figure 14, shows the frequencies of words that related to the concept of Allah over 194 blocks

division. ................................................................................................................................................. 49

Figure 15, the frequencies related verses over 194 blocks. ................................................................... 49

Figure 16, the number of Meccan verses in each block ........................................................................ 50

Figure 17, shows different markers according to groups level, similar pattern can be seen for first four

markers. ................................................................................................................................................. 50

Figure 18, the occurance of Allah in each group of text ....................................................................... 51

Figure 19, occurance of word related to the concept of allah according to 22 groups division. ........... 51

Figure 20, the number of verses that directly related to the verses in the group. .................................. 52

Figure 21, the percntage of Meccan verses that each group has. .......................................................... 53

Figure 22, Meccan and Medinan verses occurrence in each passage ................................................... 54

Figure 23, the percentage of Meccan verses in each passage it is clearly that the percentage of Meccan

verses are higher from passage 1 to 6. .................................................................................................. 55

Figure 24, shows three most frequent vowel symbols in Arabic language, x passages ordering

according to the timeline and y is the frequencies of these symbols. ................................................... 56

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List of Tables

Table 1, shows the time table of the project tasks................................................................................. 24

Table 2, revised timetable divided in 6 main tasks ............................................................................... 26

Table 3, shows most frequent words in the text in descending order. .................................................. 31

Table 4 .................................................................................................................................................. 31

Table 5, 30th most frequent words in the Quran ................................................................................... 31

Table 6, ................................................................................................................................................. 44

Table 7, shows 8 passage of texts increase dramatically according to the 8 different features ............ 50

Table 8, ................................................................................................................................................. 52

Table 9, ................................................................................................................................................. 52

Table 10, 11 most frequent morphemes in the Quran aacording to the order proposed by Bazrgan .... 53

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Glossary

Marker

One of the characteristics used to distinguish one phase from another.

Phase

A group of verses that belong to same period.

Sura

Is the Arabic word of a division that composed of several verses called chapter. The plural form of Sura is Suras.

Aya

The Arabic word of a verse, which is the shortest division in the Quran and is group of words that complete in itself. The plural form of Aya is Ayat.

Arrangements

Quran text divided in different order to traditional order such as blocks, groups and passages.

Blocks

An arrangement of the Quran verses in 194 phases.

Groups

An arrangement of the Quran verses in 22 phases, which is derived by merging several blocks.

Passages

An arrangement of Quran verses in 7 phases, which is derived by merging several groups.

Mecca-Medina

An arrangement of the Quran Suras based on the places of the revelation.

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Chapter 1

1. Introduction

In this chapter, I clarify the problem that has been tackled with the discussion of

the general area of this project. Additionally, this chapter outlines the goal and

objectives as well as describes the research methodology that has been used to

reach to my solution. Finally, its layout provides guidance to the reader about

the rest of the report.

1.1 Understanding the problem

The Holy Quran is the scriptures of the 2.1 billion Muslims around the world [2].

The earliest Muslims who were around the Prophet Muhammad and lived in the

period of the revelation understand the Holy Quran more than people today

because they were remembering some of the contextual situations of the verses.

Islamic scholars review the situation of the verse, such as the location of

revelation, the occasion on which a verse was revealed, and preceding verses

that address similar topic. This information helps in interpretation due to

dependency between the verses. However, there is a consensus that the Holy

Quran order is not according to the chronology of the revelation. Consequently,

it is easily misunderstood.

An example of misunderstanding of the Quran is when someone says that

Alcohol is not forbidden except during praying times, the verse (4:43) in the

Quran which says “Believers, do not pray when you are drunk” represents only a

gradient stage in the legislation of prohibition; alcohol was forbidden on the

stages to make it easier for people to follow this legislation. In modern times,

people do not understand why there is a verse that says alcohol has more

disadvantages than its advantages while another verse prohibits drinking alcohol

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entirely (5:90) and another mentions drinking without any mention of

prohibition (16:67).

Reading these verses without knowing their context for them and their

chronological order as it was sent down could cause misunderstanding of the

Islamic rules and may produce incorrect interoperation of the Holy Quran.

Therefore, producing a computational method or technique to show the suitable

order of those verses would help in the interpretation.

1.2 The overall aim

With the increase in text-analysis technology that detects the relationship

between the parts of texts in order to attribute authorship to disputed

documents, detect plagiarism, and determine the chronology of document parts,

there is pressure to create a suitable way to determine which text come before

the other. As was said above, the Holy Quran is not in the chronological order

according to the date of the verses or Sura [3]. The verses were revealed

responding to various events and incidents as well as the cultural-social

circumstances of the revelation period. This overall aim of this project is to

identify features that are related to the temporal ordering of the Holy Quran.

1.3 Objectives

The objectives of the project are to

• Understand the issue by investigate existing research into

computational linguistics, with a particular focus on the Quran corpus

and theme;

• Collecting the corpus of the Holy Quran and tokenizing the text down

to word level;

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• Design a DB that facilitates testing of different orders against markers

of style and to record verses in both numbering systems (Sura &

verse) and verses;

• Creating different arrangements of the Quran text.

• Compute different markers of style related to time, such as Mean

Verse Length;

• Represent different styles of the proposed chronology.

1.4 Minimum Requirements

• Collecting the corpus of the Holy Quran according to the arrangement

as described in this paper [1].

• Compute different markers of style for the corpus.

• Create a database of verses and consider different orders and markers.

• Identify some markers of style that indicate whether divided texts are

in accurate order.

Possible Enhancements:

• Develop an API which allows interested researchers to easily compute

features with arrangements of the text.

• Use additional markers and rearrangements.

• To create a user interface that applies different markers for a

generated order.

1.5 Degree Relevance

This project was created based on the knowledge and skills acquired from

several modules of my Advanced Computer Science MSc course in the School of

Computing at the University of Leeds. COMP5410M (Language) was useful as it

introduced a strong background for computational linguistics areas such as text

analytics, corpus linguistics, corpus Arabic, and corpus annotation techniques, in

particular, Arabic and Quran Corpus.

4

1.6 Deliverables

An API with a database that contains several markers and arrangements can be

used to record new markers or arrangements or represent the relationship

between them. A web user interface, to represent my expirments and make it

available for interested researchers.

1.7 Research methodology

My methodology in this project begins by dividing the Quran text into groups,

then extracting some features from each group related to the time period. In

other words, this distinguishes a group from others. Determining whether these

features are related to a certain time or not is very simple, as previous studies

pointed out that a verse length increases monotonically over time. The style of

extracted feature or its representation should be a unique. If there are some

features that have a similar style—especially if they are independent of each

other—that means they could help us detect the chronological order. Therefore,

I will start with the feature of verse length because many researchers observed

its style. Then I will look for other features have a similar style of verse length; if

there is similar pattern over a selected group, then this feature will be accepted

and it will identify the periodic ordering. Otherwise, the feature will not support

the selected group of text. At this point, I shall try other features or other

dividings of text.

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1.8 Report Layout

The remainder of the report is to split into sections explaining different stages of

the project.

Chapter 2 presents an overview of the previous research of the project, giving

more explanation on the problem to be tackled, the methodologies considered,

as well as the techniques which will be used to evaluate the software.

Chapter 3 discusses the project management, laying out the aims and

requirements that were decided upon, as well as the decisions made relating to

the program structure, usability and experiment design.

Chapter 4 explains the implementations in three sections; design, preparation,

and markers of style computing.

Chapter 5 discusses results and evaluate the success of the project and whether

it has met its aims. In addition, it addresses the limitations have encountered

during the project.

Section 6 is conclusion with possible future works.

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Chapter 2

2. Background

This chapter provides an introduction to the nature of the problem tackled in this

project, information relates to the problem, research on possible divisions and

features for use in the solution as presented in this project and research

methodologies, as well as the evaluation techniques will be used to evaluate the

success of the project.

2.1 Computational linguistics

Computational linguistics, or Natural Processing Language (NLP), is an

interdisciplinary sub-field of computer science that is concerned with the

processing of natural languages in terms of the computational perspective [4],

[22] . This field has become an important field of industrial development as well

as has shifted from studying theoretical models and small prototype to producing

a practical system that can work on large corpora [5]. The nature of projects in

this field is often expected to manage by multidisciplinary teams such as

computer scientists and language experts (those persons who have command on

the languages used in the project). For example, an English-language knows the

rules of how humans recognise verbs from the nouns in sentences in English

sentences; this is a task not easily accomplished for a computer. However, some

skills are tough to be accomplished by computer.

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Tokenization:

In text processing, the first step is often a tokenization, which is a process of

dividing the given text into small units called tokens [6] [7]. This process seems

easy in a language such as English that separates words by whitespace

character; however, whitespace is not enough to break the text into words.

Consider the following sentences:

1- What’re you looking for?

2- I went to New York.

If we use white spaces as a word boundary, the number of words in the first

sentences would be four, “are” not counting because it is part of a contraction.

Other examples like contractions, such as abbreviations (i.e.. Ph.D., W.C,

K.S.A), may result in an error in the process of tokenization because it does not

distinguish between the dot which means a sentence boundary and the dot of an

abbreviation. This problem can be solved by removing punctuation marks from

words, but in some cases it is important to keep them so that we can make a

distinction between “Wash.,” an abbreviation for Washington, from the verb

“wash” [6]. In the second example from the list above, New York would be

considered as two words even though it is a city in the United States. To avoid

this problem a technique named Entity Detection is used [7]. Fortunately in

Arabic, abbreviation does not exist. The tokenization is a crucial one for the

tagging process [8].

Part-of-speech tagging/Morphological analysis:

Part-of-speech tagging is the process of assigning the tag set class to each word

in the corpus [7] or classifying the morpheme into classes. The Quranic Corpus

labels the words into 44 tags or classes. Morphology Analysis in Arabic language

is complex and challenging for computer due to different scripts and vowels not

always included in the written text [9]. Arabic words may be composed of

several types of morphemes (i.e stem, prefix, suffix and clitic). The latter three

components may be attached to the stem without orthographic marks like

apostrophes used in English [10]. A complex example of Arabic morphology can

be seen in the following figure form [11].

