A Generalized Weighted Closed Sequential Pattern Mining Algorithm with Item Interval

DOI

10.2991/amcce-15.2015.286How to use a DOI?

Keywords

weighted sequential patterns; closed sequential patterns; item interval

Abstract

The algorithm of this paper inserts pseudo items which are converted from item interval to obtain equal extended sequence database; it defines item-interval constraints, which are relative to the item weight, to prune the mining patterns. Through doing this, the algorithm avoids mining the patterns which users are not interested in and shortens the running time. It adopts histogram statistic pattern to get the standardization description to item interval of the mining patterns, making the mining sequences include the item interval information which is valuable to user decision.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Haitao Lu
AU  - Shuo Li
PY  - 2015/04
DA  - 2015/04
TI  - A Generalized Weighted Closed Sequential Pattern Mining Algorithm with Item Interval
BT  - Proceedings of the 2015 International Conference on Automation, Mechanical Control and Computational Engineering
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/amcce-15.2015.286
DO  - 10.2991/amcce-15.2015.286
ID  - Lu2015/04
ER  -