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ICPP
2008
IEEE
13 years 11 months ago
Parallelization and Characterization of Probabilistic Latent Semantic Analysis
Probabilistic Latent Semantic Analysis (PLSA) is one of the most popular statistical techniques for the analysis of two-model and co-occurrence data. It has applications in inform...
Chuntao Hong, Wenguang Chen, Weimin Zheng, Jiulong...
CIARP
2009
Springer
13 years 11 months ago
Randomized Probabilistic Latent Semantic Analysis for Scene Recognition
The concept of probabilistic Latent Semantic Analysis (pLSA) has gained much interest as a tool for feature transformation in image categorization and scene recognition scenarios. ...
Erik Rodner, Joachim Denzler
KDD
2009
ACM
298views Data Mining» more  KDD 2009»
13 years 11 months ago
Mind the gaps: weighting the unknown in large-scale one-class collaborative filtering
One-Class Collaborative Filtering (OCCF) is a task that naturally emerges in recommender system settings. Typical characteristics include: Only positive examples can be observed, ...
Rong Pan, Martin Scholz