Latent semantic analysis

Known as: Infoscale, Latent Semantic Indexing 
Latent semantic analysis (LSA) is a technique in natural language processing, in particular distributional semantics, of analyzing relationships… (More)
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Topic mentions per year

Topic mentions per year

1984-2018
010020019842018

Papers overview

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Highly Cited
2003
Highly Cited
2003
Collaborative filtering aims at learning predictive models of user preferences, interests or behavior from community data, i.e. a… (More)
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Highly Cited
2001
Highly Cited
2001
This paper presents a novel statistical method for factor analysis of binary and count data which is closely related to a… (More)
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Highly Cited
2001
Highly Cited
2001
In this paper, we propose two generic text summarization methods that create text summaries by ranking and extracting sentences… (More)
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Highly Cited
1999
Highly Cited
1999
Probabilistic Latent Semantic Analysis is a novel statistical technique for the analysis of two{mode and co-occurrence data… (More)
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Highly Cited
1999
Highly Cited
1999
Probabilistic Latent Semantic Indexing is a novel approach to automated document indexing which is based on a statistical latent… (More)
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1999
1999
Latent Semantic Analysis (LSA) is a technique for comparing texts using a vector-based representation that is learned from a… (More)
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Review
1998
Review
1998
Latent Semantic Analysis (LSA) is a theory and method for extracting and representing the contextual-usage meaning of words by… (More)
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Highly Cited
1997
Highly Cited
1997
computational method for its solution. A Psychological Description of LSA as a Theory of Learning, Memory, and Knowledge We give… (More)
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Highly Cited
1990
Highly Cited
1990
A new method for automatic indexing and retrieval is described. The approach is to take advantage of implicit higher-order… (More)
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Highly Cited
1988
Highly Cited
1988
This paper describes a new approach for dealing with the vocabulary problem in human-computer interaction. Most approaches to… (More)
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