To search, Click below search items.


All Published Papers Search Service


Mining Weighted Frequent Patterns from Path Traversals on Weighted Graph


Seong Dae Lee, Hyu Chan Park


Vol. 7  No. 4  pp. 140-148


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.


Data mining, Graph, Traversal, Weighted frequent pattern.