Journal ArticleDOI
Latent semantic analysis.
TLDR
This article reviews latent semantic analysis (LSA), a theory of meaning as well as a method for extracting that meaning from passages of text, based on statistical computations over a collection of documents.Abstract:
This article reviews latent semantic analysis (LSA), a theory of meaning as well as a method for extracting that meaning from passages of text, based on statistical computations over a collection of documents. LSA as a theory of meaning defines a latent semantic space where documents and individual words are represented as vectors. LSA as a computational technique uses linear algebra to extract dimensions that represent that space. This representation enables the computation of similarity among terms and documents, categorization of terms and documents, and summarization of large collections of documents using automated procedures that mimic the way humans perform similar cognitive tasks. We present some technical details, various illustrative examples, and discuss a number of applications from linguistics, psychology, cognitive science, education, information science, and analysis of textual data in general. WIREs Cogn Sci 2013, 4:683-692. doi: 10.1002/wcs.1254 CONFLICT OF INTEREST: The author has declared no conflicts of interest for this article. For further resources related to this article, please visit the WIREs website.read more
Citations
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Gilles Fauconnier & Mark Turner, " The way we think: conceptual blending and the mind's hidden complexities"
Paul Sambre,Geert Brône +1 more
Journal ArticleDOI
Latent Semantic Analysis: five methodological recommendations
TL;DR: Five methodological issues that need to be addressed by the researcher who will embark on Latent Semantic Analysis are reviewed, involving the analysis of abstracts for papers published in the European Journal of Information Systems.
Journal ArticleDOI
Overview and comparative study of dimensionality reduction techniques for high dimensional data
TL;DR: This paper presents the state-of-the art dimensionality reduction techniques and their suitability for different types of data and application areas and the issues of dimensionality Reduction techniques that can affect the accuracy and relevance of results.
Journal ArticleDOI
Toward a Consensus Description of Vocal Effort, Vocal Load, Vocal Loading, and Vocal Fatigue
Eric Hunter,Lady Catherine Cantor-Cutiva,Lady Catherine Cantor-Cutiva,Eva van Leer,Miriam van Mersbergen,Chaya Devie Nanjundeswaran,Pasquale Bottalico,Mary J. Sandage,Susanna Whitling +8 more
TL;DR: The results indicate that these terms appear to be often interchanged with blurred distinctions, and the focus group proposes the use of two new terms, " vocal demand" and "vocal demand response," in place of the terms "v vocal load" and 'vocal loading.
Journal ArticleDOI
Voice of airline passenger: A text mining approach to understand customer satisfaction
TL;DR: In this article, Latent Semantic Analysis (LSA) is applied to analyse online user-generated airline reviews and find that there are fundamental differences in the drivers of passenger satisfaction depending on the class of air travel purchased, and whether the airline is a low cost or a full service carrier.
References
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Book
Communities of Practice: Learning, Meaning, and Identity
TL;DR: Identity in practice, modes of belonging, participation and non-participation, and learning communities: a guide to understanding identity in practice.
Journal ArticleDOI
Indexing by Latent Semantic Analysis
TL;DR: A new method for automatic indexing and retrieval to take advantage of implicit higher-order structure in the association of terms with documents (“semantic structure”) in order to improve the detection of relevant documents on the basis of terms found in queries.
Book
Introduction to Information Retrieval
TL;DR: In this article, the authors present an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections.
Journal ArticleDOI
A vector space model for automatic indexing
Gerard Salton,A. Wong,C. S. Yang +2 more
TL;DR: An approach based on space density computations is used to choose an optimum indexing vocabulary for a collection of documents, demonstating the usefulness of the model.
Journal ArticleDOI
A Solution to Plato's Problem: The Latent Semantic Analysis Theory of Acquisition, Induction, and Representation of Knowledge.
TL;DR: A new general theory of acquired similarity and knowledge representation, latent semantic analysis (LSA), is presented and used to successfully simulate such learning and several other psycholinguistic phenomena.