MCDM 2011, Jyvaskyla, Finland, June 13-17, 2011 A Role of Dialogue Strategy in Multiattribute...

MCDM 2011, Jyvaskyla, Finland, June 13-17, 2011

A Role of Dialogue Strategy in

Multiattribute Classification Performance

Eugenia Furems

Institute for System Analysisof Russian Academy of Sciences

[email protected]

mailto:[email protected]


A Role of Dialogue Strategy in Multiattribute Classification Performance

Outline

1. Verbal Decision Analysis (VAR) – principles & methods2. Knowledge-based multiattribute classification3. Cognitive difficulties & their avoidance 4. VDA-based method for Nominal-Ordinal Classification

(NORCLASS)5. Advantages and Disadvantages of NORCLASS 6. Modification of NORCLASS dialogue and its

effectiveness7. Conclusion


Verbal Decision Analysis – Principles

• Human (DM’s, expert’s) judgements (in verbal or, in other words, qualitative form) - the primary source of information for decision making problems solving

• Processing such information without any quantitative conversion, so that any resulting conclusion is both transparent and well-explainable to the DM/expert .


Verbal Decision Analysis - Methods

Problems

MulticriteriaChoice Problem

Classification problem

Preference-based multicriteriaclassification

Knowledge-based multiattribute classification

ZAPROS UniComBos

ORCLASS, DIFCLASS, CLARA

NORCLASS STEPCLASS


Knowledge-based Multiattribute Classification

Assigning the given objects, described with the values upon multiple attributes, to the classes* (from their pre-defined set) according to the expert knowledge.

* Class - a set of objects in respect of which the expert makes the same (classification, diagnostic, etc.) decision.


Cognitive Problems & Their Avoidance

“An Expert knows more than he/she is able to say”Although an expert would be able to list some classification

rules directly, most certainly these rules would be applicable to the typical objects only. So, the set of such rules would be incomplete both in regard of the domain coverage, and in relation to his/her knowledge.

Cause: an expert does not formulate the rules in his/her daily activity, but he/she applies them while analyzing the real-world objects.

Way out: Simulating objects to be classified and presenting them to the expert for analysis and classification.


Prerequisites for VDA-based

Multiattribute Classification Methods 1. Completeness of the expert-specified rules,

that allow to classify each object from the set of all hypothetically possible objects in the given application domain described by the values of the expert-specified attributes.

2. Consistency of rules: Any number of rules may be specified for an object; however, all of these rules have to assign it to the same class

3. Avoidance of exhaustive search while the expert’s classification rules eliciting.


VDA-based method NORCLASS

NORCLASS is designed for NOminal-ORdinal CLASSification, where classes correspond to

non-orderable decisions, but the expert is able to order the values of each and every attribute

according to their inherence in (typicality to) each such class independently of the values of other

attributes. :

_________________________________________________________________________________

Larichev O, Moshkovich H, Furems E et al (1991) Knowledge Acquisition for the Construction of the Full and Contradiction Free Knowledge Bases. Iec ProGAMMA, Groningen, The Netherlands.


Example

Localization of Pain

Myocardial Infarction

Stenocardia

The retrosternal pain 1 2

The pain left to sternum 3 1

The pain under the left scapula 2 3

1 – the most inherent, 3 – the least inherent


Formal Statement of Multiattribute Classification Problem in NORCLASS

It is given:− the names of classes pre-defined by the

expert;

− the names of attributes, values of which describe the features of objects of the given Application Domain (AD)

− the values (the scale) of the m-th attribute

A=K1xK2x…xKM− the set of M-attribute descriptions of all hypothetically possible objects of the AD;

It is required: Assign the objects from A to classes from C on the basis of the expert’s knowledge so that the resulting classification is both complete (up to the expert’s knowledge) and consistent

LlCC l ,1

MQQQQ ,..., 21

mmnmmm kkkK ,...,, 21

,,...,, 21 iMiii aaaa MmKa mim ,1,


Ordering by Inherence

−reflexive and transitive binary relations over Qm’s values, such that (kmi,kmj) Rl

m, if, according to the expert judgement, kmi is not less inherent in (typical to) Cl than kmj; m=1,…,M; l = 1, …,L.

Relations of Dominance by Inherence in a correspondent class

mmlm KKR

LlRaaMmAaaaaR lmjmimjiji

l ,1,,,1,,,


Rules in NORCLASS

1. If the expert assigns an object ai to the class Cl, any object aj, such that (aj, ai) Rl , belongs to Cl as well.

2. If, according to the expert judgement, an object ai, does not belong the class Cl, any object aj, such that (ai, aj) Rl, does not belong to Cl as well.

Violation of the rules above means the expert’s error and has to be corrected once it has been revealed.


