On attribute reduction in concept lattices: Methods based on discernibility matrix are outperformed by basic clarification and reduction-Reference-Cited by-同舟云学术

On attribute reduction in concept lattices: Methods based on discernibility matrix are outperformed by basic clarification and reduction

Published:2017-11 Issue: Volume:415-416 Page:199-212
ISSN:0020-0255
Container-title:Information Sciences
language:en
Short-container-title:Information Sciences

Author:

Konecny Jan

Funder

Grantová Agentura České Republiky

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering,Software

Reference38 articles.

1. Formal L-concepts with rough intents;Bartl,2014

2. A note on variable threshold concept lattices: threshold-based operators are reducible to classical concept-forming operators;Belohlavek;Inf. Sci.,2007

3. Scaling, granulation, and fuzzy attributes in formal concept analysis.;Belohlavek,2007

4. Generalization of one-sided concept lattices.;Butka;Comput. Inf.,2013

5. Concept Data Analysis: Theory and Applications;Carpineto,2004

Cited by 40 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. $$\delta $$-granular reduction in formal fuzzy contexts: Boolean reasoning, graph represent and their algorithms;Soft Computing;2024-07-26

2. Object-oriented concept approach on rough granular lattice with discernibility object granular;2024-01-19

3. Characterizing Clarify and Reduce Method by Means of Left-Sided Formal Concept Analysis;Studies in Computational Intelligence;2024

4. Fast attribute reduction by neighbor inconsistent pair selection for dynamic decision tables;International Journal of Machine Learning and Cybernetics;2023-08-10

5. On Shapley value interpretability in concept-based learning with formal concept analysis;Annals of Mathematics and Artificial Intelligence;2022-11-22