1. Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall Chapter 9 Using Past History Explicitly as Knowledge: Case-based Reasoning Systems

2. Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall Chapter Objectives Introduce the student to the concept of using explicit historical occurrences to solve current problems.  Explained in the context of rule-based systems that also use past experience to solve current problems Introduce case-based reasoning. Introduce how case-based systems can learn from their own experience

3. Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall Section 9.1 - Objectives Introduction of chapter contents

4. Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall Section 9.2 - Objectives Introduce the weaknesses of rule-based systems that inspired the rise of case-based reasoning.

5. Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall Section 9.3 - Objectives Introduce the basic concepts in case-based reasoning:  Search the case library  Retrieve the most similar case(s)  Adapt the most similar case(s) if not suitably similar  Apply the solution to the current problem  Add the last case to the case library

6. Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall Section 9.4 - Objectives Introduce the concept of indexing the case library Describes the main means of increasing search efficiency through indexing  Flat library  Shared feature networks  Redundant shared feature networks

7. Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall Section 9.5 - Objectives Introduces the concepts of matching and retrieval of cases from the case library Introduce the concept of distance metric to compute the distance between historical cases and current problem

8. Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall Section 9.6 - Objectives Introduce the concepts of evaluation and adaptation  How to determine whether the most similar case is similar enough  How to modify the most similar case when it is not sufficiently similar to the current problem

9. Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall Section 9.7 - Objectives Introduce the concept of learning in the context of case-based reasoning Introduce the concept of when new cases are consistent with the rest of the case library and when they are not  This is important when deciding whether to add new cases or not

10. Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall Section 9.8 - Objectives Presents a detailed example of a case-based application to property appraisal.

11. Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall Section 9.9 - Objectives Discuss some issues pertinent to case-based systems when applied to different problems Discuss the advantages of case-based systems Discuss the disadvantages of case-based systems

12. Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall Section 9.10 - Objectives Briefly introduces some variations of case-based reasoning:  Exemplar-based reasoning  Instance-based reasoning  Memory-based Reasoning  Analogy-based reasoning

13. Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall Section 9.11 - Objectives Summarize the chapter Provide Key terms Provide Review Questions Provide Review Exercises

14. Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall Figure 9.1 Self-employed Employed Ltd PartnershipCorporation Business Individual < 100K >= $100K < $100K >= $100K < $1M >= $1M < $1M Type of organization Type of Business Employment status Size of Loan Case 1. Case 77 Case 80. Case 106 Case 110. Case 158 Case 160. Case 169 Case 170. Case 206 Case 210. Case 246 Case 250. Case 287 Case 290. Case 326

15. Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall Figure 9.2 Region A Region C Region B

16. Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall Figure 9.3 Problem Space Solution Space Consistent Inconsistent Problem Space

17. Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall Conclusions The student should be familiar with:  The difference between how rule-based systems and case-based systems use historical knowledge.  The main processes of case-based reasoning:  Search  Select  Adapt  Apply  Learn  The advantages and disadvantages of case-based systems

18. Becerra-Fernandez, et al. -- Knowledge Management 1/e -- © 2004 Prentice Hall Chapter 9 Using Past History Explicitly as Knowledge: Case-based Reasoning Systems