2010Unpublished venueRequires access

Data Stream Frequent Pattern Mining

Xiaolei Zhao

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Abstract

Data stream mining has attracted many researchers' attention and has become a useful tool for many fields.A fundamental problem is how to use the limited storage space to mine frequent pattern efficiently.Various frequent pattern mining algorithms are analyzed and their classifications are pointed out in this paper.Finally,future directions in data mining stream research are discussed.

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What this paper is about

Data stream mining has attracted many researchers' attention and has become a useful tool for many fields.A fundamental problem is how to use the limited storage space to mine frequent pattern efficiently.Various frequent pattern mining algorithms are analyzed and their classifications are pointed out in this paper.Finally,future directions in data mining stream research are discussed.

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Available abstract

Data stream mining has attracted many researchers' attention and has become a useful tool for many fields.A fundamental problem is how to use the limited storage space to mine frequent pattern efficiently.Various frequent pattern mining algorithms are analyzed and their classifications are pointed out in this paper.Finally,future directions in data mining stream research are discussed.

Key concepts: Computer science, Data stream mining, Data mining, Data stream, Data science, Space (punctuation), Operating system, Telecommunications

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