Using pruning and filtering strategies to speed-up projection-based utility mining

Guo Cheng Lan*, S. Tseng, Tzung Pei Hong, Chun Hao Chen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

In this paper, we try to improve the performance of utility mining. We propose a new projection-based mining algorithm and embed two pruning strategies in it to efficiently find high utility itemsets in a database. By using the two designed strategies, a large number of unpromising itemsets can be pruned away at an early stage, and the data size could recursively be reduced to save the scan time. Finally, the experimental results on synthetic datasets show the proposed algorithm runs faster than the other utility mining algorithms under different parameter settings.

Original languageEnglish
Title of host publicationProceedings 2011 International Conference on System Science and Engineering, ICSSE 2011
Pages400-404
Number of pages5
DOIs
StatePublished - 24 Aug 2011
Event2011 International Conference on System Science and Engineering, ICSSE 2011 - Macao, China
Duration: 8 Jun 201110 Jun 2011

Publication series

NameProceedings 2011 International Conference on System Science and Engineering, ICSSE 2011

Conference

Conference2011 International Conference on System Science and Engineering, ICSSE 2011
CountryChina
CityMacao
Period8/06/1110/06/11

Keywords

  • data mining
  • high transaction-weighted utilization itemsets
  • high utility itemsets
  • upper-bound
  • utility mining

Cite this

Lan, G. C., Tseng, S., Hong, T. P., & Chen, C. H. (2011). Using pruning and filtering strategies to speed-up projection-based utility mining. In Proceedings 2011 International Conference on System Science and Engineering, ICSSE 2011 (pp. 400-404). [5961936] (Proceedings 2011 International Conference on System Science and Engineering, ICSSE 2011). https://doi.org/10.1109/ICSSE.2011.5961936