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ICDM
2007
IEEE
169views Data Mining» more  ICDM 2007»
13 years 11 months ago
Efficient Discovery of Frequent Approximate Sequential Patterns
We propose an efficient algorithm for mining frequent approximate sequential patterns under the Hamming distance model. Our algorithm gains its efficiency by adopting a "brea...
Feida Zhu, Xifeng Yan, Jiawei Han, Philip S. Yu
ADC
2008
Springer
156views Database» more  ADC 2008»
14 years 1 months ago
Interactive Mining of Frequent Itemsets over Arbitrary Time Intervals in a Data Stream
Mining frequent patterns in a data stream is very challenging for the high complexity of managing patterns with bounded memory against the unbounded data. While many approaches as...
Ming-Yen Lin, Sue-Chen Hsueh, Sheng-Kun Hwang
ICDE
2005
IEEE
146views Database» more  ICDE 2005»
14 years 9 months ago
Mining Evolving Customer-Product Relationships in Multi-Dimensional Space
Previous work on mining transactional database has focused primarily on mining frequent itemsets, association rules, and sequential patterns. However, interesting relationships be...
Xiaolei Li, Jiawei Han, Xiaoxin Yin, Dong Xin
DKE
2008
113views more  DKE 2008»
13 years 7 months ago
An efficient algorithm for mining closed inter-transaction itemsets
In this paper, we propose an efficient algorithm, called ICMiner (Inter-transaction Closed patterns Miner), for mining closed inter-transaction itemsets. Our proposed algorithm co...
Anthony J. T. Lee, Chun-sheng Wang, Wan-Yu Weng, Y...
ESWA
2006
139views more  ESWA 2006»
13 years 7 months ago
An efficient data mining approach for discovering interesting knowledge from customer transactions
Mining association rules and mining sequential patterns both are to discover customer purchasing behaviors from a transaction database, such that the quality of business decision ...
Show-Jane Yen, Yue-Shi Lee