Detail publikace

MLSP: Mining Hierarchically-Closed Multi-Level Sequential Patterns

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

Originální název

MLSP: Mining Hierarchically-Closed Multi-Level Sequential Patterns

Typ

článek ve sborníku mimo WoS a Scopus

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

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

Autoři

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

Rok RIV

2013

Vydáno

14. 12. 2013

Nakladatel

Springer Verlag

Místo

Hangzhou

ISBN

978-3-642-53913-8

Kniha

9th International Conference, ADMA 2013

Edice

Lecture Notes in Computer Science

Strany od

157

Strany do

168

Strany počet

12

URL

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"
}