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: 書貢獻/報告類型會議論文篇章同行評審

68 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???core.languages.en_GB???
主出版物標題Proceedings - 8th IEEE International Conference on Data Mining, ICDM 2008
頁面881-886
頁數6
DOIs
出版狀態已出版 - 2008
事件8th IEEE International Conference on Data Mining, ICDM 2008 - Pisa, Italy
持續時間: 15 12月 200819 12月 2008

出版系列

名字Proceedings - IEEE International Conference on Data Mining, ICDM
ISSN(列印)1550-4786

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???event.eventtypes.event.conference???8th IEEE International Conference on Data Mining, ICDM 2008
國家/地區Italy
城市Pisa
期間15/12/0819/12/08

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