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Figure 1: A word with colour-coded part-of-speech tags that composed of five morphemes fromhttp://corpus.quran.com

Difficulties:

One of oldest difficulties in computational linguistics and NLP is dealing with

ambiguous aspects of texts including lexical and syntactic ambiguity

[12]. Lexical ambiguity occurs when a word or phrase has more than one

meaning; in these situations, the software may have difficulty determining which

meaning is intended. In English, an example would be the word “bear,” which

can be a noun representing an animal or a verb meaning “to carry.” One of

methods used to solve this problem is called Word Sense Disambiguation [7].

By contrast, syntactic ambiguity is the result of relationships between words,

rather than word meanings in and of themselves. An example of syntactic

ambiguity would be “The car was found by a tree.” A reader knows that this

sentence describes the location where the car was found – not who found the

car. Although a human would be able to understand that a tree cannot have the

agency to “find” anything, computer software would not necessarily be able to

do so.

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In recent years, a subfield of computational linguistics has emerged:

computational stylistics. The goal of this field is to address some of the issues

associated with syntactic ambiguity. Among the applications for computational

linguistics are determining authorship, detecting plagiarism, extracting

information, clarifying word meaning, and, most recently, aiding in generating

the chronological order of texts.

In this study, we will focus on the latter application: the chronological ordering

of texts. In other words, we are interested in detecting how the text evolves

stylistically over time as opposed to the meaning of the text.

While most traditional research in the field of Natural Language Processing has

focused on the analysis of the subject of the text (i.e., the meaning), relatively

new vein of research focuses on linguistic style (i.e., how a text conveys its

meaning). Computational Stylistics is a trend in Natural Language Processing

that looks for patterns in a text to determine authorship of disputed documents

(Is Shakespeare really who we think he is?) or the chronology of texts [13].

Stylometry is the application of the study of linguistic style (stylistics). Although

this is usually done in the context of written language, it has been applied

successfully to music and fine art as well. In addition to its clear importance in

the academic realm, it has also proven useful in legal settings. In recent years,

it has been explored as a tool for chronological study of texts (as opposed to

stylistic analysis primarily to determine meaning).

Few scholars have studied the chronology of the Quran. The studies of those

who have can be divided into four categories: Phases 1 and 2 (Mecca and

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2.2 What is the Holy Quran

The Holy Quran is the last sacred book among books that were sent down to

God’s prophets. The Holy Quran is undoubtedly an important book; Muslims take

the rules and guidance from the Quran such as rules of marriage, divorce,

inheritance, finance, etc. The Holy Quran is composed of verses, also known as

“Ayat”; there are 6236 verses in the Quran, categorised in 114 Chapters or

(Sura). A verse is the shortest division in the Quran and is a group of words that

is complete in itself. Chapters are varying in length; one chapter has 286 verses

while another has only 3 verses. This division to Sura and Aya helps in referring

to a specific verse, the notation (113:1) meanings we refer to a chapter (Sura)

number 113 and verse (Aya) number 1.

The Holy Quran was sent down through the Holy Spirit (angel Gabriel) to the

prophet Muhammad during a period of approximately 23 years from 610 to 633

CE [14]. The Holy Quran was not sent down as a single book as it is known

today; neither was it revealed in a single session. The revelation came in

response to specific events. Therefore, in order to understand the Quran it is

important to know about the prophet Muhammad’s history. The first part of the

revelation was in Mecca, the city in which the prophet Muhammad was born.

Prophet Muhammad was born in Mecca; and the first revelation was done when

he was 40 years old. He continued to teach people Islam in Mecca for 13 years.

The verses revealed in this period are called “Meccan.”. Then, he migrated to

Medina, which is about 400 km from Mecca. The verses revealed after his

migration to Medina are called “Medinan.”.

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2.3 Traditional order of the Holy Quran

There is a consensus among Muslims that the Holy Quran is not arranged

according to the date in which the verses or chapters were revealed or even the

place where they were revealed [3], [15]. There is an agreement among

scholars that the order of verses in every chapter was done by the Prophet

Muhammad following Allah’s command. He was instructed to put these verses in

a specified location (Ahmad [399], Abu Dawood [768], Tormithi [3086] and

Nessae [8007]. Also the chapter order is believed to be according to the order

when the angel Gabriel revealed the Quran to the prophet Muhammad every

Ramadan. For instance, we find the Sura AL-Alaq (The Clot), one of Meccan

Sura, as the 96th Sura, but there are claims that this Sura was the first Sura

revealed. Similarly, the 2nd Sura, called AL-Baqarah (The Cow), is one of the

Sura that was revealed in Medina or after the migration of the prophet

Muhammad. Although the chapters have been arranged in an order that is

different from the sequence of revelation, we do not say that it has been

arranged in the wrong way because it was revealed to respond to various events

and incidents.

The following figure shows the current order of the Suras in the Holy Quran in

terms of classification to Mecca and Medina periods.

Figure 2: Traditional Order of the Holy Quran.

1

2

1 6

11

16

21

26

31

36

41

46

51

56

61

66

71

76

81

86

91

96

10

1

10

6

11

1

Traditional order of Sura's in the Holy

Quran

Sura no

12

Figure 2 shows the tradisional order of the Holy Quran. The X-coordinate

represents the order of 1 to 114 of Suras. Y shows where these Suras were

revealed. If we assume that the given order is follows the same sequence of the

revelation, it means that the Suras on the left side of the figure should be

located on the point 1 in the Y-coordinate while the right side located on point 2

of Y. It is clearly seen that the Suras are not ordered based on time because

there are some Suras, like Suras number 2 and 3, which were sent down in

Medina. Also the last four Suras appear to have been revealed in Mecca.

2.4 Quran Divisions

The Holy Quran consists of 30 parts and all of these parts are divided into a

number of sections called Hizb; each Hizb is divided into a number of

subsections named Ruba, and each Ruba has verses. The signs and this division

came after the death of the Prophet, peace be upon him, and his successors.

The purpose of these divisions is not to sort the text according to revelation time

but to facilitate the search and access to the content of the Quran.

A verse is the smallest part that can be read in the Holy Quran. For example,

verse No. 1 Sura No. 108 AL-Kawther (A river in paradise); “Indeed, we have

given you AL-Kawther”. There are some verses that consist of only 2 or 3

letters; these are special verses that comes in the beginning of a Sura and are

also called as mystery letters. Twenty-nine Suras are begin with these letters 2,

3, 7, 10, 11, 12, 13, 14, 15, 19, 20, 26, 27, ,28 , 29, 30, 31, 32, 36, 38, 40, 41,

42, 43, 44, 45, 46, 50, and 68 [16] .

Numbering of the verses is not part of the Quran, but a way to facilitate access

to particular parts of the Quranic text. According to Coofian numbering system,

there are 6236 verses in the Holy Quran distributed in 114 Suras.

These Suras are not the same length; shortest chapter, for example, Sura no

108 (Al-Kawthar), has only three verses, while the longest one Sura, no 2, (Al-

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Baqarah), has 286 verses [3] .These suras are identified as Meccan or Medinan.

The first is Mecca and the second is Medina. Mecca and Medina are two cities in

The Arab peninsula, most of which is called now Kingdom Of Saudi Arabia. Some

scholars identified them as before or after the migration of Muhammad from

Mecca to Medina. There are 89 Meccan Suras and 25 Medinan Suras. Some are

mixed and have verses from the two periods. These Suras were revealed in

Mecca then completed later after migration to Medina.

2.5 Previous works

Traditional 1 2

Weil, et

al.

1 2 3 4

Bazargan 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 21 22

Modified

Bazargan

1 2 3 4 5 6 7

Figure 3: The Previous Quranic Chronologies [1]

Early studies in the Holy Quran chronologies show there are only two phases

(Mecca-Medina) according to the location of revelation. The Meccan period lasted

for 13 years, and the remaining 10 years belong to Medina. The Weil, et al.

chronology has more detail for the Mecca period: early, mid, late. Bazargan has

proposed a 22-phase chronology, with 12 for Mecca and 11 for Medina. The

modified Bazargan merges the Bazargan chronology into 7 phases.

14

As some Suras contains verses from Mecca and Medina, it may not be possible

to rearrange the Suras. Block scheme has used from Bazrgan’s chronology to

rearrange the text [1]. A block is a set of verses that are believed to belong to

the same period. A Sura can be divided into one block or more, but a block

cannot have verses from different Suras. See Appendix E, a notation “(1) 96: 1-

5” means that Block 1 is defined as verses from 1 to 5 in Sura. 96.

2.6 Two phases

Most previous studies in the chronology of the Holy Qur’an are divided into

two phases (Mecca and Medina) and also explained the difference between those

two periods due to of the occurrence of certain words or phrases in the text. A

large number of scholars were interested in this chronological order of the Holy

Qur’an, therefore, a much work has been done to distinguish between these

periods by the style of words composing the verses or the style of the verse.

The style of verses: Meccan verses deal with matters of faith and uniformity

and give arguments and evidence that there is only one God [18], because the

Arabs before Islam were taking a number of idols and Khbl Lat and Uzza

worship. While the Medinan verses deal with the civil legislation and provisions

such as prayer, fasting, war, and the Hajj and Umrah and family affairs and so

on [18].

The form of the verses: Meccan verses tend to be short, compared to

Medinan [18], [19]. For example, verse 282, one of the Medinan verses, of Sura

No. 1 is the longest verse in the Holy Quran and has 128 words, while the first

verse of Sura No. 96 contains only 5 words and was revealed in Mecca.

According to [18] and [19], Meccan Suras also tend to be short, whereas the

Medinan tend to be long. However, there are some exceptions. For example,

Sura No. 103 (Time) that was revealed in Medina is shorter than Sura No. 96

(The Clot), which was revealed in Mecca.

