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2002
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OSSM: A Segmentation Approach to Optimize Frequency Counting

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OSSM: A Segmentation Approach to Optimize Frequency Counting
Computing the frequency of a pattern is one of the key operations in data mining algorithms. We describe a simple yet powerful way of speeding up any form of frequency counting satisfying the monotonicity condition. Our method, the optimized segment support map (OSSM), is a light-weight structure which partitions the collection of transactions into segments, so as to reduce the number of candidate patterns that require frequency counting. We study the following problems: (1) What is the optimal number of segments to be used; and (2) Given a user-determined , what is the best segmentation/composition of the segments? For Problem 1, we provide a thorough analysis and a theorem establishing the minimum value of for which there is no accuracy lost in using the OSSM. For Problem 2, we develop various algorithms and heuristics, which efficiently generate OSSMs that are compact and effective, to help facilitate segmentation.
Carson Kai-Sang Leung, Raymond T. Ng, Heikki Manni
Added 01 Nov 2009
Updated 01 Nov 2009
Type Conference
Year 2002
Where ICDE
Authors Carson Kai-Sang Leung, Raymond T. Ng, Heikki Mannila
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