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SDM
2011
SIAM
414views Data Mining» more  SDM 2011»
14 years 5 months ago
Clustered low rank approximation of graphs in information science applications
In this paper we present a fast and accurate procedure called clustered low rank matrix approximation for massive graphs. The procedure involves a fast clustering of the graph and...
Berkant Savas, Inderjit S. Dhillon
WSDM
2009
ACM
125views Data Mining» more  WSDM 2009»
15 years 9 months ago
Less is more: sampling the neighborhood graph makes SALSA better and faster
In this paper, we attempt to improve the effectiveness and the efficiency of query-dependent link-based ranking algorithms such as HITS, MAX and SALSA. All these ranking algorith...
Marc Najork, Sreenivas Gollapudi, Rina Panigrahy
ICDM
2006
IEEE
133views Data Mining» more  ICDM 2006»
15 years 8 months ago
An Experimental Investigation of Graph Kernels on a Collaborative Recommendation Task
This work presents a systematic comparison between seven kernels (or similarity matrices) on a graph, namely the exponential diffusion kernel, the Laplacian diffusion kernel, the ...
François Fouss, Luh Yen, Alain Pirotte, Mar...
ICDM
2005
IEEE
190views Data Mining» more  ICDM 2005»
15 years 7 months ago
Neighborhood Formation and Anomaly Detection in Bipartite Graphs
Many real applications can be modeled using bipartite graphs, such as users vs. files in a P2P system, traders vs. stocks in a financial trading system, conferences vs. authors ...
Jimeng Sun, Huiming Qu, Deepayan Chakrabarti, Chri...
KDD
2009
ACM
179views Data Mining» more  KDD 2009»
15 years 6 months ago
A viewpoint-based approach for interaction graph analysis
Recent innovations have resulted in a plethora of social applications on the Web, such as blogs, social networks, and community photo and video sharing applications. Such applicat...
Sitaram Asur, Srinivasan Parthasarathy