Detail publikace

Multi-level Sequence Mining Based on GSP

Originální název

Multi-level Sequence Mining Based on GSP

Anglický název

Multi-level Sequence Mining Based on GSP

Jazyk

en

Originální abstrakt

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.

Anglický abstrakt

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.

BibTex


@article{BUT96928,
  author="Michal {Šebek} and Martin {Hlosta} and Jan {Kupčík} and Jaroslav {Zendulka} and Tomáš {Hruška}",
  title="Multi-level Sequence Mining Based on GSP",
  annote="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.",
  address="NEUVEDEN",
  chapter="96928",
  doi="10.2478/v10198-012-0012-8",
  edition="NEUVEDEN",
  howpublished="print",
  institution="NEUVEDEN",
  number="2",
  volume="2012",
  year="2012",
  month="october",
  pages="31--38",
  publisher="NEUVEDEN",
  type="journal article - other"
}