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ICPR
2006
IEEE
14 years 5 months ago
Latent Layout Analysis for Discovering Objects in Images
Latent Layout Analysis (LLA) is a novel unsupervised learning technique to discover objects in unseen images using a set of un-annotated training images. LLA defines a generative ...
David Liu, Datong Chen, Tsuhan Chen
LREC
2008
153views Education» more  LREC 2008»
13 years 6 months ago
Using Random Indexing to improve Singular Value Decomposition for Latent Semantic Analysis
We present results from using Random Indexing for Latent Semantic Analysis to handle Singular Value Decomposition tractability issues. We compare Latent Semantic Analysis, Random ...
Linus Sellberg, Arne Jönsson
CORR
2010
Springer
139views Education» more  CORR 2010»
13 years 4 months ago
The semantic mapping of words and co-words in contexts
Meaning can be generated when information is related at a systemic level. Such a system can be an observer, but also a discourse, for example, operationalized as a set of document...
Loet Leydesdorff, Kasper Welbers
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
ICPR
2002
IEEE
14 years 5 months ago
Building a Latent Semantic Index of an Image Database from Patterns of Relevance Feedback
This paper proposes a novel view of the information generated by relevance feedback. Latent semantic analysis is adapted to this view to extract useful inter-query information. Th...
Douglas R. Heisterkamp