Conversational Case-Based 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 Cp=Cd+Cqa • Description Cd • Specification Cqa • Solution Cs={Ca1,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!!!