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Latent semantic analysis

Known as: Infoscale, LSA, Latent semantic indexing 
Latent semantic analysis (LSA) is a technique in natural language processing, in particular distributional semantics, of analyzing relationships… 
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Papers overview

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2008
2008
In this paper we present results from using Random indexing for Latent Semantic Analysis to handle Singular Value Decomposition… 
2006
2006
Latent semantic analysis (LSA) is an algorithm applied to approximate the meaning of texts, thereby exposing semantic structure… 
2006
2006
Latent semantic analysis (LSA) approximates human understanding of relations between word and passage meanings in a wide variety… 
2005
2005
In the past decade, Latent Semantic Analysis (LSA) was used in many NLP approaches with sometimes remarkable success. However… 
2003
2003
Talking face detection is important for videoconferencing. However, the detection of the talking face is difficult because of the… 
Highly Cited
2002
Highly Cited
2002
A map of text documents arranged using the Self-Organizing Map (SOM) algorithm (1) is organized in a meaningful manner so that… 
2001
2001
We present a Bayesian mixture model for probabilistic latent semantic analysis of documents with images and text. The Bayesian… 
Review
2000
Review
2000
Latent Semantic Analysis of Text Information The paper presents an overview of the usage of LSA for analysis of textual data. The… 
1998
1998
A theoretical foundation for latent semantic indexing (LSI) is proposed by adapting a model first used in array signal processing…