NORCLASS Rules’ Effects

C1 C21,1,1,1

1,1,1,2 1,1,2,1 1,2,1,1 2,1,1,1

1,1,1,3 1,1,2,2 1,2,1,2 1,2,2,1 2,1,1,2 2,1,2,1 2,2,1,1

1,1,2,3 1,2,1,3 1,2,2,2 2,1,1,3 2,1,2,2 2,2,1,2 2,2,2,1

1,2,2,3 2,1,2,3 2,2,1,3 2,2,2,2

2,2,2,3

1,1,1,1

1,1,1,2 1,1,2,1 1,2,1,1 2,1,1,1

1,1,1,3 1,1,2,2 1,2,1,2 1,2,2,1 2,1,1,2 2,2,1,12,1,2,1

1,1,2,3 1,2,1,3 1,2,2,22,1,1,3 2,1,2,2 2,2,1,2 2,2,2,1

1,2,2,3 2,1,2,3 2,2,1,3 2,2,2,2

2,2,2,3

a1

a2a4 a7 a13

a5a8 a10 a14

a16

a19

a6 a9a11 a15 a17 a20

a22

a12a18 a21 a23

a24

a23

a24a20 a17

a11

a22 a21 a18 a14 a12

a8a5

a19 a16 a15 a10a9 a6 a2

a13a7

a4 a3

a1

a3


Advantages and Disadvantagesof NORCLASS

Advantages Disadvantages

1. NORCLASS is based on so called Inherence Hypothesis (IH): an expert is able to order the values of any attribute independently of the values of other attributes. IH-based rules allow to reduce significantly (up to 65% in average) a number of objects presented to an expert directly.

1. NORCLASS doesn’t provide for any aids for problem structuring. Classes, attributes, values and binary relations are revealed informally.

2. Non-flexible dialogue with an expert: he/she is presented M-attribute objects as whole, while the expert may need a part of such information only.

3. It is impossible to add a new class, attribute or value in the course of classification.

2. NORCLASS allows to construct the complete (up to the expert knowledge) and consistent set of classification rules.


Modifications for NORCLASS Effectiveness Improvement

1. Restatement a problem to include the formal phase of its structuring*.

2. Changing the dialogue strategy in order to:• make it more flexible and, thus, less cognitively onerous

for en expert;• reduce further a number of questions to be asked to an

expert in a view of his/her classification rules eliciting;• provide for additional possibilities for rules’ consistency

control.

-----------------------*Eugenia M. Furems. Domain Structuring For Knowledge-Based Multiattribute Classification (A Verbal

Decision Analysis Approach) (2010) TOP, Springer Berlin / Heidelberg, DOI 10.1007/s11750-009-0133-0


Reformulation a problem

Multiattribute classification problem is stated as two interrelated sub-problems:

It is given:Some Application Domain each object of which may belong to one or more classes

It is required:1. To define the Structure of the Application Domain, i.e.,

2. To assign each aiA (A=K1 x K2 x … x KM) to a class/classes from C on the basis of the expert’s knowledge so that the resulting classification is both complete (up to the expert’s knowledge) and consistent.

),,,( lmmm RVKQCS


Explicit Structuring(Pre-defined Classes C1, C2, C3)

ATTRIBUTES

Q1

Q2

Values of Q1 for C1

k11 k12

Other classes k11 isadmissible for

C2 C3

Other values of Q1 for C2

k13

Other classes k13 is

admissible for C3


C3

Other values of Q1 for C3

k14


C1

apart from C1

apart from k11

apart from C 2

apart from k 11,k 1,3

C4

apart form C1

apart from C3


Structuring by Examples

Example for C1

If <A> & <B>, then C1

A is a valueof Q1 (k11=A)

B is a valueof Q2 (k21=B)

Other classesk11 is admissible for

C2 C3

Other valuesfor C2

k13

Other classes k31 is admissible for

C1 C3

Example for C2

If <D> & <E>, then C2

D is a value of Q2

(k22=D)E is a value of Q3

(k31=E)


Classification Rules Elicitation

ai=(x1,x2,x3,x4), xmKm

System:

x2

Expert

Q3?

System

x2x3

Expert

Q4?

