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» Learning random walks to rank nodes in graphs
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ICML
2007
IEEE
14 years 5 months ago
Learning random walks to rank nodes in graphs
Ranking nodes in graphs is of much recent interest. Edges, via the graph Laplacian, are used to encourage local smoothness of node scores in SVM-like formulations with generalizat...
Alekh Agarwal, Soumen Chakrabarti
ALT
2010
Springer
12 years 11 months ago
PageRank Optimization in Polynomial Time by Stochastic Shortest Path Reformulation
Abstract. The importance of a node in a directed graph can be measured by its PageRank. The PageRank of a node is used in a number of application contexts
Balázs Csanád Csáji, Rapha&eu...
SDM
2012
SIAM
304views Data Mining» more  SDM 2012»
11 years 7 months ago
Fast Random Walk Graph Kernel
Random walk graph kernel has been used as an important tool for various data mining tasks including classification and similarity computation. Despite its usefulness, however, it...
U. Kang, Hanghang Tong, Jimeng Sun
KDD
2010
ACM
252views Data Mining» more  KDD 2010»
13 years 8 months ago
Fast query execution for retrieval models based on path-constrained random walks
Many recommendation and retrieval tasks can be represented as proximity queries on a labeled directed graph, with typed nodes representing documents, terms, and metadata, and labe...
Ni Lao, William W. Cohen
ICML
2008
IEEE
14 years 5 months ago
Fast incremental proximity search in large graphs
In this paper we investigate two aspects of ranking problems on large graphs. First, we augment the deterministic pruning algorithm in Sarkar and Moore (2007) with sampling techni...
Purnamrita Sarkar, Andrew W. Moore, Amit Prakash