15

Another marker used to distinguish between Meccan and Medinan verses is the

style of speech: in Meccan verses the phrases “O people” and “O son of Adam”

were used while “O believers” was used in Medinan verses [18].

[16] said that the most prominent feature is the rhyme, as 90% of the verses of

the Quran contain a pattern close to the prose. Most rhymes used in the Holy

Quran end with “im,” “un,” “in,” or “um.” This feature is valuable for this project

and can be taken as a marker of style to test the proposed order by [1].

However this feature cannot be easily captured because they sometimes have a

similar pronunciation but different spelling of the word at the end of verse.

The most common Diacritics used in Arabic script [16] are the vowel a, the

vowel i, the vowel u, the lack of vowel, and the double consonant.

[20] chose only long chapters in the Holy Quran in order to be classified into

Meccan-Medinan using a multivariate technique called hierarchical clustering.

She has done a comparison between the words that appear more than 1000

times in both periods.

[21], also using the categorization of classical binary Mecca and Medina, used a

machine learning algorithm such as Support Vector Machine (SVM) and Navie

Bayesian classifiers. Using fuzzy-single linkage, Meccan suras have been

clustered into 7 clusters and Medinan suras into 3 clusters.

2.7 Four phases

According to [16], the most commonly accepted chronology is four phases:

dividing Meccan suras into three periods (Early Meccan, Middle Meccan, and Late

Meccan) and Medinan into one. This may be reasonable because the Mecca

period was longer than the period of Medina.

[1] used univariate markers of styles such as mean verse length, the 28 most

frequent morphemes in the Quran, 114 other common morphemes, and 3693

16

uncommon morphemes to verify his chronology. He also used multivariate

techniques such as PCA and MDS in order to verify the chronology of the Holy

Quran in seven passages. This is based on a different assumption of Bazargan

and Noldeke, which says that “the style of the Qur’an changes in one direction

without reversal,” but it is not necessarily true that the style is changing in one

direction without reversal. He corroborates the phases using the principle of

“Criterion of Concurrent Smoothness,” which means using independent markers

of style with particular sequences of text and seeing whether these markers vary

in smooth fashion or not. If yes, it means this chronology is true.. He used the

blocks scheme described in section 2.5 by Bazargan, and the chronology

proposed by Noldeke, described in section no 2.5. After that he merged them

into 22 groups. His work differs from previous research in that previous research

adopted the method of generating chronological order depending on the style

change in one direction and no reversal.

2.8 Evaluation techniques

The criteria will be used to decide whether the sequences generated using

markers of style are in the right order or not. Two different criteria have been

set out: historical information such as Meccan-Medinan, similar researches,

comparing the proposed order with a list of well-known date of verse and

feedback of interested scholars.

2.9 Historical information

A number of researchers have studied the classification of the Holy Quran into

two phases known as Mecca and Medina. This is helpful in this evaluation if I

calculate how many Meccan and Medinan verses are in the proposed order. If

the number of Meccan verses decreased and Medina increased, this means this

order is consistent with these previous studies. The rate will not be 100%, as

there will be some errors due to blocks, groups, and passages having mixed

verses from the two periods.

17

It is well known that the prophet Muhammad was not able to read or write,

although he is the most influential person in the history [30]. Everything in his

life was recorded by his companions, such as sayings and conduct and even his

personal life was told by his wives, and this information was gathered later in

books called “Hadith”. While the Holy Quran is considered to be the first source

of the Islamic law, the Hadith is considered to be the second source and is

important in understanding the Holy Quran.

The confidence of this criterion depends on the authenticity of the Hadith. Hadith

has been evaluated by scholars by dividing it into four categories according to

the degree of authenticity and reliability.

1. Sahih: the genuine traditions and has high degree of authenticity

2. Moothaq: almost like the Sahih but the person who narrated it is not as

reliable as the person who narrated the Sahih

3. Hasan: has low degree of authenticity

4. Dha’eef: not reliable, weak traditions

So, this criterion will be useful for evaluating my project as there are many

Hadiths about the revelation order of the Holy Quran. If my computation marker

of style is monotonically increasing, this mean there is a relation but does not

mean this is the right chronology. Therefore, this criterion will decide if the

proposed order is consistent with this information.

[29] provides a chronological order for the Holy Quran according to the

information coming from Hadith. This chronology is not only based on the whole

Sura, but it also mentions if some verses in a particular Sura were not revealed

in the same period. For instance, Sura number 68 in the traditional order has the

order number 2, except verses 17-33 and 48-50, which were revealed later in

Medina. Further detail can be shown in appendix E .

18

2.10 Similar Researches

A similar study is found in the paper “The Chronology of The Quran: A

stylometric Research Program” described here [1], and I compare my results

with Sadeghi’s to judge my work’s success. The similarity between my work and

Sadeghi’s is that we used the same scheme in dividing the Sura. The 114 Suras

were divided into 194 blocks, then merged into to 22 groups, then merged into 7

passages. My project differed from Sadeghi’s in three ways: First, I used a

different version of the Holy Quran. Second, different markers of style were

produced here. Third, I did not exclude any verse of the Holy Quran, while he

excluded 188 verses, due to repetitions and refining the style, more details in

[1].

2.11 Feedback from interested scholars

Client feedback – from the scholars who are interested in the study of the

chronology of the Holy Quran to see how appropriate the delivered solution was

and what changes could be implemented to improve it further.

2.12 Evaluation data

I will use the same data for evaluation; because of the uniqueness of the text of

the Holy Quran, there is no choice but to evaluate my solution using other texts.

The Quran is written in Uthmanic script, which is different from modern Arabic

spelling and uses didactics or vowel symbols that are not used in modern Arabic

books. It also has different punctuation marks that are not used in other texts,

like pause markers which determine when the reader should pause. The

following table presents pause markers.

19

Compulsory, you have to stop here. Unless the meaning of م

the verse will be destroyed.

� Means do not stop but it is not forbidden

.It is recommended to stop here ط

.Continuing is preferred صلي

.Necessary to stop قلي

.It is permissible to pause here ج

Table 1: special markers used in the Quran text

2.13 Tools used in this project:

Although there are several toolkits available to manipulate the natural language,

such as NLTK to build python programs, I preferred to use Java for this project.

The main reason for that is it has a strong library to manipulate the text.

Another reason is because I have enough experience with Java programming

language. Moreover, the Quranic Arabic Corpus offers an API that allows us to

access and analyse the Holy Quran.

JQuranTree is a Java API that allows access to the Holy Quran text using

different formats of text with a particular location (i.e., by access to Buckwalter

transliteration format within Sura number, verse number, or token number)

[11]. It provides classes for searching for chapters, verses, tokens or characters.

Conceptual features have been based on the Textmining website [23].

Data supplied for this project consists of 6236 verses in an XML file with Java

library (JQuranTree) to gain access to these verses according to their location in

the Holy Quran, library and XML file have been downloaded from the site [11].

20

Chapter 3

3. Project Management

In this chapter, I address the choice of project management approach that I

adopted to manage this project as well as the initial and revised schedule. A

number of project management tools were used to help accomplish the

objectives of this project.

3.1 Project management approach

In order to progress through the project steadily and effectively as well as to

meet the minimum requirements and complete the objective in section 1.3, an

iterative approach [24] as shown in figure 4 was used to manage this project.

This approach starts with developing a prototype according to the initial

requirements, then testing and modification. This process of making a prototype

is continued to produce many versions of the product until we fulfil the final

requirements taken during the process. Repeating the process helps the

manager to receiving feedback before, throughout the project and corrects the

errors which leads to a reduction in risk [25]. It also is one of the fast project

management approachthat allow you to see the results quickly [26]. In this

approach, the work development can start with incomplete requirements.

Therefore, it would be suitable if we want to change the requirements later.

21

Figure 4: The Life Cycle of the Iterative Approach

As I said the iterative development has the advantage of getting feedback and

changing the requirements during the development process because you can see

the results fast. It also allows you to reduce the risks and get high quality

results. The requirements can be changed any time during the development

time.

It also fits the nature of the project because it is repeatable and able to be

modified many times during the process until getting improved version. Each

time we need to compare the style of the new marker over the selected periodic

groups of text with the style of the marker verse length. The extracted features

should be independent, so the way of computing them is not the same but the

testing and evaluating for all features are same.

Requirements

Analysis

DesignImplementation

Testing

22

3.2 Development tasks

I categorised the project objective into sub-objectives and list them with the

tasks that must be achieved in order to complete these sub-objectives

effectively and be manageable tasks. The following figure shows the

necessary sub-tasks under each main task in the project.

Figure 5: detailed list of tasks to be performed for the project

1. Preparation

a. Collect data: download a copy of the Holy Quran, including different

types of transliterations

b. Design: design a template to save different dividings of texts

2. Pre-processing: do some experiments to investigate the most important

words mentioned in the text

3. Divide the text: three types of divisions has been used one in previous

research (see Appendix E and section 2.1)

4. Features extracting:

project

Preparation

collecting data

Databae design

preprocessing

divide data

blocks

groups

passages

features extracting

calculate frequiencies

record in DB

represent features

evaluation

23

a. Calculate frequencies: calculating an aspect in the text: for

example, calculate the number of morphemes in a given word

b. Record in DB: try to find a method to record every extracted

feature to DB instead of repeating the process every time

5. Represent features: find any relation between those divisions of text and

extracted features by plotting them against each other

3.3 Initial Schedule

Before starting the project work, an initial plan was constructed for this project

with implementation of some of the tasks described in the proposed table.

However, while the project was in progress, I needed to change the design a

number of times, resulting in a change in the plan and schedule as well. The

main reason for this change is that during the development I received feedback

that gave me more understanding about the project.

The Gantt chart is a useful technique used in project scheduling that was

invented by Henry Gantt in 1917. The Gantt chart below, which is illustrated in

[27], is widely used among project managers to organize their project tasks

[28]. The Gantt chart for this project, shown below, is split into 20 tasks during

28 weeks starting from 13 February 2012 until the end of August 2012. Each

horizontal bar represents the duration of an activity or task in the project.

