Categorisation Techniques in Computer-Assisted Reading and Analysis of Texts (CARAT) in the Humanities.
There are two important strategies in computer-assisted reading and analysis of text (CARAT). The first relates to the classification process, and the second pertains to the categorisation process. These two often-interrelated operations have been regularly recognised as essential components of text...
| Published in: | Computers & the Humanities Vol. 37; no. 1; pp. 111 - 119 |
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| Main Authors: | , |
| Format: | Article |
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Springer Nature
Feb2003
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| Subjects: | |
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=16898861&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 16898861 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00104817 CHM jtl: Computers & the Humanities issn: 00104817 maglogo: N pubinfo: dt: Feb2003 vid: 37 iid: 1 pid: 237 pub: Springer Nature artinfo: ui: 16898861 10.1023/A:1021855607270 ppf: 111 ppct: 8 formats: fmt: @attributes: type: P size: 63KB tig: atl: Categorisation Techniques in Computer-Assisted Reading and Analysis of Texts (CARAT) in the Humanities. aug: au: Pasquale, Jean-Frédéric de Meunier, Jean-Guy affil: Laboratoire d'Analyse Cognitive de l'Information (LANCI), Université du Québec à Montréal (UQAM), C.P. 8888, Succ. Centre-Ville, Montréal (Québec) Canada H3C 3P8 E-mail: Laboratoire d'Analyse Cognitive de l'Information (LANCI), Université du Québec à Montréal (UQAM), C.P. 8888, Succ. Centre-Ville, Montréal (Québec) Canada H3C 3P8 Fax: (514) 987.6721 E-mail: su: Computer assisted instruction Humanities Humanism Classical education Philosophy Statistics sug: subj: Computer assisted instruction Humanities Humanism Classical education Philosophy Statistics keyword: automatic text categorization text analysis text classification ab: There are two important strategies in computer-assisted reading and analysis of text (CARAT). The first relates to the classification process, and the second pertains to the categorisation process. These two often-interrelated operations have been regularly recognised as essential components of text analysis. However, the two operations are highly time-consuming. A possible solution to this problem calls upon more inductive or bottom-up strategies that are numerical and statistical in nature. In our own research, we have been exploring a few of these techniques and their combination. We now know, through our own past research and others' work, that the classification methods allow a good empirical thematic exploration of a corpus. More specifically, in this paper we shall concentrate on the problem of assisting the automatic categorisation of small segments of a philosophical text into a set of thematic categories. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Computers & the Humanities is a copyright of Springer, 2003. All Rights Reserved. item: Computers & the Humanities holder: Springer Nature dt: @attributes: year: 2003 holdings: @attributes: islocal: N |
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