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
Volume Number42
Pages107 - 122
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 2021-14-04 at 23:44