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Abstract
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Article Information:
Frequent Pattern Mining for Multiple Minimum Supports with Support Tuning and Tree Maintenance on Incremental Database
F.A. Hoque, M. Debnath, N. Easmin, K. Rashed
Corresponding Author: Farhana Afrin Hoque
Submitted: 2011 May, 17
Accepted: 2011 July, 02
Published: 2011 September, 30 |
Abstract:
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Mining frequent patterns in transactional databases is an important part of the association rule
mining. Frequent pattern mining algorithms with single minsup leads to rare item problem. Instead of setting
single minsup for all items, we have used multiple minimum supports to discover frequent patterns. In this
research, we have used multiple item support tree (MIS-Tree for short) to mine frequent patterns and proposed
algorithms that provide (1) a complete facility of multiple support tuning (MS Tuning), and (2) maintenance
of MIS-tree with incremental update of database. In a recent study on the same problem, MIS-tree and CFPgrowth
algorithm has been developed to find all frequent item sets as well as to maintain MS tuning with some
restrictions. In this study, we have modified the maintenance method by adding the benefit of flexible MS
tuning without any restriction. Again, since database is subject to practice, an incremental updating technique
has been proposed for maintenance of the MIS-tree after the database is updated. This maintenance ensures that
every time an incremental database is added to the original database, the tree can be kept in correct status
without costly rescanning of the aggregated database. Experiments on both synthetic and real data sets
demonstrate the effectiveness of our proposed approaches.
Key words: Association rules, database, data mining, frequent pattern, minimum supports, support tuning,
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Cite this Reference:
F.A. Hoque, M. Debnath, N. Easmin, K. Rashed, . Frequent Pattern Mining for Multiple Minimum Supports with Support Tuning and Tree Maintenance on Incremental Database. Research Journal of Information Technology , (2): 79-90.
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ISSN (Online): 2041-3114
ISSN (Print): 2041-3106 |
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