Multi-Relational Sequential Pattern Mining Based on Iceberg Concept Lattice

Abstract:

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Multi-Relational Sequential mining is one of the areas of data mining that rapidly developed in recent years. However, the performance issues of traditional mining methods are not ideal. To effectively mining the pattern, we proposed an algorithm based on Iceberg concept lattice, adopting optimization methods of partition and merger to just mining the frequent sequences. Experimental results show this algorithm effectively reduced the time complexity of multi-relational sequential pattern mining.

Info:

Periodical:

Edited by:

Yongping Zhang, Linhua Zhou and Elwin Mao

Pages:

729-733

DOI:

10.4028/www.scientific.net/AMM.109.729

Citation:

J. Yin et al., "Multi-Relational Sequential Pattern Mining Based on Iceberg Concept Lattice", Applied Mechanics and Materials, Vol. 109, pp. 729-733, 2012

Online since:

October 2011

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Price:

$35.00

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