24

Figure 6: the Gantt chartschedule of this project

The horizontal bars represent the start and end time for each of the 20 tasks.

This project took place between week 1 of semester 2 (week beginning 23

January 2012) and week 13 of semester 3 (week beginning 1 June 2012) with

the completion of this report taking place on 30 August 2012. The first meeting,

“Procedures and Timetable Meeting”, was held on 23 January 2012, and the

deadline to submit the project report was assumed to be 30 August 2012. It

looks like enough time to complete the project report as there were 28 weeks

until the deadline; however the actual duration was only 13 weeks due to having

4 modules registered in the second semester. Therefore, most of the work in the

project was made after the period of examination, at the end of May.

25

Table 2: shows the time table of the project tasks

The timetable lists tasks (without any details) per specified periods. It also has

important dates in order, such as the deadline for submitting reports.

Background reading and reviewing for methods and Quran corpus were between

16/03 and 26/03. To use a suitable method to collect the text of the Quran, I

have put 2 days because I have come across a website allowing downloading of

a copy of the Quran. After that I stopped working on the project due to having

two course works followed by exams for four modules. I was required to submit

the interim report in the middle of June, therefore after the exam period I read

more about the problem and how it can be solved for 6 days as well as trying to

do some experiments to understand it better. There were 10 days alloted for

writing up what was done so far, then starting real experiments until mid-July.

Then my work time was parallel on improving and waiting up until the end of

August.

26

3.4 Revised schedule

Figure 7 and table 3 show the modified planning and timetable. The initial

schedule was revised by adding more time for the implementation phase,

totalling 36 days instead of 21 days. This was done to find more features like

conceptual features. The revised version of the schedule has 6 main tasks. The

data preparation phase began mid-June and lasted for 6 days. In this phase I

learned the tools for dealing with the corpus, designed the database to store

different formats and orders of texts, as well as did more pre-processing for it.

The next stage required dividing the texts into particular groups so that each

Sura was divided into one or more blocks; this work occurred between 21 June

and 27 June. Next, I tried to find several markers until the middle of July.

Representing these markers and plot, the most important was attached in the

report after mid-July for 5 days. Then, I put 16 days for the evaluation followed

by writing up. The revised Gantt Chart is shown in figure 7.

Figure 7: shows the revised Gantt chart

The revised schedule can be seen in table 3. This schedule allowed less time for

writing and testing.

15-0622-0629-0606-0713-0720-0727-0703-0810-0817-0824-0831-0807-09

Data preparation

dividing texts

features computing

plotting features with orders

evaluation

Writing up

27

No Tasks Start Date Duration End Date

1 Data preparation 15-Jun 6 20-Jun

2 dividing texts 21-Jun 7 27-Jun

3 features computing 28-Jun 18 15-Jul

4 plotting features with orders 16-Jul 5 20-Jul

5 Evaluation 21-Jul 16 05-Aug

6 Writing up 06-Aug 25 30-Aug Table 3: revised timetable divided in 6 main tasks from mid of June until the deadline

3.5 Minimum requirements changing

During the development process of this project I changed the minimum

requirements in order to be more precise. The initial requirements shown in the

appendix F were submitted on 9 March 2012. On 27 July I modified these

requirements as can be seen in the section1.4 I removed the first one “Through

review of the sequence in the Quran” because it was too general. The second

requirement was modified to be more precise too. I did not change the third

one. In addition, one more was added, which is “Create a database of verses

and consider different orders and markers”.

28

Chapter 4

4. Implementations

This chapter contains a description of my implementations. The description is

broken into three sections; design, preparation and markers computing.

This project contains a number of development tasks required to complete the

main objectives listed in section 1.3 . The next section shows some of issues in

the design to be considered in approaching each task, and some information that

is required for understanding the requirements in the implementation.

4.1 Design

Depending on the purpose and objectives described in section1.3, the following

tasks have been done to achieve the goal of this project:

To verify the chronology proposed [1], there are a number of steps which have

been working out as follows:

1. Collecting the Corpus: An electronic version of the Holy Quran.

2. Create a database that will be used to record the verses and extracted

markers of them, Structure Query language (SQL) would be useful if I

record extracted features with different arrangements of texts.

3. Extracting markers of style from the text: features related to time, such

as verse length, increases against time gradually.

4. Represent markers of style in specific order.

29

4.2 Collecting the corpus

A corpus is a big set of data for the purpose of analysis using computational

linguistics techniques.

Deciding which corpus to work with is another issue because there are

several electronic versions that are available online. And those versions are

different in terms of the numbering systems they used in numbering the

verses. For example, whether “Bismillahi-rraHmani-rraHeem” may be

included in a Sura or not. In Medina Mushaf, it is only included in the

beginning of Sura number no 1.

The famous project that provided a verified copy of the Holy Quran is the

Tanzil Project, which is connected to Edina Mushaf [29]. Tanzil offers several

types of Quran text, such as simple, Uthmanic, with diacritics or not, and

pause marks, as well as in different file format like XML, SQL dump file, or

text file. Tanzil numbers verses in each Sura according to Medina Mushaf by

including the verse number and Sura number. This way makes the searching

in the Quran easy because we do not need to look to all 6236 verses to find a

verse; instead we just enter the Sura number and verse number. For

example if we want to refer to verse number 3 in Sura number 2 we type

(2:3).

Figure 8: the xml file downloaded from Tanzil web site, it has 114 Sura and each Sura has several verses(aya)

30

I used a version of Tanzil with Jquran Tree library from [11]. This API provides a

set of functions to access the Quran text with several formats like text with

diacritics, removed diacritics text and Bukwalter transliteration. It also offers an

orthographic model that provides not just a verse by its location but a specific

word; you just need to provide the word location. For example, to get the third

word in the Sura number 113 and verse number 3, you just need to write the

following lines.

Figure 9 show an example of how to obtaina specific token using JquranTree in different format.

Output:

Format Output

RemoveDiacritics غاسق

Unicode ٍَغاِسق

Buckwalter gaAsiqK

4.3 Pre-processing

Before conducting any experiments, a pre-processing work was done for the

Quran text to investigate the most frequent words. I wrote a code to extract the

frequencies list of each word in the Holy Quran in order to see the most

significant words. First, all verses were written to a text file to get the

frequencies of every single word for mining the data.

31

Figure 10:this function recieves an array of verses and filename, then it write these verses to the a given filename.

This process is required for the following function. WordLists is the function

responsible for calculating the number of occurrences for all tokens provided in

the text file.

Figure 11: A procedure that obtain the word occurrences in a given file

This function tokenizes the word and computes its frequencies in the provided

file.

32

For example, assume I provide a file that has the following text:

The key of my car is here. I lost the key of my house.

WordList would return something like the following:

Word Occurrences The 2 Key 2 Of 2 My 2 Car 1 Is 1 Here 1 I 1 Lost 1 House 1

Table 4: shows most frequent words in the text in descending order.

Applying pre-processing for Quran text:

1-10 11-20 21-30

من 2589

هللا 2153

ان 1603

فى 1185

ما 1010

812 �

الذين 811

ا� 763

و� 658

وما 646

علٮا 428

قال 416

لھم 373

ثم 340

لكم 337

ومن 337

كان 333

وان 322

بۦه 298

بما 296

قل 294

ا�رض 287

او 280

ذالك 280

الذى 268

الٮا 265

ھو 265

ءامنوا۟ 263

ھم 261

على 258

Table 5: 30th

most frequent words in the Quran

After we know the way to access the Quran texts in several formats we can get

some features. An easy example of one feature is the Mean Verse Length. This

can be obtained using a loop starting from 1 to 114 (due to there being only 114

Suras), then taking an inner loop depending on the verses that a Sura has.

However this will give the features with the traditional order of the Holy Quran.

33

The scheme we need to work with is described in section 2.3 and is different

from this scheme. Some Suras have been divided into several blocks and others

taken intact. Therefore I encoded the specific order in a text file and read the

verse number from that file.

Figure 12: the text file used to read the verses order

The left-most number is the block number; notice line number 8 and 9 has the

same block. Line number 8 means take the verses from 1 to 5 from Sura

number 88 and assign it in block number 8. Line number 9 means take the verse

from 8 to 16 from the same Sura and assign it in block 8.

This way of computing features was used in the early stage of this project when

we needed many files for computing features according to the order encoded in

the text file. After that we created a database to record the verses and features

in order to exploit the Structure Query Language (SQL) and its built-in functions

in searching and ordering.

4.4 Design and create a database

In order to represent the style of several markers within different temporal

groups of text, I constructed database with the following design.

34

Figure 13: ERD diagram for the database

There are only two tables. The first is Chapters, which represents the Suras. It

has Sura name and its number. The second table is the important one called

Verses (Aya). Here we recorded 6236 verses along with several markers and

orders. An example can be seen in Figure 7; Marker1, Marker2, and Marker4 are

word counts, and the symbol of Fatha and Kasrah have been computed for each

verse. Order5 is the revelation order adapted from [29]. Order33 field is the

order proposed by Bazargan and order44 the 7-phases order or Bazargan

modified order.

Figure 14: shows several different order and markers for each verse.

After computing some markers with orders, I can use SQL to produce these

combinations of ordered markers. For example, assume I want the style of

Marker1 with the order44; I only need to write the following SQL statement.

35

This will produce a vector of words count for the order4. Then, it can be plotted

to observe the pattern of the style. I can use others built in functions that SQL

offer like avg. It is not necessary to add the command “order by” if we use

“group by” due to this function’s ability to sort the rows according to the field

used in “group by”.

Output:

1 1253 We divided 6236 verses into 7 groups according to the

description in section 2.5, these results will be analysed

later in chapter 5.

2 3910

3 3199

4 3615

5 23841

6 28910

7 11745

This process requires a previous process to record the markers and

arrangements to the Verses table.

