Assessing single-pair similarity over graphs by aggregating first-meeting probabilities
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AbstractLink-based similarity plays an important role in measuring similarities between nodes in a graph. As a widely used link-based similarity, SimRank scores similarity between two nodes as the first-meeting probability of two random surfers. However, due to the large scale of graphs in real-world applications and dynamic change characteristic, it is not viable to frequently update the whole similarity matrix. Also, people often only concern about the similarities of a small subset of nodes in a graph. In such a case, the existing approaches need to compute the similarities of all node-pairs simultaneously, suffering from high computation cost.
All Author(s) ListHe J, Liu HY, Yu JX, Li P, He W, Du XY
Journal nameInformation Systems
Year2014
Month6
Day1
Volume Number42
PublisherElsevier
Pages107 - 122
ISSN0306-4379
eISSN1873-6076
LanguagesEnglish-United Kingdom
KeywordsAlgorithm; First-meeting probabilities; Graph mining; Link graph; Similarity measure; SimRank
Web of Science Subject CategoriesComputer Science; Computer Science, Information Systems

Last updated on 2021-22-01 at 00:26