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EACL
2006
ACL Anthology
13 years 6 months ago
Improving Probabilistic Latent Semantic Analysis with Principal Component Analysis
Probabilistic Latent Semantic Analysis (PLSA) models have been shown to provide a better model for capturing polysemy and synonymy than Latent Semantic Analysis (LSA). However, th...
Ayman Farahat, Francine Chen
IDA
2005
Springer
13 years 10 months ago
Probabilistic Latent Clustering of Device Usage
Abstract. We investigate an application of Probabilistic Latent Semantics to the problem of device usage analysis in an infrastructure in which multiple users have access to a shar...
Jean-Marc Andreoli, Guillaume Bouchard
CRV
2008
IEEE
295views Robotics» more  CRV 2008»
13 years 11 months ago
3D Human Motion Tracking Using Dynamic Probabilistic Latent Semantic Analysis
We propose a generative statistical approach to human motion modeling and tracking that utilizes probabilistic latent semantic (PLSA) models to describe the mapping of image featu...
Kooksang Moon, Vladimir Pavlovic
MM
2005
ACM
209views Multimedia» more  MM 2005»
13 years 10 months ago
Learning an image-word embedding for image auto-annotation on the nonlinear latent space
Latent Semantic Analysis (LSA) has shown encouraging performance for the problem of unsupervised image automatic annotation. LSA conducts annotation by keywords propagation on a l...
Wei Liu, Xiaoou Tang
DAGM
2008
Springer
13 years 6 months ago
Comparing Local Feature Descriptors in pLSA-Based Image Models
Abstract. Probabilistic models with hidden variables such as probabilistic Latent Semantic Analysis (pLSA) and Latent Dirichlet Allocation (LDA) have recently become popular for so...
Eva Hörster, Thomas Greif, Rainer Lienhart, M...