Conceptual distance of numerically specified case features

W. Dubitzky, A. Schuster, J. G. Hughes, D. A. Bell

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

4 Citations (Scopus)

Abstract

Case-based reasoning (CBR) systems rely on the conceptual ordering of entities called cases. If atomic case features are allowed to assume numeric as well as symbolic values, then a systematic comparison regime is needed to aggregate similarity scores. A common approach to deal with real-numbered features is normalisation. However, there are two conspicuous problems with this procedure: the similarity between two features is dependent on the corresponding values of all other cases to be ranked; and real-numbered features are often interpreted by human experts according to conceptual constraints associated with features. In such situations, a conceptual distance between two features should be determined rather than the length of a 'gap' on a linear scale. Within the framework of a comprehensive case-knowledge architecture, the notion of a concept frame that can be associated with a case feature is proposed. Through this component it is possible to represent polymorphic atomic case features, and to systematically establish the concept distance between two real-numbered feature instances.

Original languageEnglish
Title of host publicationProceedings - 1995 2nd New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems, ANNES 1995
EditorsGeorge Coghill, Nikola K. Kasabov
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages210-213
Number of pages4
ISBN (Electronic)0818671742, 9780818671746
DOIs
Publication statusPublished - 1995 Jan 1
Externally publishedYes
Event2nd New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems, ANNES 1995 - Dunedin, New Zealand
Duration: 1995 Nov 201995 Nov 23

Publication series

NameProceedings - 1995 2nd New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems, ANNES 1995

Conference

Conference2nd New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems, ANNES 1995
Country/TerritoryNew Zealand
CityDunedin
Period95/11/2095/11/23

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications

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