article

Generating complete set of implications for formal contexts

Authors:

Yan-Hui ZhaiAuthors Info & Claims

Knowledge-Based Systems, Volume 21, Issue 5

Pages 429 - 433

https://doi.org/10.1016/j.knosys.2008.03.001

Published: 01 July 2008 Publication History

Abstract

In this paper, a necessary and sufficient condition on which a set of implications is complete is proposed with the help of the notion of model from logic. Besides, using the closure of an attribute subset to a set of implications, we present a formal method to remove the redundant implications from a complete set. Subsequently, we provide an algorithm to generate a complete set of implications and an illustrative example guarantees the availability of the algorithm.

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Cited By

Zhang SLi DZhai Y(2022)Incremental method of generating decision implication canonical basisSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-021-06452-326:3(1067-1083)Online publication date: 1-Feb-2022
https://dl.acm.org/doi/10.1007/s00500-021-06452-3
Jiang YYang MQu R(2019)Semantic similarity measures for formal concept analysis using linked data and WordNetMultimedia Tools and Applications10.1007/s11042-019-7150-278:14(19807-19837)Online publication date: 1-Jul-2019
https://dl.acm.org/doi/10.1007/s11042-019-7150-2
Xie JYang MLi JZheng Z(2018)Rule acquisition and optimal scale selection in multi-scale formal decision contexts and their applications to smart cityFuture Generation Computer Systems10.1016/j.future.2017.03.01183:C(564-581)Online publication date: 1-Jun-2018
https://dl.acm.org/doi/10.1016/j.future.2017.03.011
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Generating complete set of implications for formal contexts

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Published In

cover image Knowledge-Based Systems

Knowledge-Based Systems Volume 21, Issue 5

July, 2008

81 pages

ISSN:0950-7051

Issue’s Table of Contents

Copyright © © 2008.

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Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 July 2008

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Cited By

Zhang SLi DZhai Y(2022)Incremental method of generating decision implication canonical basisSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-021-06452-326:3(1067-1083)Online publication date: 1-Feb-2022
https://dl.acm.org/doi/10.1007/s00500-021-06452-3
Jiang YYang MQu R(2019)Semantic similarity measures for formal concept analysis using linked data and WordNetMultimedia Tools and Applications10.1007/s11042-019-7150-278:14(19807-19837)Online publication date: 1-Jul-2019
https://dl.acm.org/doi/10.1007/s11042-019-7150-2
Xie JYang MLi JZheng Z(2018)Rule acquisition and optimal scale selection in multi-scale formal decision contexts and their applications to smart cityFuture Generation Computer Systems10.1016/j.future.2017.03.01183:C(564-581)Online publication date: 1-Jun-2018
https://dl.acm.org/doi/10.1016/j.future.2017.03.011
Zhai YLi DQu K(2014)Decision implication canonical basisJournal of Computer and System Sciences10.1016/j.jcss.2014.06.00181:1(208-218)Online publication date: 1-Oct-2014
https://dl.acm.org/doi/10.1016/j.jcss.2014.06.001
Medina J(2012)Relating attribute reduction in formal, object-oriented and property-oriented concept latticesComputers & Mathematics with Applications10.1016/j.camwa.2012.03.08764:6(1992-2002)Online publication date: 1-Sep-2012
https://dl.acm.org/doi/10.1016/j.camwa.2012.03.087
Rezk EBabi SIslam FJaoua A(undefined)Uncertain training data set conceptual reduction: A machine learning perspective2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)10.1109/FUZZ-IEEE.2016.7737914(1842-1849)
https://dl.acm.org/doi/10.1109/FUZZ-IEEE.2016.7737914

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