Fast and Memory Efficient Mining of High Utility Itemsets in Data Streams

Hua Fu Li, Hsin-Yun Huang, Yi-Cheng Chen, Yu-Jiun Liu, Suh-Yin Lee

研究成果: Chapter同行評審

57 引文 斯高帕斯(Scopus)

摘要

Efficient mining of high utility itemsets has become one of the most interesting data mining tasks with broad applications. In this paper, we proposed two efficient one-pass algorithms, MHUI-BIT and MHUI-TID, for mining high utility itemsets from data streams within a transaction-sensitive sliding window. Two effective representations of item information and an extended lexicographical tree-based summary data structure are developed to improve the efficiency of mining high utility itemsets. Experimental results show that the proposed algorithms outperform than the existing algorithms for mining high utility itemsets from data streams.
原文English
主出版物標題ICDM 2008: EIGHTH IEEE INTERNATIONAL CONFERENCE ON DATA MINING, PROCEEDINGS
發行者IEEE
頁面88-+
ISBN(電子)978-0-7695-3502-9
ISBN(列印)978-0-7695-3502-9
DOIs
出版狀態Published - 2008
事件8th IEEE International Conference on Data Mining - Pisa, Italy
持續時間: 15 十二月 200819 十二月 2008

出版系列

名字IEEE International Conference on Data Mining
發行者IEEE
ISSN(列印)1550-4786
ISSN(電子)1550-4786

Conference

Conference8th IEEE International Conference on Data Mining
國家Italy
城市Pisa
期間15/12/0819/12/08

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