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» Probabilistic author-topic models for information discovery
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KDD
2004
ACM
210views Data Mining» more  KDD 2004»
14 years 5 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...
FLAIRS
2009
13 years 2 months ago
Constraint-based Approach to Discovery of Inter Module Dependencies in Modular Bayesian Networks
This paper introduces an information theoretic approach to verification of modular causal probabilistic models. We assume systems which are gradually extended by adding new functi...
Patrick de Oude, Gregor Pavlin
PERCOM
2011
ACM
12 years 8 months ago
P3-coupon: A probabilistic system for Prompt and Privacy-preserving electronic coupon distribution
—In this paper, we propose P3 -coupon, a Prompt and Privacy-preserving electronic coupon distribution system based on a Probabilistic one-ownership forwarding algorithm. In this ...
Boying Zhang, Jin Teng, Xiaole Bai, Zhimin Yang, D...
ICWSM
2009
13 years 2 months ago
A Categorical Model for Discovering Latent Structure in Social Annotations
The advent of social tagging systems has enabled a new community-based view of the Web in which objects like images, videos, and Web pages are annotated by thousands of users. Und...
Said Kashoob, James Caverlee, Ying Ding
ICDM
2007
IEEE
133views Data Mining» more  ICDM 2007»
13 years 11 months ago
Topical N-Grams: Phrase and Topic Discovery, with an Application to Information Retrieval
Most topic models, such as latent Dirichlet allocation, rely on the bag-of-words assumption. However, word order and phrases are often critical to capturing the meaning of text in...
Xuerui Wang, Andrew McCallum, Xing Wei