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Closed Frequent Itemset Mining over Fast Data Stream Based on Hadoop

Authors:
Shan Jicheng
Liu Qingbao

Keywords: data stream; closed frequent itemsets; mapreduce.

Abstract:
Mining closed frequent itemsets provides complete and condensed information for non-redundant association rules generation. Online mining of closed frequent itemsets over streaming data is one of the most important issues in mining data streams. In this paper, we extend two types of methods to MapReduce platform to mine closed frequent itemset over fast data streams. Experiments show that both methods have performance improvement with more mapper nodes and the vertical format data method has higher speed to process fast data streams.

Pages: 1 to 6

Copyright: Copyright (c) IARIA, 2015

Publication date: June 21, 2015

Published in: conference

ISSN: 2326-9332

ISBN: 978-1-61208-415-2

Location: Brussels, Belgium

Dates: from June 21, 2015 to June 26, 2015