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» Graph Mining based on a Data Partitioning Approach
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105
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ICDM
2010
IEEE
125views Data Mining» more  ICDM 2010»
15 years 1 months ago
Topic Modeling Ensembles
: Topic Modeling Ensembles Zhiyong Shen, Ping Luo, Shengwen Yang, Xukun Shen HP Laboratories HPL-2010-158 Topic model, Ensemble In this paper we propose a framework of topic model...
Zhiyong Shen, Ping Luo, Shengwen Yang, Xukun Shen
138
Voted
KDD
2009
ACM
178views Data Mining» more  KDD 2009»
16 years 4 months ago
Catching the drift: learning broad matches from clickthrough data
Identifying similar keywords, known as broad matches, is an important task in online advertising that has become a standard feature on all major keyword advertising platforms. Eff...
Sonal Gupta, Mikhail Bilenko, Matthew Richardson
141
Voted
FSTTCS
2009
Springer
15 years 8 months ago
Bounded Size Graph Clustering with Applications to Stream Processing
We introduce a graph clustering problem motivated by a stream processing application. Input to our problem is an undirected graph with vertex and edge weights. A cluster is a subse...
Rohit Khandekar, Kirsten Hildrum, Sujay Parekh, De...
108
Voted
KDD
2009
ACM
192views Data Mining» more  KDD 2009»
16 years 4 months ago
Co-evolution of social and affiliation networks
In our work, we address the problem of modeling social network generation which explains both link and group formation. Recent studies on social network evolution propose generati...
Elena Zheleva, Hossam Sharara, Lise Getoor
KDD
2007
ACM
178views Data Mining» more  KDD 2007»
16 years 3 months ago
Density-based clustering for real-time stream data
Existing data-stream clustering algorithms such as CluStream are based on k-means. These clustering algorithms are incompetent to find clusters of arbitrary shapes and cannot hand...
Yixin Chen, Li Tu