To do so, the following code is used for building Insert SQL statement for each

verse and sending it to the function ExcuteQuery that will record the verses into

the the Database.

Figure 15: Buliding Insertion SQL statement

I made the process of extracting features and recording them automatic. Let me

explain that by an example. Assume we want to find the frequencies of God’s

36

names such as “Al-rahman” and “Al-raheem”. To do so, the following code is

responsible for it

Figure 16: computing the occurrences for a word considering multiple synonyms

It is divided into two parts, the first being responsible for computing the

frequencies for a given list of words in a provided file and regular expression.

The results of this part create an array of frequencies for each verse. In this

example we use a list of 99 names for Allah in the provided file. pFix and sFix

were used to consider the boundaries of these words.

The second part is responsible for building an SQL statement and performing it

in order to record this marker into the database.

The Markers function receives the text format used in the search; in this case I

type 1, which refers to Arabic removed diacritics text. This function invokes the

function of Key_Words, which retrieves a list of keywords that are recorded in a

given file. Then these keywords are passed to the function CountOccurences,

which returns the number of occurrences for them in the given format text using

regular expression provided.

37

Figure 17:Markers function which return an array of frequencies for a given keywords and regular expression

Figure 18: calculate the number of occurrences of provided array (needle) in a given text ( haystack)

4.5 Basic Markers

Word count is the easiest one among all the features that can be extracted using

String functions with any programming language. Java provides many functions

to manipulate with the strings variables such as split function that divides the

text into tokens depending on the regular expression provided to the function.

For example, to calculate the number of words in verse number 3 in the Sura

number 1, the following code will illustrate this. MVL calculated using the

following formula:

38

MVL =��

��

One method to calculate the tokens number in a verse is listed below.

String arr[] = Document.getChapter(1).getVerse(3).toBuckwalter().split(" ");

System,output.println(arr.length);

Figure 19: compute the words number in a verse

An Alternative and easy way to us JquranTree as follow:

System.out.println(Document.getChapter(1)..getVerse(3).getTokenCount());

Figure 20: using JquranTree tokenizer

select avg(Marker1) from verses group by order22;



Figure 21: retrive the Marker1 according to three different divided text

Vowels markers Fathah, Dammah, Kasrah also using similar procedures as

explained above.

Fatha frequencies =��

��

Other way to calculate this marker by creating a file that only has a white space

and run the following function:

39

4.6 Occurences of Allah names

Assume we have a vector V of words that refer to Allah.

To compute the frequencies of these names is as shown in the below:

Allah names frequenciesin phase a =∑ ��

��

4.7 Conceptual markers

The concept of Allah includes that every verb related to him such as in (112:4)

“Nor is there to Him any equivalent”. The name of Allah is not specifically in this

verse but ”Him” refers to Allah, therefore this verse has a concept of Allah.

I used HTTPWebRequest class that is supported by Java to read contents from a

web application that provides a list of the Allah concept in the Quran and its

locations. Then I transferred contents to the database. [23] Offfers a list of

verses that have a concept of this entry word.

Figure 22: taken from (http://www.textminingthequran.com/apps/referents.php?con=1 ) shows a list of the concept of

Allah from , there are 3061 word related to Allah in the Quran according to TafsirIbnKhathir.

40

The following code was used to transfer the frequencies to the verses table in

the database.

Figure 23: the function that is the responsibe to return the concept frequencies of a given word.

4.8 Related verse

Related verses based on the information from Tafser Ibn Kathir. We just collect

directed related verses from [23] using same technique in conceptual markers.

41

Figure 24: extraxting the feature of related verses

4.9 Relative frequencies of Part-of-Speech tagset in the Quran

We employ the Quranc Arabic corpus Part-of-Speech tags shown in the following

table in the project. I also used here the same techniques as used in 4.3, 4.4

number to extract the morphemes frequencies for a token.

42

No Tag Frequency Description

1 N 25137 Noun

2 PRON 24691 Personal pronoun

3 V 19356 Verb

4 P 13007 Preposition

5 CONJ 9450 Coordinating conjunction

6 PN 3911 Proper noun

7 REL 3575 Relative pronoun

8 REM 2925 Resumption particle

9 NEG 2688 Negative particle

10 ACC 2283 Accusative particle

11 ADJ 1961 Adjective

12 EMPH 1244 Emphatic lam prefix

13 T 1166 Time adverb

14 DEM 1059 Demonstrative pronoun

15 COND 1049 Conditional particle

16 INTG 946 Interogative particle

17 SUB 684 Subordinating conjunction

18 LOC 669 Location adverb

19 RES 558 Restriction particle

20 CERT 414 Particle of certainty

21 VOC 376 Vocative particle

22 RSLT 350 Result particle

23 PRO 332 Prohibition particle

24 PRP 319 Purpose lam prefix

25 CIRC 293 Circumstantial particle

26 SUP 235 Supplemental particle

27 PREV 162 Preventive particle

28 FUT 161 Future particle

29 RET 122 Retraction particle

30 EXP 104 Exceptive particle

31 INC 90 Inceptive particle

32 CAUS 88 Particle of cause

33 IMPV 78 Imperative lam prefix

34 EXL 66 Explanation particle

35 AMD 65 Amendment particle

36 INT 47 Particle of interpretation

37 ANS 40 Answer particle

38 EXH 40 Exhortation particle

39 SUR 35 Surprise particle

40 AVR 33 Aversion particle

41 INL 30 Quranic initials

42 EQ 6 Equalization particle

43 COM 3 Comitative particle

44 IMPN 2 Imperative verbal noun

Table 6: Part-of-Speech tags used in the Quranic Arabic Corpus http://corpus.quran.com/

43

Relative frequency of a tag is the number of occurences for this tag in the text

divided by total number of tags.

An example of computing relative frequency of Noun in the phase 7 is shown

below:

Relative frequency of Noun in phase 7 =��

��

Figure 25: a function receives location and returned an array of Part-of-Speech tags.

I type the location (6:113:8) this means the 8th token in verse number 113 of

sura number 6. This word has 5 morphemes as the following output shows:

The following figure shows the output for first verse in the Quran. The (bisomi

{ll¬ahilr¬aHoma’nlr¬aHiymi) it is clear that it has 4 words and 5 morphemes

and 3 types of part-of-speech tagsets.

44

Figure 26: Part-of-Speech information tags

Another example for extracting feature from the text:

I prepared a file that contains a list of questions in Arabic and provide that file to

the function as can be seen below.

Figure 27: shows how to extract the question feature in each verse as well as record it to the database.

The difficulties I confronted here are that Arabic text has different spelling in

several question words; for instance, the word أأسلمتم would be written as ءاسلمتم

and the word ارأيت would be ارءيت.

4.10 28th most frequent morphemes in the Quran

Most frequent morphemes in the Quran are shown in the following table:

No Morpheme Meaning Description

1 Wa And prefixed conjunction 2 I /e/ or /i/ Kasrah, Sound like e or i 3 L For Preposition 4 U /u/ or /o/ Dammah, Sound like o or u 5 A /a/ Fathah, Sound equivalent a 6 An About Double Fatha 7 Min From Preposition 8 Una 3rd person plural personal

pronoun 9 Fa then, and so prefixed resumption particle

45

10 Hum they 3rd person masculine plural personal pronoun

11 Llah God’s name Allah 12 Ma 13 In 14 Bi prefixed preposition 15 Un nominative feminine indefinite

noun 16 La 17 Kum Masculine plural Enclitic pronoun 18 Hu Him 3rd person masculine singular

possessive pronoun 19 La 20 Fi In prefixed preposition 21 Ina 22 Ka prefixed preposition 23 Hi him 3rd person masculine singular

object pronoun 24 Li to indirect

object prefixed preposition

25 Ha Her 3rd person feminine singular object pronoun

26 Inna accusative particle 27 Na Our Enclitic pronouns 28 alladina who masculine plural relative

pronoun Table 7:28 most frequent morphemes based on [1]

Relative frequency of a morpheme is the total of occurences these morphemes normalise by the all

28 morphemes.

4.11 Relative frequencies of vowels

No Vowel Frequency Description

1 a 122948 Fatha,Sound equivalent to a 2 i 45970 Kasrah, Sound like I or e 3 u 37320 Dmmah, Sound like u or o 4 aa 15955 Sound aa 5 ii 4194 Sound ii 6 final an 3741 Double Fatha 7 final in 2633 Double Kasrah 8 final un 2519 Double Dammah 9 uu 2034 Sound uu

Table 8: 9th

vowels used in relative frequencies of vowels

Similar to the releative frequencies of morphemes and tags, we normlise by total

number of all vowels that appeare.

Notice: there are further implementations in appendix G.

46

Chapter 5

5. Results and Evaluation

In this chapter I present and evaluate the results of the project. I chose a set of

criteria to judge the success of this project. In addition, I am going to address

any limitations I have encountered during the project.

5.1 Results

I divided this section into three parts; the first part shows the results according

to blocks division. The second presents the results for 22 groups of consecutive

texts. Finally, the last part is according tothe 7 phases chronology proposed by

[1].

5.2 Experiment One: arrangements of 194 blocks

Figure 28: The Mean Verse Length for 194 blocks according to scheme of blocks described in [1]

It is clear that the verse length increases in coherence with the Bazargn’s blocks

except for the three blocks (110, 132 and 179). This confirms the claim that

says the length of a verse tends to increase with time.

0

20

40

60

80

1

10

19

28

37

46

55

64

73

82

91

10

0

10

9

11

8

12

7

13

6

14

5

15

4

16

3

17

2

18

1

19

0

Mean Verse Length

47

Figure 29: representsblocks from 108 to 137 using MVL with three vowel symbols as well as the count of morphemes in

the block.

The results for the other four markers show a similar pattern. There are two

peaks at 110 and 132 and one valley at 179. However, the overall trend is a

gradual increasing over 194 blocks or time. However, this similarity may due to

the dependency between markers and the word count. The first peaks occurs at

block number 110 which has only one verse the 31st verse of Sura 74. This verse

is different to these verses that were revealed at Mecca due to its long length.

