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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...
CIVR
2008
Springer
166views Image Analysis» more  CIVR 2008»
13 years 6 months ago
Non-negative matrix factorisation for object class discovery and image auto-annotation
In information retrieval, sub-space techniques are usually used to reveal the latent semantic structure of a data-set by projecting it to a low dimensional space. Non-negative mat...
Jiayu Tang, Paul H. Lewis
CIKM
2008
Springer
13 years 6 months ago
Combining concept hierarchies and statistical topic models
Statistical topic models provide a general data-driven framework for automated discovery of high-level knowledge from large collections of text documents. While topic models can p...
Chaitanya Chemudugunta, Padhraic Smyth, Mark Steyv...
WWW
2008
ACM
14 years 5 months ago
Detecting image spam using visual features and near duplicate detection
Email spam is a much studied topic, but even though current email spam detecting software has been gaining a competitive edge against text based email spam, new advances in spam g...
Bhaskar Mehta, Saurabh Nangia, Manish Gupta 0002, ...
IJCV
2008
151views more  IJCV 2008»
13 years 4 months ago
Describing Visual Scenes Using Transformed Objects and Parts
We develop hierarchical, probabilistic models for objects, the parts composing them, and the visual scenes surrounding them. Our approach couples topic models originally developed...
Erik B. Sudderth, Antonio Torralba, William T. Fre...