Conference, International Asia-Pacific Web (2010)

Buscan, Korea

Apr. 6, 2010 to Apr. 8, 2010

ISBN: 978-0-7695-4012-2

pp: 157-163

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/APWeb.2010.47

ABSTRACT

SimRank is a well known algorithm which conducts link analysis to measure similarity between each pair of nodes (nodepair). But it suffers from high computational cost, limiting its usage in large-scale datasets. Moreover, Links between nodes are changing over time. It may be desirable to quickly approximate the similarity score between certain nodepair without performing a large-scale computation on the entire graph. In our approach we propose a method to efficiently estimate the similarity score using only a small subgraph of the entire graph. We call this novel algorithm “Local-SimRank”. The experimental results conducted on real datasets and synthetic dataset show that our algorithm efficiently produces good approximations to the global SimRank scores. Meanwhile, we prove that the Local-SimRank score LS(a, b) is always less than original SimRank score S(a, b) mathematically.

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CITATION

X. Jia, L. Zou, J. He, X. Du, Y. Cai and H. Liu, "Local Methods for Estimating SimRank Score,"

*Conference, International Asia-Pacific Web(APWEB)*, Buscan, Korea, 2010, pp. 157-163.

doi:10.1109/APWeb.2010.47

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