Using non boolean similarity functions for frequent similar pattern mining

1Citations
Citations of this article
7Readers
Mendeley users who have this article in their library.
Get full text

Abstract

In this paper, we focus on frequent pattern mining using non Boolean similarity functions. Several properties and propositions that allow pruning the search space of frequent similar patterns, are proposed. Based on these properties, an algorithm for mining frequent similar patterns using non Boolean similarity functions is also introduced. We evaluate the quality of the frequent similar patterns computed by our algorithm by means of a supervised classifier based on frequent patterns. © 2010 Springer-Verlag Berlin Heidelberg.

Cite

CITATION STYLE

APA

Rodríguez-González, A. Y., Martínez-Trinidad, J. F., Carrasco-Ochoa, J. A., & Ruiz-Shulcloper, J. (2010). Using non boolean similarity functions for frequent similar pattern mining. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6085 LNAI, pp. 374–378). https://doi.org/10.1007/978-3-642-13059-5_50

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free