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» Kernels and Regularization on Graphs
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AIRWEB
2008
Springer
15 years 1 months ago
Web spam identification through content and hyperlinks
We present an algorithm, witch, that learns to detect spam hosts or pages on the Web. Unlike most other approaches, it simultaneously exploits the structure of the Web graph as we...
Jacob Abernethy, Olivier Chapelle, Carlos Castillo
CORR
2006
Springer
161views Education» more  CORR 2006»
14 years 12 months ago
Consensus Propagation
We propose consensus propagation, an asynchronous distributed protocol for averaging numbers across a network. We establish convergence, characterize the convergence rate for regul...
Ciamac Cyrus Moallemi, Benjamin Van Roy
KDD
2005
ACM
157views Data Mining» more  KDD 2005»
16 years 8 days ago
A fast kernel-based multilevel algorithm for graph clustering
Graph clustering (also called graph partitioning) -- clustering the nodes of a graph -- is an important problem in diverse data mining applications. Traditional approaches involve...
Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis
SIGMOD
2008
ACM
144views Database» more  SIGMOD 2008»
16 years 11 hour ago
Mining significant graph patterns by leap search
With ever-increasing amounts of graph data from disparate sources, there has been a strong need for exploiting significant graph patterns with user-specified objective functions. ...
Xifeng Yan, Hong Cheng, Jiawei Han, Philip S. Yu
IWPEC
2009
Springer
15 years 6 months ago
Improved Induced Matchings in Sparse Graphs
An induced matching in graph G is a matching which is an induced subgraph of G. Clearly, among two vertices with the same neighborhood (called twins) at most one is matched in any...
Rok Erman, Lukasz Kowalik, Matjaz Krnc, Tomasz Wal...