Some limitations of feature-based recognition in case-based design

Thomas R Hinrichs*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

A crucial part of Case-Based Reasoning is retrieving cases that are similar or otherwise relevant to the problem at hand. Traditionally, this has been formulated as a problem of indexing and accessing cases based on sets of predictive features. More generally, however, we can think of retrieval as a problem of recognition. In this light, several limitations of the feature-based approach become apparent. What constitutes a feature? What makes a feature predictive? And how is retrieval possible when the structure of an input is predictive, but its components are not? This paper presents an analysis of some of the limitations of featurebased recognition and describes a process that integrates structural recognition with retrieval. This structural recognition algorithm is designed to augment the retrieval capabilities of case-based reasoners by facilitating the recognition of functional design clich6s, natural laws, and sub problems for which individual features may not be predictive.

Original languageEnglish (US)
Title of host publicationCase-Based Reasoning Research and Development - 1st International Conference, ICCBR-1995, Proceedings
PublisherSpringer Verlag
Pages471-480
Number of pages10
ISBN (Print)3540605983, 9783540605980
StatePublished - Jan 1 1995
Event1st International Conference on Case-Based Reasoning, ICCBR 1995 - Sesimbra, Portugal
Duration: Oct 23 1995Oct 26 1995

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1010
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other1st International Conference on Case-Based Reasoning, ICCBR 1995
CountryPortugal
CitySesimbra
Period10/23/9510/26/95

Fingerprint

Case based reasoning
Retrieval
Case-based Reasoning
Recognition Algorithm
Indexing
Integrate
Design

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Hinrichs, T. R. (1995). Some limitations of feature-based recognition in case-based design. In Case-Based Reasoning Research and Development - 1st International Conference, ICCBR-1995, Proceedings (pp. 471-480). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1010). Springer Verlag.
Hinrichs, Thomas R. / Some limitations of feature-based recognition in case-based design. Case-Based Reasoning Research and Development - 1st International Conference, ICCBR-1995, Proceedings. Springer Verlag, 1995. pp. 471-480 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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Hinrichs, TR 1995, Some limitations of feature-based recognition in case-based design. in Case-Based Reasoning Research and Development - 1st International Conference, ICCBR-1995, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 1010, Springer Verlag, pp. 471-480, 1st International Conference on Case-Based Reasoning, ICCBR 1995, Sesimbra, Portugal, 10/23/95.

Some limitations of feature-based recognition in case-based design. / Hinrichs, Thomas R.

Case-Based Reasoning Research and Development - 1st International Conference, ICCBR-1995, Proceedings. Springer Verlag, 1995. p. 471-480 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1010).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Hinrichs TR. Some limitations of feature-based recognition in case-based design. In Case-Based Reasoning Research and Development - 1st International Conference, ICCBR-1995, Proceedings. Springer Verlag. 1995. p. 471-480. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).