Proceedings of the 2015 International Conference on Automation, Mechanical Control and Computational Engineering

A Generalized Weighted Closed Sequential Pattern Mining Algorithm with Item Interval

Authors
Haitao Lu, Shuo Li
Corresponding Author
Haitao Lu
Available Online April 2015.
DOI
https://doi.org/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.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
2015 International Conference on Automation, Mechanical Control and Computational Engineering
Part of series
Advances in Intelligent Systems Research
Publication Date
April 2015
ISBN
978-94-62520-64-6
ISSN
1951-6851
DOI
https://doi.org/10.2991/amcce-15.2015.286How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

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  - 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  - https://doi.org/10.2991/amcce-15.2015.286
ID  - Lu2015/04
ER  -