A role of dialogue strategy in multiattribute classification performance
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A Role of Dialogue Strategy in Multiattribute Classification Performance. Eugenia Furems Institute for System Analysis of Russian Academy of Sciences [email protected] A Role of Dialogue Strategy in Multiattribute Classification Performance Outline.

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A role of dialogue strategy in multiattribute classification performance

A Role of Dialogue Strategy in Multiattribute Classification Performance

Eugenia Furems

Institute for System Analysisof Russian Academy of Sciences

[email protected]

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


A role of dialogue strategy in multiattribute classification performance outline

A Role of Dialogue Strategy in Multiattribute Classification PerformanceOutline

Verbal Decision Analysis (VAR) – principles & methods

Knowledge-based multiattribute classification

Cognitive difficulties & their avoidance

VDA-based method for Nominal-Ordinal Classification(NORCLASS)

Advantages and Disadvantages of NORCLASS

Modification of NORCLASS dialogue and its effectiveness

Conclusion

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


Verbal decision analysis principles

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.

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


Verbal decision analysis methods

Verbal Decision Analysis - Methods

Problems

MulticriteriaChoice Problem

Classification problem

Preference-based multicriteriaclassification

Knowledge-based multiattribute classification

ZAPROS

UniComBos

ORCLASS, DIFCLASS, CLARA

NORCLASS

STEPCLASS

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


Knowledge based multiattribute classification

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.

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


Cognitive problems their avoidance

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 notformulatethe rules in his/her daily activity, but he/sheappliesthem while analyzing the real-world objects.

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

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


Prerequisites for vda based multiattribute classification methods

Prerequisites for VDA-based Multiattribute Classification Methods

  • 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.

  • 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

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

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


Vda based method norclass

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.

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


Example

Example

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


Formal statement of multiattribute classification problem in norclass

Formal Statement of Multiattribute Classification Problem in NORCLASS

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


Ordering by inherence

Ordering by Inherence

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


Rules in norclass

Rules in NORCLASS

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

  • 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.

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


Norclass rules effects

C1

C2

NORCLASS Rules’ Effects

a1

1,1,1,1

a23

1,1,1,1

a11

a20

a17

a4

a24

1,1,1,2

1,1,2,1

a7

1,2,1,1

2,1,1,1

1,1,1,2

1,1,2,1

1,2,1,1

2,1,1,1

a2

a13

a22

a5

a21

a19

a8

a3

a8

a18

a14

a5

a10

a16

a12

a14

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

1,1,1,3

1,1,2,2

1,2,1,2

1,2,2,1

2,1,1,2

2,1,2,1

2,2,1,1

a19

a6

a22

a16

a9

a6

a2

a11

a9

a15

a17

a20

a15

a10

2,1,1,3

2,1,2,2

2,2,1,2

2,2,2,1

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

1,1,2,3

1,2,1,3

1,2,2,2

a18

a4

a3

a7

a12

a21

a23

a13

1,2,2,3

2,1,2,3

2,2,1,3

2,2,2,2

1,2,2,3

2,1,2,3

2,2,1,3

2,2,2,2

a24

2,2,2,3

2,2,2,3

a1

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


Advantages and disadvantages of norclass

Advantages and Disadvantagesof NORCLASS

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


Modifications for norclass effectiveness improvement

Modifications for NORCLASS Effectiveness Improvement

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

  • 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, DOI10.1007/s11750-009-0133-0

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


Reformulation a problem

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:

To define the Structure of the Application Domain, i.e.,

To assign each aiA (A=K1xK2x … 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.