The second peak occurs at 132, which belongs to the period of Mecca but has a

long length as well.

Figure 30: represents blocks from 176 to last block using five markers.

In this figure, the increase in length is even clearer than in the previous one.The

decline at 179 may be because this block has only three verses, belonging to

Sura number 110. Despite that Sura was revealed in Medina according to the

revelation order in the appendix E its verses are not as long as typical Medina

verses.

48

The only explanation for this similarity is that other markers, such as vowel

symbol and morphemes, depend on the marker of MVL because the morphemes

and symbols are components of a word. A greater number of words would

increase the number of their components.

It seems that taking one of these markers to prove the validity of this

arrangement is not sufficient due to dependence on the words count by others.

All markers related to the composition of the word may be dependent on the

marker of MVL because it basically has a more words depicting more morphemes

and more vowel symbols.

Figure 31: the frequencies of most frequent word in the Holy Quran “ Allah “.

This graph also shows an increase but slightly different trend in comparision with

the previous five markers. This marker is not dependent on the word count as

were previous markers. The differences between them are that the vowel

symbols and morphemes occur in almost every word in the Quran, while the

word “Allah” is repeated 3000 times out of the 77430 words in the Quran.

Despite of this difference it shows similar pattern that five markers show over

same division.

0

1

2

3

4

5

6

7

8

1 9

17

25

33

41

49

57

65

73

81

89

97

10

5

11

3

12

1

12

9

13

7

14

5

15

3

16

1

16

9

17

7

18

5

19

3

The frequencies of (Allah)

49

Figure 32, shows the frequencies of words that related to the concept of Allah over 194 blocks division.

This marker does not support this method of division in comparing with others

markers. The pattern is not showing increasing of this feature over the blocks

division.

Figure 33: the frequencies related verses over 194 blocks.

Related verse marker has less fluctuation than marker related to the concept of

Allah. It increases in different way of previous features.

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1 8

15

22

29

36

43

50

57

64

71

78

85

92

99

10

6

11

3

12

0

12

7

13

4

14

1

14

8

15

5

16

2

16

9

17

6

18

3

19

0

19

7

concept of allah

0

2

4

6

8

10

12

14

1

11

21

31

41

51

61

71

81

91

10

1

11

1

12

1

13

1

14

1

15

1

16

1

17

1

18

1

19

1

related verse

related verse

50

In order to evaluate these results using the Meccan-Medinan criterion, I

calculated the number of verses revealed in Mecca and in Medina for each block.

Then, if I assumed that the Meccan verses were sent down before the Medinan

verses, the number of Meccan verses will be larger in the first half of the blocks,

and Medianan verses will be larger in the other half.

Figure 34: the number of Meccanverses in each block

The percentage of verses that were revealed in Mecca in blocks 1 to 140 is much

larger than the percentage in the later blocks. This means that there is a clear

agreement with the Meccan-Medinan arrangement of texts.

5.3 Experiment number two: Groups

Figure 35: shows different markers according to groups level, similar pattern can be seen for first four markers.

0

10

20

30

40

50

60

70

80

90

100

0 20 40 60 80 100 120 140 160 180

Meccan Verses

0

10

20

30

40

50

60

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

MVL

fatha

Damma

Kasrah

morphemes

51

Five dependant’s markers show increasing over 22 consecutive texts.

Figure 36: the occurance of Allah in each group of text

The occurrence of “Allah” is increasing over the 22 phases. Although there are

some fluctuations between phases 11 and 16, the overall trend shows an

agreement with the dependant markers fatha, Damma, Kasrah and morphemes

number that influenced by the words count.

Figure 37: occurance of word related to the concept of allah according to 22 groups division.

This confirms that this marker does not support this chronology

0

0.5

1

1.5

2

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

Allah

0

0.05

0.1

0.15

0.2

0.25

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

concept of allah

52

Figure 38: the number of verses that directly related to the verses in the group.

Related verses marker does not support the 22 groups.

The relative frequency of Part-of-speech-tag set

No N PRON V P CONJ PN REL REM NEG ACC ADJ

22 16.90 16.07 12.87 9.25 6.06 3.58 2.81 2.26 1.76 1.11 1.23

17 17.34 19.53 13.98 9.86 7.14 3.70 2.99 2.49 1.78 1.47 1.57

11 17.62 19.97 15.55 10.19 6.78 2.46 2.19 1.82 2.18 1.87 1.38

10 17.64 20.98 16.08 9.99 7.16 2.98 2.61 2.35 1.92 1.76 0.97

21 17.81 17.27 13.41 9.49 5.70 3.65 2.63 3.19 1.82 1.48 1.22

16 18.35 20.22 15.39 10.53 6.94 2.93 3.11 1.79 2.25 1.55 1.23

13 18.54 18.89 15.06 9.60 6.85 3.82 3.12 2.42 1.96 2.14 1.37

20 18.63 18.41 14.60 9.58 6.77 3.52 2.48 2.71 1.74 1.12 1.86

18 18.73 18.04 14.83 9.95 7.60 4.00 2.93 2.39 2.13 1.19 1.53

19 18.80 17.08 14.61 10.00 7.76 4.16 3.34 1.58 1.99 1.55 1.87

15 19.09 17.67 15.19 10.51 6.18 4.74 3.15 3.19 1.97 1.87 1.27

9 19.11 19.83 14.67 10.19 7.24 2.69 2.86 1.98 2.15 1.79 1.23

14 19.19 18.85 14.39 11.13 7.09 3.49 3.47 2.05 2.23 1.94 1.79

7 19.34 19.37 16.49 9.68 7.44 1.81 3.04 2.07 2.43 1.45 1.48

8 20.29 18.93 15.70 9.63 7.95 2.73 2.94 1.87 2.27 1.95 1.51

12 20.55 17.80 14.49 11.76 8.11 3.43 3.67 1.64 2.28 1.84 1.74

6 20.91 21.05 14.89 9.95 8.71 2.19 2.29 1.69 2.05 2.07 1.19

5 21.23 21.31 14.45 10.18 7.65 1.53 2.10 2.05 2.34 2.03 1.71

4 22.57 21.70 15.54 10.15 7.43 1.75 1.81 2.85 1.71 2.66 1.58

3 23.81 19.50 14.56 9.79 8.05 1.47 1.89 2.60 2.27 2.74 2.20

2 24.53 15.15 17.22 8.87 10.32 1.24 2.13 1.87 2.75 1.76 2.54

1 27.47 12.40 15.75 6.87 13.57 1.51 2.85 1.51 2.35 2.35 4.19 Table 9: most 11th frequent tags in the Quran aacording to the order proposed by Bazrgan

0

0.5

1

1.5

2

2.5

3

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

related verse

53

Relative frequent markers show different results from basic markers that may

depend on the word counts. With this marker, I saw an increase in almost

reverse order of the 22 groups. It can be seen that there are three markers—N,

CONJ, and ADJ—that support this arrangement.

Figure 39: Three relative frequency of Part-of-speech tags

Figure 40: the percntage of Meccan verses that each group has.

Bazrgan’s chronology divides the text into 22 groups, from 1 to11 belonging to

Mecca, and 12 to 22 referring to Medina. In this figure, it is clear that the

percentage of Meccan verses is above 80% in groups 1-12, and this percentage

declines in the later groups, most of which belong to the Medina period.

0.00

5.00

10.00

15.00

20.00

25.00

30.00

22 17 11 10 21 16 13 20 18 19 15 9 14 7 8 12 6 5 4 3 2 1

N

CONJ

ADJ

0

20

40

60

80

100

120

140

0 5 10 15 20 25

54

5.4 Experiment number three: Passages, or 7 phases

Passage no MVL fatha Damma Kasrah morphemes

concept of Allah Allah

related verse

1 3.6506 6.2784 1.4744 2.0256 5.4773 0 0.02 0.3608

2 4.579 7.7691 2.0829 2.8564 7.0674 0.0298 0.04 0.6939

3 6.6653 10.574 3.1684 3.854 10.6673 0.0426 0.05 0.645

4 8.3944 13.3318 3.8167 4.8654 13.8051 0.0696 0.05 0.9072

5 13.1773 21.1552 6.0359 7.7309 22.1818 0.1066 0.29 1.3171

6 17.8011 27.7882 8.9608 10.7717 29.7479 0.1365 0.88 1.7625

7 24.4179 38.237 12.3888 14.2328 43.8586 0.0894 1.34 1.79

Table 10: shows 7 passage of texts increase dramatically according to the 8 different features

The average number of tokens per passage or MVL can be seen to be clearly

increasing gradually from passage number 1 to 4, then a sharp increase starts at

passage number 5.

The 7-phases chronology was supported by almost all markers in the table

above. The two chronological-order blocks and groups are supported by the

markers MVL, Fatha, Damma, Kasrah, morphemes number, and the occurrence

of “Allah”. Conceptual occurrence of “Allah” and related verses does not support

these divisions of text.

Table 11: Meccan and Medinan verses occurrence in each passage

Passage no Meccan Medinan

1 130 0

2 352 64

3 841 22

4 471 31

5 400 135

6 1675 956

7 678 415

8 66 0

55

The order of these passages seems to support the claims of many scholars that

a word’s use increases over time in the Holy Quran. This table also show that

Meccan verses are decreasing and the Medinan ones are increasing in this order,

and this is another support because the Meccan verses were sent down before

the Medinan verses, according to the historical information. On the other hand, it

seems that the passages have mixed verses from different periods.

Figure 41: the percentage of Meccan verses in each passage it is clearly that the percentage of Meccan verses are higher

from passage 1 to 6.

In this section, we show the relative frequencies of 11 most frequent of the 44

morphemes.

