Efficiently mining frequent subpaths

Authors:
Sumanta Guha
Affiliations:
Computer Science & Information Management Program Asian Institute of Technology, Klong Luang, Pathumthani, Thailand
Venue:
AusDM '09 Proceedings of the Eighth Australasian Data Mining Conference - Volume 101
Year:
2009

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Abstract

The problem considered is that of finding frequent subpaths of a database of paths in a fixed undirected graph. This problem arises in applications such as predicting congestion in network traffic. An algorithm based on Apriori, called AFS, is developed, but with significantly improved efficiency through exploiting the underlying graph structure, which makes AFS feasible for practical input path sizes. It is also proved that a natural generalization of the frequent subpaths problem is not amenable to any solution quicker than Apriori.