Concept Compression in Formal Concept Analysis Using Entropy-Based Attribute Priority

Concept Compression in Formal Concept Analysis Using Entropy-Based Attribute Priority

Discovering important concepts in formal concept analysis (FCA) is an important issue due to huge number of concepts arising out of complicated contexts. To address this issue, this paper proposes a method for concept compression in FCA, involving many-valued decision context, based on information e...

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Bibliographic Details
Main Authors: Sumangali K, Aswani Kumar Ch., Jinhai Li
Format: Article
Language:English
Published: Taylor & Francis Group 2017-03-01
Series:Applied Artificial Intelligence
Online Access:http://dx.doi.org/10.1080/08839514.2017.1316182

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