An improved approach for sequential utility pattern mining

Guo Cheng Lan, Tzung Pei Hong*, S. Tseng, Shyue Liang Wang

*Corresponding author for this work

研究成果: Conference contribution

3 引文 斯高帕斯(Scopus)

摘要

In this paper, we propose an efficient projection-based algorithm to discover high sequential utility patterns from quantitative sequence databases. An effective pruning strategy in the proposed algorithm is designed to tighten upper-bounds for subsequences in mining. By using the strategy, a large number of unpromising subsequences could be pruned to improve execution efficiency. Finally, the experimental results on synthetic datasets show the proposed algorithm outperforms the previously proposed algorithm under different parameter settings.

原文English
主出版物標題Proceedings - 2012 IEEE International Conference on Granular Computing, GrC 2012
頁面226-230
頁數5
DOIs
出版狀態Published - 1 十二月 2012
事件2012 IEEE International Conference on Granular Computing, GrC 2012 - HangZhou, China
持續時間: 11 八月 201213 八月 2012

出版系列

名字Proceedings - 2012 IEEE International Conference on Granular Computing, GrC 2012

Conference

Conference2012 IEEE International Conference on Granular Computing, GrC 2012
國家China
城市HangZhou
期間11/08/1213/08/12

引用此

Lan, G. C., Hong, T. P., Tseng, S., & Wang, S. L. (2012). An improved approach for sequential utility pattern mining. 於 Proceedings - 2012 IEEE International Conference on Granular Computing, GrC 2012 (頁 226-230). [6468697] (Proceedings - 2012 IEEE International Conference on Granular Computing, GrC 2012). https://doi.org/10.1109/GrC.2012.6468697