Extensions and intentions in the rough set theory
Information Sciences: an International Journal
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Formal Concept Analysis: Mathematical Foundations
Formal Concept Analysis: Mathematical Foundations
Modal-style operators in qualitative data analysis
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Complexity Reduction in Lattice-Based Information Retrieval
Information Retrieval
Relationship between generalized rough sets based on binary relation and covering
Information Sciences: an International Journal
Short Communication: Concept lattice reduction using fuzzy K-Means clustering
Expert Systems with Applications: An International Journal
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To be an efficient tool for knowledge expression and analysis, formal concept analysis has been paid more attention to in recent years. For the object-oriented concept lattice of a formal context, this paper proposes two compression methods to reduce the original lattice based on covering of the object (attribute) set. We firstly introduce the similarity degree and the neighborhood of an object (attribute) set, and then obtain the covering of the object (attribute) set. Based on which, the objectoriented concept lattice can be compressed into a smaller one through adjusting the object (attribute) neighborhood's size by the similarity degree, and the reduced lattice is a subset of the original one.