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Conference, International Asia-Pacific Web (2010)
Buscan, Korea
Apr. 6, 2010 to Apr. 8, 2010
ISBN: 978-0-7695-4012-2
pp: 157-163
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
Xu Jia, Li Zou, Jun He, Xiaoyong Du, Yuanzhe Cai, Hongyan Liu, "Local Methods for Estimating SimRank Score", Conference, International Asia-Pacific Web, vol. 00, no. , pp. 157-163, 2010, doi:10.1109/APWeb.2010.47
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