Paper Info
Title
Distributed Computation of Generalized One-Sided Concept Lattices on Sparse Data Tables.
Abstract
In this paper we present the study on the usage of distributed version of the algorithm for generalized one-sided concept lattices (GOSCL), which provides a special case for fuzzy version of data analysis approach called formal concept analysis (FCA). The methods of this type create the conceptual model of the input data based on the theory of concept lattices and were successfully applied in several domains. GOSCL is able to create one-sided concept lattices for data tables with different attribute types processed as fuzzy sets. One of the problems with the creation of FCA-based models is their computational complexity. In order to reduce the computation times, we have designed the distributed version of the algorithm for GOSCL. The algorithm is able to work well especially for data where the number of newly generated concepts is reduced, i.e., for sparse input data tables which are often used in domains like text-mining and information retrieval. Therefore, we present the experimental results on sparse data tables in order to show the applicability of the algorithm on the generated data and the selected text-mining datasets.
Year
Venue
Keywords
2015
COMPUTING AND INFORMATICS
One-sided concept lattices,distributed algorithm,formal concept analysis,sparse data,text-mining
Field
DocType
Volume
Computer science,Lattice Miner,Fuzzy logic,Algorithm,Fuzzy set,Theoretical computer science,Distributed algorithm,Formal concept analysis,Sparse matrix,Computation,Computational complexity theory
Journal
34
Issue
ISSN
Citations 
SP1
1335-9150
3
PageRank 
References 
Authors
0.67
0
3
Name
Order
Citations
PageRank
Peter Butka1418.44
Jozef Pócs214616.23
Jana Pócsová3336.02