Assessing single-pair similarity over graphs by aggregating first-meeting probabilities
Publication in refereed journal


引用次數
替代計量分析
.

其它資訊
摘要Link-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.
著者He J, Liu HY, Yu JX, Li P, He W, Du XY
期刊名稱Information Systems
出版年份2014
月份6
日期1
卷號42
出版社Elsevier
頁次107 - 122
國際標準期刊號0306-4379
電子國際標準期刊號1873-6076
語言英式英語
關鍵詞Algorithm; First-meeting probabilities; Graph mining; Link graph; Similarity measure; SimRank
Web of Science 學科類別Computer Science; Computer Science, Information Systems

上次更新時間 2021-23-02 於 00:14