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KDD
2007
ACM
124views Data Mining» more  KDD 2007»
16 years 22 days ago
Hierarchical mixture models: a probabilistic analysis
Mixture models form one of the most widely used classes of generative models for describing structured and clustered data. In this paper we develop a new approach for the analysis...
Mark Sandler
KDD
2004
ACM
209views Data Mining» more  KDD 2004»
16 years 7 months ago
Tracking dynamics of topic trends using a finite mixture model
In a wide range of business areas dealing with text data streams, including CRM, knowledge management, and Web monitoring services, it is an important issue to discover topic tren...
Satoshi Morinaga, Kenji Yamanishi
KDD
2004
ACM
210views Data Mining» more  KDD 2004»
16 years 7 months ago
Probabilistic author-topic models for information discovery
We propose a new unsupervised learning technique for extracting information from large text collections. We model documents as if they were generated by a two-stage stochastic pro...
Mark Steyvers, Padhraic Smyth, Michal Rosen-Zvi, T...
JCDL
2009
ACM
139views Education» more  JCDL 2009»
16 years 1 months ago
Topic model methods for automatically identifying out-of-scope resources
Recent years have seen the rise of subject-themed digital libraries, such as the NSDL pathways and the Digital Library for Earth System Education (DLESE). These libraries often ne...
Steven Bethard, Soumya Ghosh, James H. Martin, Tam...
KDD
2009
ACM
191views Data Mining» more  KDD 2009»
16 years 7 months ago
Efficient methods for topic model inference on streaming document collections
Topic models provide a powerful tool for analyzing large text collections by representing high dimensional data in a low dimensional subspace. Fitting a topic model given a set of...
Limin Yao, David M. Mimno, Andrew McCallum