Formal Concept Analysis: Mathematical Foundations
Formal Concept Analysis: Mathematical Foundations
Pattern Structures and Their Projections
ICCS '01 Proceedings of the 9th International Conference on Conceptual Structures: Broadening the Base
Two FCA-Based Methods for Mining Gene Expression Data
ICFCA '09 Proceedings of the 7th International Conference on Formal Concept Analysis
Mining gene expression data with pattern structures in formal concept analysis
Information Sciences: an International Journal
Backing composite web services using formal concept analysis
ICFCA'11 Proceedings of the 9th international conference on Formal concept analysis
Biclustering numerical data in formal concept analysis
ICFCA'11 Proceedings of the 9th international conference on Formal concept analysis
Symbolic galois lattices with pattern structures
RSFDGrC'11 Proceedings of the 13th international conference on Rough sets, fuzzy sets, data mining and granular computing
| Hi-index | 0.00 |
This paper shows how to embed a similarity relation between complex descriptions in concept lattices. We formalize similarity by a tolerance relation: objects are grouped within a same concept when having similar descriptions, extending the ability of FCA to deal with complex data. We propose two different approaches.~A first classical manner defines a discretization procedure. A second way consists in representing data by pattern structures, from which a pattern concept lattice can be constructed directly. In this case, considering a tolerance relation can be mathematically defined by a projection in a meet-semi-lattice. This allows to use concept lattices for their knowledge representation and reasoning abilities without transforming data. We show finally that resulting lattices are useful for solving information fusion problems.