Extension the Rule according to Dominance Inherence:If ‘any value’ of Q1, and any k2i, such that (k2i, x2) R1

2, and any k3j, such that (k3j,x3) R1

3, and any k4s, such that (k4s, x4) R14, than C1

System

x2x3x4

Expert: C1

Rule: If ‘any value’ of Q1, and x2 upon Q2, and x3 upon Q3 , and x4 upon Q4, than C1


Effect of Dialogue Strategy Modification(Class C1)

Before After1,1,1,1

1,1,1,2 1,1,2,1 1,2,1,1 2,1,1,1

1,1,1,3 1,1,2,2 1,2,1,2 1,2,2,1 2,1,1,2 2,1,2,1 2,2,1,1

1,1,2,3 1,2,1,3 1,2,2,2 2,1,1,3 2,1,2,2 2,2,1,2 2,2,2,1

1,2,2,3 2,1,2,3 2,2,1,3 2,2,2,2

2,2,3,3

1,1,1,1

1,1,1,2 1,1,2,1 1,2,1,1 2,1,1,1

1,1,1,3 1,1,2,2 1,2,1,2 1,2,2,1 2,1,1,2 2,2,1,12,1,2,1

1,1,2,3 1,2,1,3 1,2,2,22,1,1,3 2,1,2,2 2,2,1,2 2,2,2,1

1,2,2,3 2,1,2,3 2,2,1,3 2,2,2,2

2,,2,3,3

a1

a2a4 a7 a13

a5a8 a10 a14

a16

a19

a6 a9a11 a15 a17 a20

a22

a12a18 a21 a23

a24

a1

a2a4 a7

a13

a3 a5 a8 a10 a14

a16a19

a6 a9 a11 a15a17 a20 a22

a12a18

a21 a23

a24

a3


Effect of Dialogue Strategy Modification(Class C2)

Before After1,1,1,1

1,1,1,2 1,1,2,1 1,2,1,1 2,1,1,1

1,1,1,3 1,1,2,2 1,2,1,2 1,2,2,1 2,1,1,2 2,1,2,1 2,2,1,1

1,1,2,3 1,2,1,3 1,2,2,2 2,1,1,3 2,1,2,2 2,2,1,2 2,2,2,1

1,2,2,3 2,1,2,3 2,2,1,3 2,2,2,2

2,,2,3,3

1,1,1,1

1,1,1,2 1,1,2,1 1,2,1,1 2,1,1,1

1,1,1,3 1,1,2,2 1,2,1,2 1,2,2,1 2,1,1,2 2,2,1,12,1,2,1

1,1,2,3 1,2,1,3 1,2,2,22,1,1,3 2,1,2,2 2,2,1,2 2,2,2,1

1,2,2,3 2,1,2,3 2,2,1,3 2,2,2,2

2,,2,3,3

a23

a24a20

a17a11

a21a18 a14 a12

a8

a5

a19 a16a15 a10 a9 a6

a2

a13a7 a4 a3

a1

a23

a24a20 a17

a11

a22 a21 a18 a14 a12 a8

a5

a19 a16 a15 a10a9 a6 a2

a13a7

a4 a3

a1

a22


AD Structure Adjustment

• Expert has opportunity to specify a new class

He/she is asked to determine admissibility of all values of the attributes fromthe current set Q to such class before to proceed to the next object classification.

• Expert has opportunity to inquire about a new attribute

He/she names it, lists all of its possible values and specifies their correspondentadmissibility to the classes. The first value of the new attribute is added tothe description of the object under consideration, and it is presented to theexpert in addition to information she/he knows already for such object

• Expert points out incompatible values in the object’s description

All objects with such incompatible values’ combinations are excludedfrom the set A.


Additional Consistency Control

Possible contradictions:1. The expert specifies a rule for a class

with the value(s) in left-hand part, he/she determined as inadmissible to the class at the stage of structuring

2. The rule elicited last is inconsistent with the rules elicited previously.


Explicit Rules Inconsistency

Rule 1If any value of Q1, and x2 upon Q2, andx3 upon Q3 ,and x4 upon Q4 , then C1

If x1 upon Q1,and x2 upon Q2, andx3 upon Q3 ,and x4 upon Q4 , then C1

Rule 2If x1 upon Q1, and x2 upon Q2 , and any valueof Q3, and x4 upon Q4 ,then C2

If x1 upon Q1, and x2

upon Q2 , and x3 upon Q3 ,and x4 upon Q4 , then C2

Contradiction


Conclusions

1. VDA-based techniques for multiattribute classification use only those operations of eliciting information from a DM/expert and such information processing so that both intermediate and resulting conclusions are traceable (well-explainable) to the expert.

2. Proposed modification of a dialogue strategy for NORCLASS allows to make an expert’ knowledge acquisition more close to his/her routine practice, and, thus, to facilitate for him/her the rules’ eliciting procedure.

3. In addition, proposed modification allows to eliminate disadvantages of NORCLASS (absence of preliminary structuring procedures, non-flexible dialogue, impossibility of new classes, attributes and their values specification, etc.) and to reduce further the number of objects to be presented the expert directly for his/her classification rules eliciting.


Thank You!

MCDM 2011, Jyvaskyla, Finland, June 13-17, 2011 A Role of Dialogue Strategy in Multiattribute...

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