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KDD
2004
ACM
210views Data Mining» more  KDD 2004»
14 years 9 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...
MLDM
1999
Springer
14 years 1 months ago
Non-hierarchical Clustering with Rival Penalized Competitive Learning for Information Retrieval
In large content-based image database applications, e cient information retrieval depends heavily on good indexing structures of the extracted features. While indexing techniques f...
Irwin King, Tak-Kan Lau
WIDM
2004
ACM
14 years 2 months ago
Stylistic and lexical co-training for web block classification
Many applications which use web data extract information from a limited number of regions on a web page. As such, web page division into blocks and the subsequent block classifica...
Chee How Lee, Min-Yen Kan, Sandra Lai
NIPS
2008
13 years 10 months ago
DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification
Probabilistic topic models have become popular as methods for dimensionality reduction in collections of text documents or images. These models are usually treated as generative m...
Simon Lacoste-Julien, Fei Sha, Michael I. Jordan
RIAO
1997
13 years 10 months ago
Coupling information retrieval and information extraction: A new text technology for gathering information from the web
The techniques of information retrieval and information extraction are complementary, but to date there has been little concrete work aimed at integrating the two. We describe how...
Robert J. Gaizauskas, Alexander M. Robertson