Journal
KNOWLEDGE-BASED SYSTEMS
Volume 65, Issue -, Pages 1-11Publisher
ELSEVIER
DOI: 10.1016/j.knosys.2014.03.006
Keywords
Attribute reduction; Concept lattice; Dominance relation; Formal concept analysis; Rough set
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Funding
- Geographical Modeling and Geocomputation Program under the focused investment Scheme of The Chinese University of Hong Kong
- National Natural Science Foundation of China [60963006, 61173181, 61363056]
- Humanities and Social Science funds Project of Ministry of Education of China [09YJCZH082, 11XJJAZH001]
- Science and Technology Project of Qingdao [12-1-4-4-(9)-jch]
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One of the key issues of knowledge discovery and data mining is knowledge reduction. Attribute reduction of formal contexts based on the granules and dominance relation are first reviewed in this paper. Relations between granular reduts and dominance reducts are investigated with the aim to establish a bridge between the two reduction approaches. We obtain meaningful results showing that granule-based and dominance-relation-based attribute reducts and attribute characteristics are identical. Utilizing dominance reducts and attribute characteristics, we can obtain all granular reducts and attribute characteristics by the proposed approach. In addition, we establish relations between dominance classes and irreducible elements, and present some judgment theorems with respect to the irreducible elements. (C) 2014 Elsevier B.V. All rights reserved.
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