Case Base Maintenance(CBM)

1
Case Base Maintenance (CBM)

• Fabiana Prabhakar
• CSE 435
• November 6, 2006

2
Introduction

• The growing use of CBR applications has brought
  with it increased awareness of the importance of
  case-base maintenance (CBM).
• Large scale CBR systems are becoming more
  prevalent, with case library sizes ranging from
  thousands to millions of cases.
• Large case-bases raises concern about the utility
  problem for case retrieval, underlining the
  potential need to control case-base growth
  through case deletion policies.

3
Definition

• CBM is the process of refining a CBR systems
  case base to improve the systems performance.

4
Standard CBR learning

• The system always add each new case to the case
  base.
• Domain expert adds a variable number of new
  cases.
• Indexing of the cases.

5
Knowledge-based Systems Utility Problem

• The cost associated with searching for relevant
  knowledge outweighs the benefit of applying the
  knowledge.

6
Traditional Deletion Policies

• A simple deletion policy is random deletion.
  According to this policy a random item is removed
  from the knowledgebase once the knowledge-base
  size exceeds some predefined limit.
• Mintons utility metric Minton, 1990. Chooses a
  knowledge item for deletion based on an estimate
  of its performance benefits. Utility(ApplicationF
  reqAverageSavings)-MatchCost

7
Remembering to Forget

• Competency Preserving Case Deletion Policy for
  CBR Systems (Smyth and Keane, 1995)

8
Coverage and Reachability

• Coverage of a case is the set of target problems
  that can be solved by such case.
• Reachability of a target problem is the set of
  cases that can be used to provide a solution for
  the target problem.

9
Case Competence Categories

• Pivotal Cases its deletion directly reduces the
  competence of the system. A case is pivotal if it
  is reachable by no other case but itself.
• Auxiliary Cases do not effect competence at all.
  A case is auxiliary case if the coverage it
  provides is subsumed by the coverage of one of
  its reachable cases.

10
Case Competence Categories (Cont.)

• Spanning Cases do not directly affect the
  competence. Their coverage spaces link regions of
  the problem space that are independently covered
  by other cases. If cases from this linked regions
  are deleted, then the spanning case might be
  necessary.
• Support Cases a special class of spanning cases.
  They exist in groups. The deletion of the group
  is analogous to removing a pivotal case.

11
Case Competence Categories (Cont.)
12
Case Competence Categories (Cont.)

• The case categories provide a means of ordering
  cases for deletion in terms of their competence
  contributions.
• Auxiliary cases (they make no direct contribution
  to competence)
• Support cases
• Spanning cases
• Pivotal cases.

13
Modeling Case Competence

• Competence categories are computed at start-up.
• During future problem solving as cases are
  learned, the case categories must be updated
• Re-compute the coverage and reachability sets of
  the appropriate cases
• Adjust the categories accordingly.

14
The Footprint Deletion Policy

• Ideally a deletion policy should work to remove
  irrelevant cases guiding the case-base toward an
  optimal configuration of cases.
• Competence Footprint is this optimal case-base.
  It provides the same competence of the entire
  case-base but with fewer cases.

15
The Footprint Deletion Algorithm

• DeleteCase(Cases)
• If there are auxiliary cases then
• SelectAuxiliary(AuxiliaryCases)
• ElseIf there are support cases then
• With the largest support group
• SelectSupport(SuportGroup)
• ElseIf there are spanning cases then
• SelectSpanning(SpanningCases)
• ElseIf there are pivotal cases then
• SelectPivot(PivotalCases)
• Endif

16
The Footprint Utility Deletion Policy

• Combine Footprint and Utility Deletion
• Mintons utility metric An item is selected
  based on an estimate of its performance benefits.
• Utility (ApplicationFreq AverageSavings)
  MatchCost
• The footprint method is used to select candidates
  for deletion. If there is only one such candidate
  then it is deleted.
• If, however, there a number of candidates, then
  rather than selecting the one with the least
  coverage or largest reachability set, the
  candidate with the lowest utility is chosen.
• In other words the utility metric is used within
  the SelectPivot, SelectSpanning, SelectSupport,
  and SelectAuxiliary procedures.

17
Further Applications

• The competence modeling approach may be used
  during the initial case acquisition stage of
  system development. It is often undesirable to
  store every available case in the initial
  case-base.
• Utility Problem
• Irrelevant cases may introduce noise into the
  retrieval stage and lead to the selection of
  suboptimal cases or difficulties in tuning the
  similarity metric.
• The competence modeling approach may be used
  during the authoring process.

18
CBR systems Authoring Process

• Case base authoring can be a long, difficult, and
  tedious process, and the only advice given to the
  author is often of the choose representative
  cases variety.
• This can ultimately lead to the development of
  poor case bases, which offer limited coverage of
  the target problem space, and which include
  significant redundancy.

19
CASCADE (Case Authoring Support Development
Environment)

• Keeps the knowledge engineer informed about how
  case authoring is progressing, and in particular,
  how case base competence is evolving.
• Extends the case competency model proposed by
  Smyth and Keane.

20
Competence Groups

• A competence group is a collection of related
  cases.
• The key idea underlying the definition of a
  competence group is that of shared coverage. Two
  cases exhibit shared coverage if their coverage
  or reachability sets overlap.

21
The Evolution of Competence

• In general as cases are added to the case base
  one of four things can happen
• New groups are created
• Existing competence groups grow in size and
  coverage
• A number of existing groups merge to form a new
  super group
• Existing groups can grow in size but without
  increasing coverage.
• Conversely, as cases are deleted, groups may
  disappear altogether, or they may split into
  smaller sub groups.

22
The Competence Visualization Tool
23
Competence Regions
24
The Competence Visualization Tool Examples
25
The Competence Visualization Tool Examples
(Cont.)
26
Conclusion

• Experience with the growing number of large-scale
  CBR systems has led to increasing recognition of
  the importance of case-base maintenance.
• Multiple researches have addressed pieces of the
  CBM problem, considering such issues as
  maintaining consistency and controlling case-base
  growth.
• The authoring process can be improved in order to
  avoid the development of poor case bases.

27
References

• Smyth B., and Keane, M. Remembering to forget A
  competence-preserving case deletion policy for
  case-based reasoning systems, in Proc. of the
  14th International Joint Conf. on Artificial
  Intelligence, Montreal, Morgan Kauffmann, Canada,
  1995, pp. 377-382.
• D.B. Leak and D.C. Wilson Categorizing
  case-based maintenance Dimensions and
  directions, in Proc. of the 4th European
  Workshop on Case-Base Reasoning, Dublin, Ireland,
  Springer Verleg 1998, pp. 196-207.
• McKenna, E. Smyth, B. An Interactive
  Visualisation Tool for Case-Based Reasoners,
  Journal of Applied Intelligence Special Issue on
  Interactive Case-Based Reasoning, 2000