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General Information
Prof. Wael Badawy
Department of Computing and Information Systems Umm Al Qura University, Canada
I'm happy to take on the position of editor in chief of IJCTE. We encourage authors to submit papers concerning any branch of computer theory and engineering.
IJCTE 2015 Vol.7(2): 132-138 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2015.V7.944

Skeletal Algorithms: Sequential Pattern Mining

Michal R. Przybylek
Abstract—The basic idea behind the skeletal algorithm is to express a problem in terms of congruences on a structure, build an initial set of congruences, and improve it by taking limited unions/intersections, until a suitable condition is reached. Skeletal algorithms naturally arise in the context of data/process mining, where the skeleton is the “free” structure on initial data and congruence corresponds to similarities in data. In this paper we study skeletal algorithms applied to sequential pattern mining and compare their performance with real models, Markov chains and models based on Shannon entropy.

Index Terms—Evolutionary algorithms, pattern mining, process mining, language recognition, skeletal algorithms.

Michal R. Przybylek is with the University of Warsaw, Poland (e-mail: mrp@mimuw.edu.pl).


Cite: Michal R. Przybylek, "Skeletal Algorithms: Sequential Pattern Mining," International Journal of Computer Theory and Engineering vol. 7, no. 2, pp. 132-138, 2015.

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