Case retrieval based on formal concept analysis

Chongyang Shi*, Bai Yu, Zhendong Niu, Zhang Qi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

This paper proposes a novel case-based retrieval measure by using formal concept analysis. The proposed method employs the concept lattice to express the knowledge base of cases. The proposed retrieval method combines semantic, featural, and structural information into a decision. In this measure, we use the information content approach to obtain automatically the semantic part of the similarity scores of two concepts that constitute the traditional feature and structural similarityevaluating measures. Furthermore, the similarity for case retrieval can be calculated from the lower approximations on the basis of the rough set. Experiment results on the four UCI datasets show that our proposed similarity measure provides better accuracy than some existing similarity measures.

Original languageEnglish
Pages (from-to)4211-4222
Number of pages12
JournalJournal of Computational and Theoretical Nanoscience
Volume13
Issue number7
DOIs
Publication statusPublished - Jul 2016

Keywords

  • Case-Based Reasoning
  • Formal Concept Analysis
  • Information Content Similarity
  • Rough Set

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