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2009•Journal of Kunming University of Science and TechnologyRequires access

An Algorithm for Mining Frequent Itemsets in Data Streams

Meng Cai-xia

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Abstract

Different from data in traditional static database,a data stream is an ordered sequence of items that arrives in timely order.Classical frequent item-sets mining method is difficult to apply to data stream.Based on the characteristics of data streams,FP-SegCount algorithm is proposed in this paper to mine frequent item-sets from data streams.The algorithm partitions the data stream and uses modified FP-growth algorithm to mine frequent item-sets in every segment.It then counts item-sets in Count Min Sketch.This algorithm solves compressed statistics and ensures effective computation.Through experimentation and comparison with FP-DS algorithm,FP SegCount algorithm is shown to have a good time efficiency.

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What this paper is about

Different from data in traditional static database,a data stream is an ordered sequence of items that arrives in timely order.Classical frequent item-sets mining method is difficult to apply to data stream.Based on the characteristics of data streams,FP-SegCount algorithm is proposed in this paper to mine frequent item-sets from data streams.The algorithm partitions the data stream and uses modified FP-growth algorithm to mine frequent item-sets in every segment.It then counts item-sets in Count Min Sketch.This algorithm solves compressed statistics and ensures effective computation.Through experimentation and comparison with FP-DS algorithm,FP SegCount algorithm is shown to have a good time efficiency.

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Available abstract

Different from data in traditional static database,a data stream is an ordered sequence of items that arrives in timely order.Classical frequent item-sets mining method is difficult to apply to data stream.Based on the characteristics of data streams,FP-SegCount algorithm is proposed in this paper to mine frequent item-sets from data streams.The algorithm partitions the data stream and uses modified FP-growth algorithm to mine frequent item-sets in every segment.It then counts item-sets in Count Min Sketch.This algorithm solves compressed statistics and ensures effective computation.Through experimentation and comparison with FP-DS algorithm,FP SegCount algorithm is shown to have a good time efficiency.

Key concepts: Data stream mining, Data mining, Computer science, Algorithm, GSP Algorithm, Data stream, Computation, Sketch

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