Using a domain-ontology and semantic search in an eLearning environment Lothar Lemnitzer, Kiril...
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Using a domain-ontology and semantic search in an eLearning
environmentLothar Lemnitzer, Kiril Simov, Petya Osenova, Eelco Mossel and Paola
Monachesi
International Conference on Engineering Education, Instructional Technology,
Assessment, and E-learning(EIAE 07), December 2007
Outline of the Talk• Introductory notes
• LT4eL Domain Ontology
• Ontology-based Lexicon Model
• Semantic annotation of learning objects
• Semantic Search
• Evaluation
• Conclusions
Introductory notes (1)• LT4eL European project aims at
demonstrating the relevance of language technology and ontologies for improving learning management systems (LMS)
• Multilingual approach
Lexikon
CZ
CZCZEN
ENCONVERTOR 1
Documents SCORM
Pseudo-Struct.
Basic XML LING. PROCESSOR
Lemmatizer, POS, Partial Parser
CROSSLINGUAL RETRIEVAL
LMS User Profile
Documents SCORM
Pseudo-Struct
Metadata (Keywords)
Ling. Annot XML
Ontology
CONVERTOR 2
Documents HTML
Lexikon
PT
Lexikon
RO
Lexikon
PL
Lexicon
GE
Lexikon
MT
Lexikon
BG
Lexikon
DT
Lexicon
EN
PLPL
GEGE
BGBG
PTPT
MTMT
DTDT
RORO
ENDocuments User
(PDF, DOC, HTML,
SCORM,XML)
REPOSITORY
Glossary
Introductory notes (2)
We created and use
• A domain ontology
• Lexicons for several languages
• (Linguistically, semantically) annotated learning objects
for semantic search
LT4eL Domain Ontology: general issues
• The domain: Computer Science for Non-Computer Scientists
• The role of the ontology: indexing of the Los, semantic search
LT4eL Domain Ontology: creation
Keywordsannotation
BG
EN
PT
NL
MT
CZ
PO
RO
Translationinto EN
DefinitionCollection
Conceptcreation
Current state of the ontology
• about 750 domain concepts,
• about 50 concepts from DOLCE
• about 250 intermediate concepts from OntoWordNet
• about 200 new concepts extracted from LOs
Ontology-Based Lexicon Model (1)
• The lexicons represent the main interface between the user's query and the ontology
• Lexicons for all languages of the project have been created
Ontology-Based Lexicon Model (2)
• all the important concepts within a domain should be included
• we allow the lexicons to contain also non-lexicalized phrases (e.g. mapping variety)
Example from the Dutch lexicon
<entry id="id60"> <owl:Class rdf:about="lt4el:BarWithButtons"> <rdfs:subClassOf> <owl:Class rdf:about="lt4el:Window"/> </rdfs:subClassOf> </owl:Class> <def>A horizontal or vertical bar as a part of a window, that contains buttons, icons.</def> <termg lang="nl"> <term shead="1">werkbalk</term> <term>balk</term> <term type="nonlex">balk met knoppen</term> <term>menubalk</term> </termg> </entry>
Semantic Annotation of Learning Objects
• Within the project we performed both types of annotation,:– inline– through metadata
• The inline annotation will be used:
– as a mechanism to validate the coverage of the ontology;
– for semantic retrieval
Semantic Search
Aims at improved retrieval of documents– Find documents that would not be found by simple full
text search; e.g. search for “screen” retrieves documents that contain “monitor”
Crosslingual– Find documents in languages different from
search/interface language; – Advantage: No need to translate search query
Ontology: contains concepts Document
Database
Lexicons: contain
term-concept mappings
Visualisation selec
t conce
pts
Search-Term(s)
Search-Concepts
Retrieved Documents
Search procedure
Search procedure
• Provide a search query in Language L(1)• Find terms in lexicons of L(1) that reflect search
query• Find relevant documents for concepts in L(1),
L(2) etc. • Rank for set of found documents• Create ontology fragment containing necessary
information to present concept neighbourhood
Search with ILIAS
Evaluation of Semantic Search
Aspects:• Does semantic search return correct results, i.e.
appropriate documents?• How easy is it to use semantic search?• Are the results better (precision/recall) than with
keyword search or full text search?• Does semantic search improve learning
processes?
Formal EvaluationProcedure: Search for paragraphs with query
• formed on the basis of Concepts from ontology
#Program* + #Slide
• formed on the basis of Terms in the lexicons
Program, Software, Editor, Slide
For a variety of languages.
Conclusions
Language Full-text search
(F-measure)
Semantic search (F-measure)
Bulgarian 56,25 91,30
Dutch 47,50 94,12
English 27,96 79,42
German 36,00 59.26
Polish 12,50 50,00
Portuguese 28,67 33,33
Conclusions
• Evaluation experiment showed the superiority of semantic search over simple full text search
• Our architecture introduces cross-lingual search into the learning process