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An improved algorithm of mining Strong Jumping Emerging Patterns based on sorted SJEP-Tree

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2 Author(s)
Xiangtao Chen ; Sch. of Comput. & Commun., Hunan Univ., Changsha, China ; Lijuan Lu

Jumping Emerging Patterns (JEPs) are a data mining model that is useful as a mean of discovering differences present amongst a collection of classified transaction datasets. However, current JEPs mining algorithms are usually time-consuming and pruning with minimum support may require several adjustments. In this paper, we investigate Strong Jumping Emerging Patterns (SJEPs), which are believed to be high quality patterns with the most differentiating power. We propose an improved tree-based method to effectively mine SJEPs of two data classes. Experimental results show that our algorithm is effective.

Published in:

Bio-Inspired Computing: Theories and Applications (BIC-TA), 2010 IEEE Fifth International Conference on

Date of Conference:

23-26 Sept. 2010