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» Learning random walks to rank nodes in graphs
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WEBI
2005
Springer
14 years 29 days ago
WICER: A Weighted Inter-Cluster Edge Ranking for Clustered Graphs
Several algorithms based on link analysis have been developed to measure the importance of nodes on a graph such as pages on the World Wide Web. PageRank and HITS are the most pop...
Divya Padmanabhan, Prasanna Kumar Desikan, Jaideep...
CORR
2010
Springer
177views Education» more  CORR 2010»
13 years 7 months ago
Supervised Random Walks: Predicting and Recommending Links in Social Networks
Predicting the occurrence of links is a fundamental problem in networks. In the link prediction problem we are given a snapshot of a network and would like to infer which interact...
Lars Backstrom, Jure Leskovec
ICML
2006
IEEE
14 years 8 months ago
A new approach to data driven clustering
We consider the problem of clustering in its most basic form where only a local metric on the data space is given. No parametric statistical model is assumed, and the number of cl...
Arik Azran, Zoubin Ghahramani
SIGIR
2006
ACM
14 years 1 months ago
AggregateRank: bringing order to web sites
Since the website is one of the most important organizational structures of the Web, how to effectively rank websites has been essential to many Web applications, such as Web sear...
Guang Feng, Tie-Yan Liu, Ying Wang, Ying Bao, Zhim...
ITA
2006
163views Communications» more  ITA 2006»
13 years 7 months ago
Graph fibrations, graph isomorphism, and PageRank
PageRank is a ranking method that assigns scores to web pages using the limit distribution of a random walk on the web graph. A fibration of graphs is a morphism that is a local i...
Paolo Boldi, Violetta Lonati, Massimo Santini, Seb...