N PRON V P CONJ

4 9021.429 9057.143 6142.857 4328.571 3250

1 11825 7300 8300 4275 4975

3 16957.14 16300 11671.43 7628.571 5585.714

7 19736.84 19142.11 15121.05 10484.21 6852.632

6 20765.91 20418.18 16318.18 11465.91 7950

2 30460 24940 18620 12520 10300

5 764000 804800 626900 399200 300900 Table 12: Relative frequencies of 11 most frequent tags List 1

0

20

40

60

80

100

120

140

0 2 4 6 8 10

56

PN REL REM NEG ACC ADJ

4 650 892.8571 871.4286 992.8571 864.2857 728.5714

1 600 1025 900 1325 850 1225

3 1314.286 1357.143 2142.857 1285.714 2000 1185.714

7 3978.947 2931.579 3021.053 1968.421 1373.684 1589.474

6 4211.364 3540.909 2443.182 2281.818 1850 1686.364

2 1880 2420 3320 2900 3500 2820

5 99200 106100 79300 86900 72400 51700 Table 13: Relative frequencies of 11 most frequent tags list2

Table 12 and 13 shows the results of the relative frequency of the 11 most

frequent Tagsets in the Quran. For example, the relative frequencies of Nouns

for verse number 1 in Sura number 1 in the Quran (bisomi {ll~ahi

{lr~aHoma`ni {lr~aHiymi) can be seen below.:

Relative frequency of Noun =�� !��

��× 100 in this case it equal to

%

& ×

100 = 20 Notice that “somi” is a Noun while “ll~ahi” is Proper Noun.

The most significant finding in this part is that different relative frequencies of

morphemes increase in different orders proposed in [1].

Figure 42: shows three most frequent vowel symbols in Arabic language, x passages ordering according to the timeline

and y is the frequencies of these symbols.

This figure also shows an increasing pattern, which means that these markers

are in support of the hypothesis word length tends to increase over time.

However, these markers may have been influenced by the marker of word

0

5

10

15

20

25

30

35

40

1 2 3 4 5 6 7

fatha

damma

kasrah

57

length because the more the number of words that formed the verse, the more

the number of vowels that would be there. Therefore, the dependency between

word length and vowel symbols is very clear here.

This marker also has a similar pattern to previous ones. It may be because of

the dependency due to a word containings one morpheme or more.

5.1 Relative frequencies of 11 most frequent tags

Figure 43: relative frequencies of Noun, Verb, Conjective

and Adjective over reversal 7 phases order

Figure 44: Three part-of-speech tagset within level of

Passages

Figure 43 and 44 show the most significant results, which depict that the 7

phases are increasing monotonically in a reverse order.

Limitation

The results have been affected by the method used in carrying out this study.

There is no project which is perfect with its results showing 100% success and

this project is no exception. There are some limitations which have been noticed.

The first limitation in our methods is the use of tokenise the corpus which gives

different results [1]. I have noticed slightly different results that were obtained

by JQuran Tree from the kenization process in the library JQuran Tree.

0

5

10

15

20

25

30

7 6 5 4 3 2 1

N

V

CONJ

ADJ

0

5

10

15

20

25

30

7 6 5 4 3 2 1

N

CONJ

ADJ

58

Sura Number Number of word obtained using JQuran

Tree

Number of Words from[1]

37 861 865

36 725 729

21 1169 1174

25 893 896

27 1151 1158

11 1917 1945

29 976 977

Table 14: The variation of the number of words from experiment done in [1]

The only matched results are for Sura number 57 and 13.

Second limitation, is in the method of computing five dpendants marker. We

normalise by number of verses in the phase instead of the total number of

marker in all phases. Verses number decrease in latest phases, which means

dividing by small number. Thus the marker increases dpepending on the number

of verses.

59

Chapter 6

6. Conclusions

In this chapter, I summarise the findings in respect to the initial aims and the

objectives of this project. In addition, I suggest further works based on this

project.

The aim of this project was to identify features related to the temporal ordering

of the Holy Quran. I collected a verified copy of the Holy Quran and divided it

into three different arrangements. The first one arranges the text into 194

blocks, which is explained in detail in the background chapter. The second

division is 22 phases, which is the chronology proposed by Bazargan, while third

is the modified Bazargan. I also applied some markers of style to identify

whether these markers support the arrangements or not.

The basic markers that are dependent on the words count including Mean verse

length, the three most common vowel symbols in Arabic, the number of

morphemes, and the occurrence of “Allah”, support these texual arrangements.

In contrast, blocks and groups arrangements do not appear to be supported by

other markers like the conceptual occurrence of “Allah” and related verses.

In addition, the relative frequencies for 11th most frequent tags support the

reversal order for the 7-phases’ chronology. And the relative frequencies for 28

most common morphemes show a different order.

It seems the modified Bazargan’s chronology is supported by only dependant

markers, except for conceptual frequencies of “Allah”, which is not dependant on

word count.

As a result of these findings, an API has been produced to test several markers

computed during the implementation of the project, as well as a web user

interface to make the expirements available for interested researchers.

60

6.1 Future works

If I had more time, I would compute the markers of tajweed and pause markers

that could be an alternative to verse numbering systems, which our project is

based on. The pause markers or the system of stop and start, do not have big

variation as verses have, therefore it is worthable to be considered.

We use the criteria of agreement to evaluate the results. The suggestion for

future works could be improved by the agreement between the proposed order

and historical information.

i

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iv

Appendix A

Appendix A: Personal Reflection

There were certainly challenging moments encountered during my work on this

project. These challenges have changed my mind and improved my experiences.

One of the challenging parts of the project was the management of time; I

needed to change my planning twice as the implementation stage was increased.

I think it is important to divide the main tasks into small units and it is crucial to

know when to start and stop working on these subtasks. As some tasks are not

clear during the early stage of the project, as to the number of hours required,

the first timetable will be modified while the project progresses. In order to

avoid excess modifications, it is important to start early and allow some gaps

between the subtasks so that such a modification does not affect other tasks. It

is also a good practice if you construct an alternative plan in case the initial plan

fails.

An example of what have changed my mind that, I thought, If work continuously

without having some rest would finish early, and keeping me connected with the

tasks of the project. But what happened with me in this project is the reverse. I

did not enjoy weekends from 15 of june until 16 of august. Therefore, any

students reading this should not miss weekends or at least one day a week in

order to increase your activity.

Despite that my background is in web developing, I enjoyed this project. This

project allows me to see web as I have never seen before. My previous works

dealing with issues like designing a form or a service that allows user to post or

retrive contents. But this project gave me enthusiasm to explore more about the

textual content of web. I am looking to finish this project to looking for another

idea that has just corssed my mind. Overall, I think this project was a start

toward the researching life.

v

Appendix B:

Appendix B: Interim Report

The interim report is submitted with the hard copy only.

vi

Appendix C:

Appendix C: Feedback

vii

Appendix D

Appendix D: Figures

viii

Appendix E:

Appendix E: Text arrangements used in the project

Groups:

Group 1: blocks{2-16}, Group 2: blocks{17-34}, Group 3: blocks{1,35-65},

Group 4: blocks{66-82}, Group 5: blocks{83-91}, Group 6: blocks{92-101},

Group 7: blocks{102-110}, Group 8: blocks{111-116}, Group 9: blocks{117-

121}, Group 10: blocks{122-126}, Group 11: blocks{127-131}, Group 12:

blocks{132-138}, Group 13: blocks{139-143}, Group 14: blocks{144-150},

Group 15: blocks{151-154}, Group 16: blocks{155-160}, Group 17:

blocks{161-164}, Group 18: blocks{165-167}, Group 19: blocks{168-174},

Group 20: blocks{175-178}, Group 21: blocks{179-183}, Group 22:

blocks{184-194}

Passages:

Passage 1: group{2}, Passage 2: group{3}, Passage 3: group{4}, Passage 4:

group{5}, Passage 5: group{6-11}, Passage 6: group{12-19}, Passage 7:

group{20-22}

Blocks:

