@inproceedings{3293331a5b7b436fb701b923d4a50801,
title = "An improved approach for sequential utility pattern mining",
abstract = "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.",
keywords = "data mining, high sequence utility upper-bound patterns, high sequential utility patterns, upper-bound",
author = "Lan, {Guo Cheng} and Hong, {Tzung Pei} and S. Tseng and Wang, {Shyue Liang}",
year = "2012",
month = dec,
day = "1",
doi = "10.1109/GrC.2012.6468697",
language = "English",
isbn = "9781467323093",
series = "Proceedings - 2012 IEEE International Conference on Granular Computing, GrC 2012",
pages = "226--230",
booktitle = "Proceedings - 2012 IEEE International Conference on Granular Computing, GrC 2012",
note = "2012 IEEE International Conference on Granular Computing, GrC 2012 ; Conference date: 11-08-2012 Through 13-08-2012",
}