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


Explicit structuring pre defined classes c 1 c 2 c 3

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

ATTRIBUTES

Values of Q1 for C1

apart form C1

Q1

k11

k12

Other classes k12 isadmissible for

Q2

C3

Other classes k11 isadmissible for

apart from C1

apart from k11,k1,3

C2

C3

Other values of Q1 for C3

k14

Other values of Q1 for C2

apart from C3

apart from k11

Other classes k14 isadmissible for

k13

apart from C2

C1

C4

Other classes k13 isadmissible for

C3

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


Structuring by examples

Structuring by Examples

Example for C1

Other classesk11 is admissible for

A is a valueof Q1 (k11=A)

If <A> & <B>, then C1

C2

C3

B is a valueof Q2 (k21=B)

Example for C2

Other valuesfor C2

If <D> & <E>, then C2

k13

D is a value of Q2(k22=D)

E is a value of Q3

(k31=E)

Other classes k31is admissible for

C1

C3

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


Classification rules elicitation

Classification Rules Elicitation

ai=(x1,x2,x3,x4), xmKm

System:

Expert

System

Expert

System

Q3?

x2x3

Q4?

x2x3x4

x2

Expert: C1

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

and x4 upon Q4, than C1

Extension the Rule according to Dominance Inherence:

If ‘any value’ of Q1, and any k2i, such that (k2i, x2) R12, and any k3j,

such that (k3j,x3) R13, and any k4s, such that (k4s, x4) R14, than C1

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


Effect of dialogue strategy modification class c 1

Before

After

Effect of Dialogue Strategy Modification(Class C1)

a1

1,1,1,1

a1

1,1,1,1

a13

a4

a7

a4

a2

1,1,1,2

1,1,2,1

a7

1,2,1,1

2,1,1,1

1,1,1,2

1,1,2,1

1,2,1,1

2,1,1,1

a2

a13

a3

a19

a5

a19

a16

a3

a8

a8

a10

a5

a10

a16

a14

a14

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

1,1,1,3

1,1,2,2

1,2,1,2

1,2,2,1

2,1,1,2

2,1,2,1

2,2,1,1

a6

a6

a22

a9

a17

a20

a22

a11

a9

a15

a17

a20

a11

a15

2,1,1,3

2,1,2,2

2,2,1,2

2,2,2,1

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

1,1,2,3

1,2,1,3

1,2,2,2

a18

a21

a23

a18

a12

a21

a23

a12

1,2,2,3

2,1,2,3

2,2,1,3

2,2,2,2

1,2,2,3

2,1,2,3

2,2,1,3

2,2,2,2

a24

2,2,3,3

2,,2,3,3

a24

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


Effect of dialogue strategy modification class c 2

Before

After

Effect of Dialogue Strategy Modification(Class C2)

a23

1,1,1,1

a23

1,1,1,1

a11

a17

a20

a17

a20

a24

a24

1,1,1,2

1,1,2,1

1,2,1,1

2,1,1,1

1,1,1,2

1,1,2,1

1,2,1,1

2,1,1,1

a11

a22

a5

a21

a5

a22

a18

a18

a14

a21

a14

a8

a12

a8

a12

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

1,1,1,3

1,1,2,2

1,2,1,2

1,2,2,1

2,1,1,2

2,1,2,1

2,2,1,1

a19

a19

a2

a16

a9

a6

a2

a15

a16

a10

a9

a6

a15

a10

2,1,1,3

2,1,2,2

2,2,1,2

2,2,2,1

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

1,1,2,3

1,2,1,3

1,2,2,2

a7

a4

a3

a7

a13

a4

a3

a13

1,2,2,3

2,1,2,3

2,2,1,3

2,2,2,2

1,2,2,3

2,1,2,3

2,2,1,3

2,2,2,2

a1

2,,2,3,3

2,,2,3,3

a1

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


Ad structure adjustment

AD Structure Adjustment

  • Expert has opportunity to specify a new class

He/she is asked to determine admissibility of all values of the attributes from

the 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 correspondent

admissibility to the classes. The first value of the new attribute is added to

the description of the object under consideration, and it is presented to the

expert 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 excluded

from the set A.

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


Additional consistency control

Additional Consistency Control

Possible contradictions:

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

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

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


Explicit rules inconsistency

Explicit Rules Inconsistency

Rule 1

If any value of Q1, andx2 upon Q2, andx3 upon Q3 ,and x4 upon Q4 , then C1

If x1 upon Q1,andx2 upon Q2, andx3 upon Q3 ,and x4 upon Q4 , then C1

Contradiction

Rule 2

If x1 upon Q1, and x2upon 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

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


Conclusions

Conclusions

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.

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.

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.

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


A role of dialogue strategy in multiattribute classification performance

Thank You!

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


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