A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is `application/pdf`

.

##
###
Towards efficient SimRank computation on large networks

2013
*
2013 IEEE 29th International Conference on Data Engineering (ICDE)
*

SimRank has been a powerful model for assessing the similarity of pairs of vertices in a graph. It is based on the concept that two vertices are similar if they are referenced by similar vertices. Due to its self-referentiality, fast SimRank computation on large graphs poses significant challenges. The state-of-the-art work [16] exploits partial sums memorization for computing SimRank in O(Kmn) time on a graph with n vertices and m edges, where K is the number of iterations. Partial sums

doi:10.1109/icde.2013.6544859
dblp:conf/icde/YuLZ13
fatcat:g54pw7ghpjdd7gcsgvtm7hdi3q