Closed Sequential Pattern Mining Algorithm Based Positional Data
This paper proposed a new closed sequential pattern mining algorithm.The algorithm used a list of positional data to reserve the information of item ordering .By using these positional data, we developed two main pruning techniques, backward super-pattern condition and same positional data condition. To ensure correct and compact resulted lattice, we also manipulated some special conditions. From the experimental results, our algorithm outperforms CloSpan in the cases of moderately large datasets and low support threshold.
data mining sequential pattern dosed sequential pattern backward super-patter
Zhu Zhenxin Lu Jiaguo
Department of Computer Hebei Vocational College of Politics and Law Shijiazhuang,HeibeiProvince, Chi Department of Computer Zaozhuang University Zaozhuang, Shandong Province,China
国际会议
北京
英文
22-26
2010-09-18（万方平台首次上网日期，不代表论文的发表时间）