Formal rough concept analysis

Jamil Saquer, Jitender S. Deogun

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

50 Scopus citations

Abstract

In this paper, we present a novel approach for approximating concepts in the framework of formal concept analysis. Two main problems are investigated. The first, given a set A of objects (or a set B of features), we want to find a formal concept that approximates A (or B). The second, given a pair (A,B), where A is a set of objects and B is a set of features, the objective is to find formal concepts that approximate (A,B). The techniques developed in this paper use ideas from rough set theory. The approach we present is different and more general than existing approaches.

Original languageEnglish (US)
Title of host publicationNew Directions in Rough Sets, Data Mining, and Granular-Soft Computing - 7th International Workshop, RSFDGrC 1999, Proceedings
EditorsSetsuo Ohsuga, Ning Zhong, Andrzej Skowron
PublisherSpringer Verlag
Pages91-99
Number of pages9
ISBN (Print)3540666451, 9783540666455
DOIs
Publication statusPublished - Jan 1 1999
Event7th International Workshop on Rough Sets, Fuzzy Sets, Data Mining, and Granular-Soft Computing, RSFDGrC 1999 - Yamaguchi, Japan
Duration: Nov 9 1999Nov 11 1999

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1711
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other7th International Workshop on Rough Sets, Fuzzy Sets, Data Mining, and Granular-Soft Computing, RSFDGrC 1999
CountryJapan
CityYamaguchi
Period11/9/9911/11/99

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ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Saquer, J., & Deogun, J. S. (1999). Formal rough concept analysis. In S. Ohsuga, N. Zhong, & A. Skowron (Eds.), New Directions in Rough Sets, Data Mining, and Granular-Soft Computing - 7th International Workshop, RSFDGrC 1999, Proceedings (pp. 91-99). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1711). Springer Verlag. https://doi.org/10.1007/978-3-540-48061-7_13