Literature DB >> 29024568

Word maturity indices with latent semantic analysis: why, when, and where is Procrustes rotation applied?

Guillermo Jorge-Botana1, Ricardo Olmos2, José M Luzón1.   

Abstract

The aim of this paper is to describe and explain one useful computational methodology to model the semantic development of word representation: Word maturity. In particular, the methodology is based on the longitudinal word monitoring created by Kirylev and Landauer using latent semantic analysis for the representation of lexical units. The paper is divided into two parts. First, the steps required to model the development of the meaning of words are explained in detail. We describe the technical and theoretical aspects of each step. Second, we provide a simple example of application of this methodology with some simple tools that can be used by applied researchers. This paper can serve as a user-friendly guide for researchers interested in modeling changes in the semantic representations of words. Some current aspects of the technique and future directions are also discussed. WIREs Cogn Sci 2018, 9:e1457. doi: 10.1002/wcs.1457 This article is categorized under: Computer Science > Natural Language Processing Linguistics > Language Acquisition Psychology > Development and Aging.
© 2017 Wiley Periodicals, Inc.

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Year:  2017        PMID: 29024568     DOI: 10.1002/wcs.1457

Source DB:  PubMed          Journal:  Wiley Interdiscip Rev Cogn Sci        ISSN: 1939-5078


  2 in total

1.  Prediction of psychosis across protocols and risk cohorts using automated language analysis.

Authors:  Cheryl M Corcoran; Facundo Carrillo; Diego Fernández-Slezak; Gillinder Bedi; Casimir Klim; Daniel C Javitt; Carrie E Bearden; Guillermo A Cecchi
Journal:  World Psychiatry       Date:  2018-02       Impact factor: 49.548

Review 2.  Bridging the theoretical gap between semantic representation models without the pressure of a ranking: some lessons learnt from LSA.

Authors:  Guillermo Jorge-Botana; Ricardo Olmos; José María Luzón
Journal:  Cogn Process       Date:  2019-09-25
  2 in total

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