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» Mining Noisy Data Streams via a Discriminative Model
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ICDM
2010
IEEE
186views Data Mining» more  ICDM 2010»
13 years 3 months ago
MoodCast: Emotion Prediction via Dynamic Continuous Factor Graph Model
Human emotion is one important underlying force affecting and affected by the dynamics of social networks. An interesting question is "can we predict a person's mood base...
Yuan Zhang, Jie Tang, Jimeng Sun, Yiran Chen, Jing...
KDD
2009
ACM
229views Data Mining» more  KDD 2009»
14 years 6 months ago
Relational learning via latent social dimensions
Social media such as blogs, Facebook, Flickr, etc., presents data in a network format rather than classical IID distribution. To address the interdependency among data instances, ...
Lei Tang, Huan Liu
SDM
2012
SIAM
252views Data Mining» more  SDM 2012»
11 years 8 months ago
Learning from Heterogeneous Sources via Gradient Boosting Consensus
Multiple data sources containing different types of features may be available for a given task. For instance, users’ profiles can be used to build recommendation systems. In a...
Xiaoxiao Shi, Jean-François Paiement, David...
ICDM
2010
IEEE
200views Data Mining» more  ICDM 2010»
13 years 3 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
2012
ACM
244views Data Mining» more  KDD 2012»
11 years 8 months ago
Open domain event extraction from twitter
Tweets are the most up-to-date and inclusive stream of information and commentary on current events, but they are also fragmented and noisy, motivating the need for systems that c...
Alan Ritter, Mausam, Oren Etzioni, Sam Clark