Sciweavers

Share
ICDM
2008
IEEE

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

12 years 2 months ago
Fast and Memory Efficient Mining of High Utility Itemsets in Data Streams
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.
Hua-Fu Li, Hsin-Yun Huang, Yi-Cheng Chen, Yu-Jiun
Added 30 May 2010
Updated 30 May 2010
Type Conference
Year 2008
Where ICDM
Authors Hua-Fu Li, Hsin-Yun Huang, Yi-Cheng Chen, Yu-Jiun Liu, Suh-Yin Lee
Comments (0)
books