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Title

Mining Weighted Frequent Patterns from Path Traversals on Weighted Graph

Author

Seong Dae Lee, Hyu Chan Park

Citation

Vol. 7  No. 4  pp. 140-148

Abstract

A lot of real world problems can be modeled as traversals on graph, and mining from such traversals has been found useful in several applications. However, previous works considered only traversals on unweighted graph. This paper generalizes this to the case where vertices of graph are given weights to reflect their importance. Under such weight settings, traditional mining algorithms can not be adopted directly any more. To cope with the problem, this paper proposes new algorithms to discover weighted frequent patterns from the traversals. Specifically, we devise support bound paradigms for candidate generation and pruning during the mining process.

Keywords

Data mining, Graph, Traversal, Weighted frequent pattern.

URL

http://paper.ijcsns.org/07_book/200704/20070419.pdf