標題: | Fast and Memory Efficient Mining of High Utility Itemsets in Data Streams |
作者: | Li, Hua-Fu Huang, Hsin-Yun Chen, Yi-Cheng Liu, Yu-Jiun Lee, Suh-Yin 資訊工程學系 Department of Computer Science |
公開日期: | 2008 |
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. |
URI: | http://dx.doi.org/10.1109/ICDM.2008.107 http://hdl.handle.net/11536/135084 |
ISBN: | 978-0-7695-3502-9 |
ISSN: | 1550-4786 |
DOI: | 10.1109/ICDM.2008.107 |
期刊: | ICDM 2008: EIGHTH IEEE INTERNATIONAL CONFERENCE ON DATA MINING, PROCEEDINGS |
起始頁: | 881 |
結束頁: | + |
顯示於類別: | 會議論文 |