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A frequent pattern mining algorithm based on FP-growth without generating tree


Tohid, Hossein and Ibrahim, Hamidah (2010) A frequent pattern mining algorithm based on FP-growth without generating tree. In: Knowledge Management International Conference 2010 (KMICe2010), 25-27 May 2010, Kuala Terengganu, Malaysia.

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Abstract

An interesting method to frequent pattern mining without generating candidate pattern is called frequent-pattern growth, or simply FP-growth, which adopts a divide-and-conquer strategy as follows.First, it compresses the database representing frequent items into a frequent-pattern tree, or FP-tree, which retains the itemset association information. It then divides the compressed database into a set of conditional databases (a special kind of projected database), each associated with one frequent item or pattern fragment, and mines each such database separately.For a large database, constructing a large tree in the memory is a time consuming task and increase the time of execution.In this paper we introduce an algorithm to generate frequent patterns without generating a tree and therefore improve the time complexity and memory complexity as well.Our algorithm works based on prime factorization, and is called Frequent Pattern- Prime Factorization (FPPF).

Item Type: Conference or Workshop Item (Paper)
Additional Information: ISBN 978-983-2078-40-1 Organized by: UUM College of Art & Sciences, Universiti Utara Malaysia
Uncontrolled Keywords: Data Mining, Frequent Pattern Mining, Association Rule Mining
Subjects: H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
Divisions: College of Arts and Sciences
Depositing User: Mrs. Norazmilah Yaakub
Date Deposited: 05 Jun 2014 01:16
Last Modified: 05 Jun 2014 01:16
URI: http://repo.uum.edu.my/id/eprint/11250

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