標題: An efficient algorithm for mining temporal high utility itemsets from data streams
作者: Chu, Chun-Jung
Tseng, Vincent S.
Liang, Tyne
資訊工程學系
Department of Computer Science
關鍵字: utility mining;temporal high utility itemsets;data stream mining;association rules
公開日期: 1-Jul-2008
摘要: Utility of an itemset is considered as the value of this itemset, and utility mining aims at identifying the itemsets with high utilities. The temporal high utility itemsets are the itemsets whose support is larger than a pre-specified threshold in current time window of the data stream. Discovery of temporal high utility itemsets is an important process for mining interesting patterns like association rules from data streams. In this paper, we propose a novel method, namely THUI (Temporal High Utility Itemsets)-Mine, for mining temporal high utility itemsets from data streams efficiently and effectively. To the best of our knowledge, this is the first work on mining temporal high utility itemsets from data streams. The novel contribution of THUI-Mine is that it can effectively identify the temporal high utility itemsets by generating fewer candidate itemsets such that the execution time can be reduced substantially in mining all high utility itemsets in data streams. In this way, the process of discovering all temporal high utility itemsets under all time windows of data streams can be achieved effectively with less memory space and execution time. This meets the critical requirements on time and space efficiency for mining data streams. Through experimental evaluation, THUI-Mine is shown to significantly outperform other existing methods like Two-Phase algorithm under various experimental conditions. (c) 2007 Elsevier Inc. All rights reserved.
URI: http://dx.doi.org/10.1016/j.jss.2007.07.026
http://hdl.handle.net/11536/8592
ISSN: 0164-1212
DOI: 10.1016/j.jss.2007.07.026
期刊: JOURNAL OF SYSTEMS AND SOFTWARE
Volume: 81
Issue: 7
起始頁: 1105
結束頁: 1117
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