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KDD
2009
ACM
164views Data Mining» more  KDD 2009»
15 years 10 months ago
Social influence analysis in large-scale networks
In large social networks, nodes (users, entities) are influenced by others for various reasons. For example, the colleagues have strong influence on one's work, while the fri...
Jie Tang, Jimeng Sun, Chi Wang, Zi Yang
KDD
2009
ACM
611views Data Mining» more  KDD 2009»
15 years 10 months ago
Fast approximate spectral clustering
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-s...
Donghui Yan, Ling Huang, Michael I. Jordan
KDD
2008
ACM
178views Data Mining» more  KDD 2008»
15 years 10 months ago
Training structural svms with kernels using sampled cuts
Discriminative training for structured outputs has found increasing applications in areas such as natural language processing, bioinformatics, information retrieval, and computer ...
Chun-Nam John Yu, Thorsten Joachims
KDD
2007
ACM
176views Data Mining» more  KDD 2007»
15 years 10 months ago
Mining correlated bursty topic patterns from coordinated text streams
Previous work on text mining has almost exclusively focused on a single stream. However, we often have available multiple text streams indexed by the same set of time points (call...
Xuanhui Wang, ChengXiang Zhai, Xiao Hu, Richard Sp...
KDD
2007
ACM
178views Data Mining» more  KDD 2007»
15 years 10 months ago
Practical learning from one-sided feedback
In many data mining applications, online labeling feedback is only available for examples which were predicted to belong to the positive class. Such applications include spam filt...
D. Sculley
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