Proceedings of the 2015 5th International Conference on Computer Sciences and Automation Engineering

An Algorithm of Mining Closed Frequent Itemsets

Authors
Haifeng Li
Corresponding Author
Haifeng Li
Available Online February 2016.
DOI
10.2991/iccsae-15.2016.20How to use a DOI?
Keywords
Closed Frequent Itemset, Sampling, Data Mining.
Abstract

Closed frequent itemset is a perfect representation of frequent itemset. This paper tries to find an efficient solution to mine the closed frequent itemsets over databases by sampling technique. We employ the SCFI tree to record the data synopsis of the frequent itemsets, and propose an efficient algorithm SCFI to maintain the SCFI. We conduct the experiments over standard benchmark datasets, and the results show that sampling is an effective method to improve the performance when mining the closed frequent itemsets.

Copyright
© 2016, 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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Volume Title
Proceedings of the 2015 5th International Conference on Computer Sciences and Automation Engineering
Series
Advances in Computer Science Research
Publication Date
February 2016
ISBN
978-94-6252-156-8
ISSN
2352-538X
DOI
10.2991/iccsae-15.2016.20How to use a DOI?
Copyright
© 2016, 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/).

Cite this article

TY  - CONF
AU  - Haifeng Li
PY  - 2016/02
DA  - 2016/02
TI  - An Algorithm of Mining Closed Frequent Itemsets
BT  - Proceedings of the 2015 5th International Conference on Computer Sciences and Automation Engineering
PB  - Atlantis Press
SP  - 95
EP  - 98
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccsae-15.2016.20
DO  - 10.2991/iccsae-15.2016.20
ID  - Li2016/02
ER  -