1998 AnIntroductiontoLatentSemanticA

• (Landauer et al., 1998) ⇒ Thomas K. Landauer, Peter W Foltz, and Darrell Laham. (1998). “An Introduction to Latent Semantic Analysis.” In: Discourse processes, 25(2-3). 10.1080/01638539809545028 doi: 10.1080/01638539809545028

Subject Headings: Latent Semantic Analysis.

Cited By

• http://scholar.google.com/scholar?q=%221998%22+An+Introduction+to+Latent+Semantic+Analysis

2009

• (Recchia & Jones, 2009) ⇒ Gabriel Recchia, and Michael N. Jones. (2009). “More Data Trumps Smarter Algorithms: Comparing Pointwise Mutual Information with Latent Semantic Analysis.” In: Behavior research methods, 41(3).
  • QUOTE: As described by Landauer, Foltz, and Laham (1998), LSA operates by first constructing a term–document matrix in which the value of each cell (i,j) represents the number of occurrences of word i in document j.

Quotes

Abstract

Latent Semantic Analysis (LSA) is a theory and method for extracting and representing the contextual-usage meaning of words by statistical computations applied to a large corpus of text (Landauer & Dumais, 1997). The underlying idea is that the aggregate of all the word contexts in which a given word does and does not appear provides a set of mutual constraints that largely determines the similarity of meaning of words and sets of words to each other. The adequacy of LSA's reflection of human knowledge has been established in a variety of ways. For example, its scores overlap those of humans on standard vocabulary and subject matter tests; it mimics human word sorting and category judgments; it simulates word‐word and passage‐word lexical priming data; and, as reported in 3 following articles in this issue, it accurately estimates passage coherence, learnability of passages by individual students, and the quality and quantity of knowledge contained in an essay.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
1998 AnIntroductiontoLatentSemanticA	Thomas K. Landauer Peter W Foltz Darrell Laham			An Introduction to Latent Semantic Analysis				10.1080/01638539809545028		1998