Block number Sura From To

1 96 1 5

2 74 1 7

3 103 1 2

4 51 1 6

5 102 1 2

6 52 1 8

7 112 1 4

8 88 1 16

ix

9 86 11 17

10 82 1 5

11 91 1 10

12 108 1 3

13 87 1 7

14 85 1 22

15 81 1 29

16 94 1 8

17 93 1 11

18 114 1 6

19 79 1 26

20 74 8 10

21 92 1 21

22 107 1 7

23 70 5 18

24 91 11 15

25 77 1 50

26 78 1 36

27 74 11 56

28 106 1 4

29 53 1 25

30 89 1 30

31 84 1 25

32 80 1 42

33 104 1 9

34 109 1 6

35 96 6 19

36 88 6 26

37 75 7 40

38 95 1 8

39 75 1 19

40 56 1 96

41 55 1 76

42 87 8 19

43 1 1 7

44 100 1 11

45 69 38 52

46 79 27 46

47 111 1 5

48 113 1 5

49 90 1 20

50 102 3 8

51 105 1 5

52 68 1 16

53 89 15 26

54 99 1 8

x

55 86 1 10

56 53 33 62

57 101 1 11

58 37 1 182

59 82 6 19

60 69 1 37

61 70 19 35

62 83 1 36

63 44 43 59

64 23 1 11

65 26 52 227

66 38 67 88

67 15 1 99

68 69 4 12

69 97 1 5

70 51 7 60

71 54 1 55

72 68 17 52

73 44 1 42

74 70 1 44

75 52 9 28

76 43 66 80

77 71 1 28

78 55 8 78

79 73 1 19

80 20 1 52

81 19 75 98

82 52 21 49

83 15 6 48

84 26 1 51

85 76 1 31

86 38 1 66

87 50 1 45

88 36 1 83

89 103 3 3

90 23 12 118

91 41 1 8

92 43 1 89

93 33 1 68

94 21 1 112

95 72 1 28

96 78 37 40

97 85 8 11

98 19 1 74

99 98 1 8

100 31 1 11

xi

101 30 1 27

102 25 1 77

103 20 53 135

104 67 1 30

105 14 42 52

106 19 34 40

107 16 1 128

108 18 1 110

109 32 1 30

110 74 31 31

111 17 9 111

112 40 1 60

113 2 1 245

114 27 1 93

115 39 29 66

116 45 1 37

117 64 1 18

118 11 1 123

119 41 9 36

120 30 28 60

121 17 1 100

122 7 59 206

123 24 46 57

124 22 18 69

125 6 1 117

126 29 1 69

127 34 10 54

128 10 71 109

129 38 26 29

130 12 1 111

131 28 1 88

132 73 20 20

133 40 7 85

134 53 23 32

135 18 29 59

136 31 12 34

137 14 1 41

138 42 1 53

139 2 30 195

140 35 4 45

141 39 1 52

142 47 1 38

143 8 1 75

144 61 1 14

145 41 37 54

146 17 53 70

xii

147 46 1 28

148 16 33 119

149 5 7 40

150 62 1 11

151 3 32 180

152 63 1 11

153 22 1 78

154 3 1 200

155 7 1 176

156 59 1 24

157 39 67 75

158 34 1 9

159 9 38 70

160 10 1 70

161 57 1 29

162 16 90 97

163 24 1 34

164 2 40 152

165 33 4 73

166 4 44 175

167 6 31 165

168 13 1 43

169 9 71 129

170 48 1 29

171 65 8 12

172 5 51 86

173 49 1 18

174 28 76 84

175 4 1 126

176 18 9 28

177 9 1 37

178 46 15 35

179 110 1 3

180 14 6 31

181 58 1 22

182 5 27 120

183 2 21 283

184 60 1 13

185 35 1 18

186 66 1 12

187 6 135 153

188 65 1 7

189 4 127 176

190 24 35 64

191 5 12 50

192 2 164 286

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193 33 53 55

194 5 1 6

Chronological Order of Suras from Tanzil project

Order Sura Name Number Type Note

1 Al-Alaq 96 Meccan

2 Al-Qalam 68 Meccan Except 17-33 and 48-50, from Medina

3 Al-Muzzammil 73 Meccan Except 10, 11 and 20, from Medina

4 Al-Muddaththir 74 Meccan

5 Al-Faatiha 1 Meccan

6 Al-Masad 111 Meccan

7 At-Takwir 81 Meccan

8 Al-A'laa 87 Meccan

9 Al-Lail 92 Meccan

10 Al-Fajr 89 Meccan

11 Ad-Dhuhaa 93 Meccan

12 Ash-Sharh 94 Meccan

13 Al-Asr 103 Meccan

14 Al-Aadiyaat 100 Meccan

15 Al-Kawthar 108 Meccan

16 At-Takaathur 102 Meccan

17 Al-Maa'un 107 Meccan Only 1-3 from Mecca; rest from Medina

18 Al-Kaafiroon 109 Meccan

19 Al-Fil 105 Meccan

20 Al-Falaq 113 Meccan

21 An-Naas 114 Meccan

22 Al-Ikhlaas 112 Meccan

xiv

23 An-Najm 53 Meccan Except 32, from Medina

24 Abasa 80 Meccan

25 Al-Qadr 97 Meccan

26 Ash-Shams 91 Meccan

27 Al-Burooj 85 Meccan

28 At-Tin 95 Meccan

29 Quraish 106 Meccan

30 Al-Qaari'a 101 Meccan

31 Al-Qiyaama 75 Meccan

32 Al-Humaza 104 Meccan

33 Al-Mursalaat 77 Meccan Except 48, from Medina

34 Qaaf 50 Meccan Except 38, from Medina

35 Al-Balad 90 Meccan

36 At-Taariq 86 Meccan

37 Al-Qamar 54 Meccan Except 44-46, from Medina

38 Saad 38 Meccan

39 Al-A'raaf 7 Meccan Except 163-170, from Medina

40 Al-Jinn 72 Meccan

41 Yaseen 36 Meccan Except 45, from Medina

42 Al-Furqaan 25 Meccan Except 68-70, from Medina

43 Faatir 35 Meccan

44 Maryam 19 Meccan Except 58 and 71, from Medina

45 Taa-Haa 20 Meccan Except 130 and 131, from Medina

46 Al-Waaqia 56 Meccan Except 81 and 82, from Medina

47 Ash-Shu'araa 26 Meccan Except 197 and 224-227, from Medina

48 An-Naml 27 Meccan

49 Al-Qasas 28 Meccan Except 52-55 from Medina and 85 from Juhfa at the time of the

Hijra

xv

50 Al-Israa 17 Meccan Except 26, 32, 33, 57, 73-80, from Medina

51 Yunus 10 Meccan Except 40, 94, 95, 96, from Medina

52 Hud 11 Meccan Except 12, 17, 114, from Medina

53 Yusuf 12 Meccan Except 1, 2, 3, 7, from Medina

54 Al-Hijr 15 Meccan Except 87, from Medina

55 Al-An'aam 6 Meccan Except 20, 23, 91, 93, 114, 151, 152, 153, from Medina

56 As-Saaffaat 37 Meccan

57 Luqman 31 Meccan Except 27-29, from Medina

58 Saba 34 Meccan

59 Az-Zumar 39 Meccan

60 Al-Ghaafir 40 Meccan Except 56, 57, from Medina

61 Fussilat 41 Meccan

62 Ash-Shura 42 Meccan Except 23, 24, 25, 27, from Medina

63 Az-Zukhruf 43 Meccan Except 54, from Medina

64 Ad-Dukhaan 44 Meccan

65 Al-Jaathiya 45 Meccan Except 14, from Medina

66 Al-Ahqaf 46 Meccan Except 10, 15, 35, from Medina

67 Adh-Dhaariyat 51 Meccan

68 Al-Ghaashiya 88 Meccan

69 Al-Kahf 18 Meccan Except 28, 83-101, from Medina

70 An-Nahl 16 Meccan Except last three verses 127-129, from Medina

71 Nooh 71 Meccan

72 Ibrahim 14 Meccan Except 28, 29, from Medina

73 Al-Anbiyaa 21 Meccan

74 Al-Muminoon 23 Meccan

75 As-Sajda 32 Meccan Except 16-20, from Medina

76 At-Tur 52 Meccan

xvi

77 Al-Mulk 67 Meccan

78 Al-Haaqqa 69 Meccan

79 Al-Ma'aarij 70 Meccan

80 An-Naba 78 Meccan

81 An-Naazi'aat 79 Meccan

82 Al-Infitaar 82 Meccan

83 Al-Inshiqaaq 84 Meccan

84 Ar-Room 30 Meccan Except 17, from Medina

85 Al-Ankaboot 29 Meccan Except 1-11, from Medina

86 Al-Mutaffifin 83 Meccan Last from Mecca

87 Al-Baqara 2 Medinan Except 281 from Mina at the time of the Last Hajj

88 Al-Anfaal 8 Medinan Except 30-36 from Mecca

89 Aal-i-Imraan 3 Medinan

90 Al-Ahzaab 33 Medinan

91 Al-Mumtahana 60 Medinan

92 An-Nisaa 4 Medinan

93 Az-Zalzala 99 Medinan

94 Al-Hadid 57 Medinan

95 Muhammad 47 Medinan Except 13, from during the Hijrah

96 Ar-Ra'd 13 Medinan

97 Ar-Rahmaan 55 Medinan

98 Al-Insaan 76 Medinan

99 At-Talaaq 65 Medinan

100 Al-Bayyina 98 Medinan

101 Al-Hashr 59 Medinan

102 An-Noor 24 Medinan

103 Al-Hajj 22 Medinan Except 52-55, from between Mecca and Medina

xvii

104 Al-Munaafiqoon 63 Medinan

105 Al-Mujaadila 58 Medinan

106 Al-Hujuraat 49 Medinan

107 At-Tahrim 66 Medinan

108 At-Taghaabun 64 Medinan

109 As-Saff 61 Medinan

110 Al-Jumu'a 62 Medinan

111 Al-Fath 48 Medinan While returning from Hudaybiyya

112 Al-Maaida 5 Medinan Except 3, from Arafat on Last Hajj

113 At-Tawba 9 Medinan Except last two verses from Mecca

114 An-Nasr 110 Medinan Last one, from Mina on Last Hajj

Noldeke arrangements:

Early Meccan

Nöldeke are: 96, 74, 111, 106, 108, 104, 107, 102, 105, 92, 90, 94, 93, 97,

86, 91, 80, 68, 87, 95, 103, 85, 73, 101, 99, 82, 81, 53, 84, 100, 79, 77, 78,

88, 89, 75, 83, 69, 51, 52, 56, 70, 55, 112, 109, 113, 114, 1.

Middle Mecca

The suras of the period are: 54, 37, 71, 76, 44, 50, 20, 26, 15, 19, 38, 36,

43, 72, 67, 23, 21, 25, 17, 27, 18.

Late meccan

The suras of this period are: 32, 41, 45, 16, 30, 11, 14, 12, 40, 28, 39, 29,

31, 42, 10, 34, 35, 7, 46, 6, 13.

Medina

The suras of the period are: 2, 98, 64, 62, 8, 47, 3, 61, 57, 4, 65, 59, 33, 63,

24, 58, 22, 48, 66, 60, 110, 49, 9, 5. 2

xviii

Appendix F:

Appendix F: Initial minimum requirements

• Re-implement the experiment described in (Sadeghi, 2011).

• Generate different permutations of text.

• Do same whether reversing the order provide monotonically increasing

or not. (is not an English sentence).

• Compute the markers used in (Sadeghi, 2011) essay.

• Represent the Quran in statistical

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Appendix G:

Appendix G: Web user interface

A web user interface has been developed in order to make the analysis have

been done during this project available for interested scholars. The form

developed using php programming language and supporting Ajax technologies.

It allows user to do epirements by coosing one of marker against a selected

order as well as, it offers four different normalisation variables that can be

applied.

This is a screenshot of the form published.

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This screenshot represent the three section that this interface provide; a form to

recive the marker, division, and the function of normalisation. The seconde

section, show the results in a table. Third section, plot the given table in 2

dimition.

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