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...
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...
Previous work on mining transactional database has focused primarily on mining frequent itemsets, association rules, and sequential patterns. However, interesting relationships be...
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...
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 ...