Abstract
Frequent pattern mining has attracted a great deal of interests during the recent surge in Web mining research because it is the basis of many applications such as customer behavior analysis and trend prediction. Researchers have proposed various data structures and algorithms to discover frequently occurring patterns from a given data set. In particular, tree structures have been popular since they can effectively represent the input data set for efficient pattern discovery. In this paper, we propose an efficient tree structure and its associated algorithm that provides a considerable performance improvement over CATS, one of the fastest frequent pattern mining algorithms known to date, in terms of memory usage and processing time. We demonstrate the effectiveness of our algorithm and performance improvement over me existing approach by a series of experiments.
| Original language | English |
|---|---|
| Pages (from-to) | 1665-1670 |
| Number of pages | 6 |
| Journal | Information (Japan) |
| Volume | 17 |
| Issue number | 5 |
| Publication status | Published - 2014 Jan 1 |
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ASJC Scopus subject areas
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Cite this
Efficient mining of frequent patterns based on a condensed tree structure. / Park, Byung Joon; Kim, Sang Young; Choi, Lynn.
In: Information (Japan), Vol. 17, No. 5, 01.01.2014, p. 1665-1670.Research output: Contribution to journal › Article
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TY - JOUR
T1 - Efficient mining of frequent patterns based on a condensed tree structure
AU - Park, Byung Joon
AU - Kim, Sang Young
AU - Choi, Lynn
PY - 2014/1/1
Y1 - 2014/1/1
N2 - Frequent pattern mining has attracted a great deal of interests during the recent surge in Web mining research because it is the basis of many applications such as customer behavior analysis and trend prediction. Researchers have proposed various data structures and algorithms to discover frequently occurring patterns from a given data set. In particular, tree structures have been popular since they can effectively represent the input data set for efficient pattern discovery. In this paper, we propose an efficient tree structure and its associated algorithm that provides a considerable performance improvement over CATS, one of the fastest frequent pattern mining algorithms known to date, in terms of memory usage and processing time. We demonstrate the effectiveness of our algorithm and performance improvement over me existing approach by a series of experiments.
AB - Frequent pattern mining has attracted a great deal of interests during the recent surge in Web mining research because it is the basis of many applications such as customer behavior analysis and trend prediction. Researchers have proposed various data structures and algorithms to discover frequently occurring patterns from a given data set. In particular, tree structures have been popular since they can effectively represent the input data set for efficient pattern discovery. In this paper, we propose an efficient tree structure and its associated algorithm that provides a considerable performance improvement over CATS, one of the fastest frequent pattern mining algorithms known to date, in terms of memory usage and processing time. We demonstrate the effectiveness of our algorithm and performance improvement over me existing approach by a series of experiments.
KW - Frequent pattern
KW - Pattern discovery
KW - Tree structure
UR - http://www.scopus.com/inward/record.url?scp=84903957328&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84903957328&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:84903957328
VL - 17
SP - 1665
EP - 1670
JO - Information (Japan)
JF - Information (Japan)
SN - 1343-4500
IS - 5
ER -