Computing Similarity Dependencies with Pattern Structures
Abstract
Functional dependencies provide valuable knowledge on the relations between the attributes of a data table. To extend their use, generalizations have been proposed, among which purity and approximate dependencies. After discussing those generalizations, we provide an alternative definition, the similarity dependencies, to handle a similarity relation between data-values, hence un-crisping the basic definition of functional dependencies. This work is rooted in formal concept analysis, and we show that similarity dependencies can be easily characterized and computed with pattern structures.
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