Publication Details
Multi-level Sequence Mining Based on GSP
Hlosta Martin, Ing. (DIFS FIT BUT)
Kupčík Jan, Ing. (DIFS FIT BUT)
Zendulka Jaroslav, doc. Ing., CSc. (DIFS FIT BUT)
Hruška Tomáš, prof. Ing., CSc. (DIFS FIT BUT)
multi-level sequence pattern mining, GSP, taxonomy
Mining sequential patterns is an important problem in the field of data mining and many algorithms and optimization techniques have been published to deal with that problem. The GSP algorithm, which is one of them, can be used for mining sequential patterns with some additional constraints. In this paper, we propose a new algorithm for mining multi-level sequential patterns based on GSP. The idea is that if a more general item appears in a pattern, the pattern has higher or at least the same support as the one containing the corresponding specific item. However, too generalized sequence patterns are not important for user. In our algorithm generalization uses a selective method based on information content of patterns. This allows us to mine more patterns with the same minimal support threshold and to reveal new potentially useful patterns.
@ARTICLE{FITPUB9874,
author = "Michal \v{S}ebek and Martin Hlosta and Jan Kup\v{c}\'{i}k and Jaroslav Zendulka and Tom\'{a}\v{s} Hru\v{s}ka",
title = "Multi-level Sequence Mining Based on GSP",
pages = "31--38",
journal = "Acta Electrotechnica et Informatica",
volume = 2012,
number = 2,
year = 2012,
ISSN = "1335-8243",
doi = "10.2478/v10198-012-0012-8",
language = "english",
url = "https://www.fit.vut.cz/research/publication/9874"
}