Conversational CaseBased Reasoning

1
Conversational Case-Based Reasoning

• Shruti Bhandari

2
Overview

• Concept
• Rule Based Systems
• Representation
• Problem Solving Process
• Challenges
• Applications

3
Case Based Reasoning

• Direct Reuse of prior knowledge
• Cases and Case Base
• Retrieve
• Reuse
• Revise
• Retain

4
CBR

• 3 Approaches to CBR
• Textual Approach
• Structural Approach
• Conversational Approach

5
Textual Approach

• Cases recorded as free text
• Large collection of documents
• Easy Case Acquisition
• Keyword Matching
• Syntactic Retrieval
• Complexity
• Example Frequently Asked Questions

6
Structural Approach

• Case Represented according to vocabulary
• Assigned values to predefined attributes
• Partially filled query description
• Example Sales Support for Electronic Devices

7
CCBR

• Pioneered by Inference Corporation
• Interactive Problem Assessment
• Incremental Approach
• Solutions available during conversation
• A-priori knowledge not required

8
CCBR (contd)

• Customer/Agent Conversations
• List of questions
• No Domain Model
• No Structure
• Domains of high volume of simple problems
• Example Call Center for Printer Problems

9
CCBR vs Rule Based System

• Problem solving method
• Learning from experience
• Complexity of systems
• Scaling
• Cost

10
Case Representation

• Problem CpCdCqa
• Description Cd
• Specification Cqa
• Solution CsCa1,Ca2

11
Steps in CCBR

• Input of problem description Qd
• Computation of similarity s(Q,C)
• Display of solutions of top ranked cases, Ds and
  unanswered questions, Dq
• Selection by user
• Re-computation of similarity
• Successful/Unsuccessful Termination

12
Generic CCBR problem solving process
13
Generic Algorithm
14
Component Reuse using CCBR

• Component based Software Development
• Component Retrieval
• Different Methods for Retrieval
• Assumptions

15
Conversational Component Retrieval Module (CCRM)
16
Parts of CCRM

• Knowledge Base
• New Case Generating Module
• Knowledge Intensive CBR module
• Component Displaying module
• Question Generating and Ranking Module
• Question Displaying Module

17
Challenges

• Case Authoring
• Dialog Inferencing
• Expanded Applicability

18
Case Authoring

• Art of designing good libraries
• Design guidelines
• 3 phase revision of cases

19
Dialogue Inferencing

• Lack of Intelligence
• Challenges
• Input Size
• Comprehensibility
• Maintenance

20
Example of Dialogue Inferencing
21
NaCoDAE

• To address the challenges
• HICAP
• Text Processing
• Question Ranking
• Case Ranking

22
Text Processing

• Problem description and User Input are
  canonicalized
• Nouns identified
• Similarity Calculation

23
Question Ranking

• Frequency Calculation
• No need of information gain

24
Case Ranking

• Similarity Calculation
• score(Q,C) same(Qqa,Cqa)-diff(Qqa,Cqa)
• Cqa
• Bias Control

25
Applications

• Maintenance and Repair of Complex systems like
  aircrafts, trucks etc
• CREEK
• NaCoDAE
• HICAP
• Expert Clerk

26
Final Remarks

• CCBR interactive and incremental approach
• Main components of CCBR
• Future of CCBR
• Our Project

27
References

• Conversational Case-Based Reasoning David Aha,
  Leonard Breslow, Hector Munoz-Avila, Sept 1999
• Experience Management Ralph Bergmann
• Conversational Case-Based Software Reasoning in
  Reuse Mingyang Gu

28
THANK YOU!!!