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ICDM
2003
IEEE
111views Data Mining» more  ICDM 2003»
15 years 5 months ago
OP-Cluster: Clustering by Tendency in High Dimensional Space
Clustering is the process of grouping a set of objects into classes of similar objects. Because of unknownness of the hidden patterns in the data sets, the definition of similari...
Jinze Liu, Wei Wang 0010
ICDM
2010
IEEE
200views Data Mining» more  ICDM 2010»
14 years 9 months ago
Bayesian Maximum Margin Clustering
Abstract--Most well-known discriminative clustering models, such as spectral clustering (SC) and maximum margin clustering (MMC), are non-Bayesian. Moreover, they merely considered...
Bo Dai, Baogang Hu, Gang Niu
KDD
2009
ACM
203views Data Mining» more  KDD 2009»
16 years 11 days ago
Characterizing individual communication patterns
The increasing availability of electronic communication data, such as that arising from e-mail exchange, presents social and information scientists with new possibilities for char...
R. Dean Malmgren, Jake M. Hofman, Luis A. N. Amara...
KDD
2008
ACM
164views Data Mining» more  KDD 2008»
16 years 7 days ago
Microscopic evolution of social networks
We present a detailed study of network evolution by analyzing four large online social networks with full temporal information about node and edge arrivals. For the first time at ...
Jure Leskovec, Lars Backstrom, Ravi Kumar, Andrew ...
SDM
2003
SIAM
123views Data Mining» more  SDM 2003»
15 years 1 months ago
Fast Online SVD Revisions for Lightweight Recommender Systems
The singular value decomposition (SVD) is fundamental to many data modeling/mining algorithms, but SVD algorithms typically have quadratic complexity and require random access to ...
Matthew Brand