Paper Title:
Multi-Relational Sequential Pattern Mining Based on Iceberg Concept Lattice
  Abstract

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
Chapter
Chapter 6: Materials and Mechanics Information System
Edited by
Yongping Zhang, Linhua Zhou and Elwin Mao
Pages
729-733
DOI
10.4028/www.scientific.net/AMM.109.729
Citation
J. Yin, Y. Li, C. C. Shen, B. Liu, "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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