Title
Characterizing approximate-matching dependencies in formal concept analysis with pattern structures.
Abstract
Functional dependencies (FDs) provide valuable knowledge on the relations between attributes of a data table. A functional dependency holds when the values of an attribute can be determined by another. It has been shown that FDs can be expressed in terms of partitions of tuples that are in agreement w.r.t. the values taken by some subsets of attributes. To extend the use of FDs, several generalizations have been proposed. In this work, we study approximate-matching dependencies that generalize FDs by relaxing the constraints on the attributes, i.e. agreement is based on a similarity relation rather than on equality. Such dependencies are attracting attention in the database field since they allow uncrisping the basic notion of FDs extending its application to many different fields, such as data quality, data mining, behavior analysis, data cleaning or data partition, among others. We show that these dependencies can be formalized in the framework of Formal Concept Analysis (FCA) using a previous formalization introduced for standard FDs. Our new results state that, starting from the conceptual structure of a pattern structure, and generalizing the notion of relation between tuples, approximate-matching dependencies can be characterized as implications in a pattern concept lattice. We finally show how to use basic FCA algorithms to construct a pattern concept lattice that entails these dependencies after a slight and tractable binarization of the original data.
Year
DOI
Venue
2018
10.1016/j.dam.2018.03.073
Discrete Applied Mathematics
Keywords
Field
DocType
Functional dependencies,Similarity,Tolerance relation,Formal concept analysis,Pattern structures,Attribute implications
Discrete mathematics,Data quality,Lattice (order),Tuple,Generalization,Functional dependency,Theoretical computer science,Approximate matching,Knowledge extraction,Formal concept analysis,Mathematics
Journal
Volume
ISSN
Citations 
249
0166-218X
0
PageRank 
References 
Authors
0.34
24
4
Name
Order
Citations
PageRank
Jaume Baixeries19912.57
Víctor Codocedo29613.46
Mehdi Kaytoue339336.08
Amedeo Napoli41180135.52