How the ExpLSA approach impacts the document classification tasks

Author

Béchet, Nicolas ; Roche, Mathieu ; Chauché, Jacques

Author_Institution

CNRS, Univ. Montpellier 2, Montpellier

fYear

2008

fDate

13-16 Nov. 2008

Firstpage

241

Lastpage

246

Abstract

Latent semantic analysis (LSA) is a statistical method which can be used to classify texts. This paper proposes a sentence expansion method (ExpLSA) to improve document classification tasks. We propose to study the impact of ExpLSA on the size and on the type of corpora.

Keywords

document handling; statistical analysis; text analysis; document classification tasks; latent semantic analysis; sentence expansion method; statistical method; Classification algorithms; Heart; Humans; Matrix decomposition; Protocols; Statistical analysis; Support vector machine classification; Support vector machines; Vocabulary; Writing;

fLanguage

English

Publisher

ieee

Conference_Titel

Digital Information Management, 2008. ICDIM 2008. Third International Conference on

Conference_Location

London

Print_ISBN

978-1-4244-2916-5

Electronic_ISBN

978-1-4244-2917-2

Type

conf

DOI

10.1109/ICDIM.2008.4746814

Filename

4746814

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2338461