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KDD
2012
ACM
229views Data Mining» more  KDD 2012»
11 years 10 months ago
Finding trendsetters in information networks
Influential people have an important role in the process of information diffusion. However, there are several ways to be influential, for example, to be the most popular or the...
Diego Sáez-Trumper, Giovanni Comarela, Virg...
KDD
2012
ACM
200views Data Mining» more  KDD 2012»
11 years 10 months ago
Vertex neighborhoods, low conductance cuts, and good seeds for local community methods
The communities of a social network are sets of vertices with more connections inside the set than outside. We theoretically demonstrate that two commonly observed properties of s...
David F. Gleich, C. Seshadhri
WWW
2007
ACM
14 years 8 months ago
Finding community structure in mega-scale social networks: [extended abstract]
[Extended Abstract] Ken Wakita Tokyo Institute of Technology 2-12-1 Ookayama, Meguro-ku Tokyo 152-8552, Japan wakita@is.titech.ac.jp Toshiyuki Tsurumi Tokyo Institute of Technolog...
Ken Wakita, Toshiyuki Tsurumi
WAW
2004
Springer
178views Algorithms» more  WAW 2004»
14 years 29 days ago
Communities Detection in Large Networks
We develop an algorithm to detect community structure in complex networks. The algorithm is based on spectral methods and takes into account weights and links orientations. Since t...
Andrea Capocci, Vito Domenico Pietro Servedio, Gui...
NIPS
2001
13 years 9 months ago
Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering
Drawing on the correspondence between the graph Laplacian, the Laplace-Beltrami operator on a manifold, and the connections to the heat equation, we propose a geometrically motiva...
Mikhail Belkin, Partha Niyogi