Publication result detail

MLSP: Mining Hierarchically-Closed Multi-Level Sequential Patterns

ŠEBEK, M.; HLOSTA, M.; ZENDULKA, J.; HRUŠKA, T.

Original Title

MLSP: Mining Hierarchically-Closed Multi-Level Sequential Patterns

English Title

MLSP: Mining Hierarchically-Closed Multi-Level Sequential Patterns

Type

Paper in proceedings outside WoS and Scopus

Original Abstract

The problem of mining sequential patterns has been widely studied and many efficient algorithms used to solve this problem have been published. In some cases, there can be implicitly or explicitely defined taxonomies (hierarchies) over input items (e.g. product categories in a e-shop or sub-domains in the DNS system). However, how to deal with taxonomies in sequential pattern mining is marginally discussed. In this paper, we formulate the problem of mining hierarchically-closed multi-level sequential patterns and demonstrate its usefulness. The MLSP algorithm based on the on-demand generalization that outperforms other similar algorithms for mining multi-level sequential patterns is presented here.

English abstract

The problem of mining sequential patterns has been widely studied and many efficient algorithms used to solve this problem have been published. In some cases, there can be implicitly or explicitely defined taxonomies (hierarchies) over input items (e.g. product categories in a e-shop or sub-domains in the DNS system). However, how to deal with taxonomies in sequential pattern mining is marginally discussed. In this paper, we formulate the problem of mining hierarchically-closed multi-level sequential patterns and demonstrate its usefulness. The MLSP algorithm based on the on-demand generalization that outperforms other similar algorithms for mining multi-level sequential patterns is presented here.

Keywords

closed sequential pattern mining,taxonomy,generalization,GSP,MLSP

Key words in English

closed sequential pattern mining,taxonomy,generalization,GSP,MLSP

Authors

ŠEBEK, M.; HLOSTA, M.; ZENDULKA, J.; HRUŠKA, T.

RIV year

2014

Released

14.12.2013

Publisher

Springer Verlag

Location

Hangzhou

ISBN

978-3-642-53913-8

Book

9th International Conference, ADMA 2013

Edition

Lecture Notes in Computer Science

Pages from

157

Pages to

168

Pages count

12

URL

http://link.springer.com/chapter/10.1007/978-3-642-53914-5_14

BibTex

@inproceedings{BUT104515,
  author="Michal {Šebek} and Martin {Hlosta} and Jaroslav {Zendulka} and Tomáš {Hruška}",
  title="MLSP: Mining Hierarchically-Closed Multi-Level Sequential Patterns",
  booktitle="9th International Conference, ADMA 2013",
  year="2013",
  series="Lecture Notes in Computer Science",
  pages="157--168",
  publisher="Springer Verlag",
  address="Hangzhou",
  doi="10.1007/978-3-642-53914-5\{_}14",
  isbn="978-3-642-53913-8",
  url="http://link.springer.com/chapter/10.1007/978-3-642-53914-5_14"
}

Documents

mlsp_adma