<p>The keyword “stroke” is used as an example here. (a) The result for “stroke” by LSA method. (b) The whole graph inferred by LSA method. </p
This paper introduces latent semantic analysis (LSA) as an automated, statistically reliable metric ...
This paper proposes and examines modifications for the method of Latent Semantic Analysis (LSA). Sev...
Latent Semantic Analysis (LSA) is a technique that analyzes relationships between documents and its ...
Probabilistic Latent Semantic Analysis is a novel statistical technique for the analysis of two{mode...
Pairwise similarity judgement correlations between humans and Latent Semantic Analysis (LSA) were ex...
In three studies we investigated whether LSA cosine values estimate human similarity ratings of word...
The purpose of this document is to explain why LSA works – specifically, why (and when) is it (mathe...
Latent Semantic Analysis (LSA) is a statisti-cal, corpus-based text comparison mechanism that was or...
In three studies we investigated whether LSA cosine values estimate human similarity ratings of wor...
not shown here. Latent Semantic Analysis (LSA) is a commonly-used method for automated processing, m...
[[abstract]]The purpose of this study is to apply latent semantic analysis (LSA) to analyze item sim...
Latent Semantic Analysis (LSA) is a matching technique capable of recognizing the semantic relations...
Discourse research has provided an increasingly pre-cise understanding of the factors that influence...
Latent Semantic Analysis (LSA) uses semantic correlations across a corpora to reduce problems with p...
Latent Semantic Analysis (LSA) is a vector space technique for representing word meaning. Traditiona...
This paper introduces latent semantic analysis (LSA) as an automated, statistically reliable metric ...
This paper proposes and examines modifications for the method of Latent Semantic Analysis (LSA). Sev...
Latent Semantic Analysis (LSA) is a technique that analyzes relationships between documents and its ...
Probabilistic Latent Semantic Analysis is a novel statistical technique for the analysis of two{mode...
Pairwise similarity judgement correlations between humans and Latent Semantic Analysis (LSA) were ex...
In three studies we investigated whether LSA cosine values estimate human similarity ratings of word...
The purpose of this document is to explain why LSA works – specifically, why (and when) is it (mathe...
Latent Semantic Analysis (LSA) is a statisti-cal, corpus-based text comparison mechanism that was or...
In three studies we investigated whether LSA cosine values estimate human similarity ratings of wor...
not shown here. Latent Semantic Analysis (LSA) is a commonly-used method for automated processing, m...
[[abstract]]The purpose of this study is to apply latent semantic analysis (LSA) to analyze item sim...
Latent Semantic Analysis (LSA) is a matching technique capable of recognizing the semantic relations...
Discourse research has provided an increasingly pre-cise understanding of the factors that influence...
Latent Semantic Analysis (LSA) uses semantic correlations across a corpora to reduce problems with p...
Latent Semantic Analysis (LSA) is a vector space technique for representing word meaning. Traditiona...
This paper introduces latent semantic analysis (LSA) as an automated, statistically reliable metric ...
This paper proposes and examines modifications for the method of Latent Semantic Analysis (LSA). Sev...
Latent Semantic Analysis (LSA) is a technique that analyzes relationships between documents and its ...
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