Efficient Mining of Frequent Sequence Generators
Sequential pattern mining has raised great interest in data mining research field in recent years. However, to our best knowledge, no existing work studies the problem of frequent sequence generator mining. In this paper we present a novel algorithm, FEAT (abbr. Frequent sEquence generATor miner), to perform this task. Experimental results show that FEAT is more efficient than traditional sequential pattern mining algorithms but generates more concise result set, and is very effective for classifying Web product reviews.
Sequence Generators Sequence Web Mining
Chuancong Gao Jianyong Wang Yukai He Lizhu Zhou
Tsinghua University, Beijing, 100084, P.R.China
国际会议
第十七届国际万维网大会(the 17th International World Wide Web Conference)(WWW08)
北京
英文
2008-04-21（万方平台首次上网日期，不代表论文的发表时间）