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KDD
2006
ACM
164views Data Mining» more  KDD 2006»
16 years 6 months ago
Sampling from large graphs
Given a huge real graph, how can we derive a representative sample? There are many known algorithms to compute interesting measures (shortest paths, centrality, betweenness, etc.)...
Jure Leskovec, Christos Faloutsos
KDD
2005
ACM
157views Data Mining» more  KDD 2005»
16 years 6 months 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
KDD
2005
ACM
194views Data Mining» more  KDD 2005»
16 years 6 months ago
Web object indexing using domain knowledge
Web object is defined to represent any meaningful object embedded in web pages (e.g. images, music) or pointed to by hyperlinks (e.g. downloadable files). Users usually search for...
Muyuan Wang, Zhiwei Li, Lie Lu, Wei-Ying Ma, Naiya...
WSDM
2010
ACM
322views Data Mining» more  WSDM 2010»
16 years 3 months ago
Inferring Search Behaviors Using Partially Observable Markov (POM) Model
This article describes an application of the partially observable Markov (POM) model to the analysis of a large scale commercial web search log. Mathematically, POM is a variant o...
Kuansan Wang, Nikolas Gloy, Xiaolong Li
SDM
2009
SIAM
164views Data Mining» more  SDM 2009»
16 years 3 months ago
Exact Discovery of Time Series Motifs.
Time series motifs are pairs of individual time series, or subsequences of a longer time series, which are very similar to each other. As with their discrete analogues in computat...
Abdullah Mueen, Eamonn J. Keogh, M. Brandon Westov...