WTPMiner: efficient mining of weighted frequent patterns based on graph traversals

Authors:
Runian Geng;Wenbo Xu;Xiangjun Dong
Affiliations:
School of Information Technology, Jiangnan University, Wuxi, Jiangsu, China and School of Information Science and Technology, Shandong Institute of Light Industry, Jinan, Shandong, China;School of Information Technology, Jiangnan University, Wuxi, Jiangsu, China;School of Information Science and Technology, Shandong Institute of Light Industry, Jinan, Shandong, China
Venue:
KSEM'07 Proceedings of the 2nd international conference on Knowledge science, engineering and management
Year:
2007

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Abstract

Data mining for traversal patterns has been found useful in several applications. Traditional model of traversal patterns mining only considered un-weighted traversals. In this paper, a transformable model of EWDG(Edge-Weighted Directed Graph) andVWDG(Vertex-Weighted Directed Graph) is proposed. Based on the model and the notion of support bound, a new algorithm, called WTPMiner(Weighted Traversal Patterns Miner), and two methods for the estimations of algorithm are developed to discover weighted frequent patterns from the traversals on graph. Experimental results show the effect of different estimation method of support bound.