Organizing large case library by linear programming

Caihong Sun, Chi Keung Simon Shiu, Xizhao Wang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

In this paper we proposed an approach to maintain large case library, which based on the idea that a large case library can be transformed to a compact one by using a set of case-specific weights. A linear programming technique is being used to obtain case-specific weights. By learning such local weights knowledge, many of redundant or similar cases can be removed from the original case library or stored in a secondary case library, This approach is useful for case library with a large number of redundant or similar cases and the retrieval efficiency is a real concern of the user. This method of maintaining case library from scratch, as proposed in this paper, consists of two main steps. First, a linear programming technique for learning case-specific weights is used to evaluate the importance of different features for each case. Second, a case selection strategy based on the concepts of case coverage and reachability is carried out to select representative cases, Furthermore, a case retrieval strategy of the compact case library we built is discussed. The effectiveness of the approach is demonstrated experimentally by using two sets of testing data, and the results are promising.
Original languageEnglish
Title of host publicationMICAI 2005
Subtitle of host publicationAdvances in Artificial Intelligence - 4th Mexican International Conference on Artificial Intelligence, Proceedings
Pages554-564
Number of pages11
DOIs
Publication statusPublished - 1 Dec 2005
Event4th Mexican International Conference on Artificial Intelligence, MICAI 2005 - Monterrey, Mexico
Duration: 14 Nov 200518 Nov 2005

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3789 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference4th Mexican International Conference on Artificial Intelligence, MICAI 2005
Country/TerritoryMexico
CityMonterrey
Period14/11/0518/11/05

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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