Automatically Categorizing Written Texts by Author Gender.
The problem of automatically determining the gender of a document's author would appear to be a more subtle problem than those of categorization by topic or authorship attribution. Nevertheless, it is shown that automated text categorization techniques can exploit combinations of simple lexical and...
| Publicado en: | Literary & Linguistic Computing Vol. 17; no. 4; pp. 401 - 412 |
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| Autores principales: | , , |
| Formato: | Artículo |
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Oxford University Press / USA
Nov2002
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=10037175&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 10037175 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 02681145 BJ1 jtl: Literary & Linguistic Computing issn: 02681145 maglogo: N pubinfo: dt: Nov2002 vid: 17 iid: 4 pid: 622 pub: Oxford University Press / USA artinfo: ui: 10037175 10.1093/llc/17.4.401 ppf: 401 ppct: 11 formats: fmt: @attributes: type: P size: 124KB tig: atl: Automatically Categorizing Written Texts by Author Gender. aug: au: Koppel, Moshe Argamon, Shlomo Shimoni, Anat Rachel su: Text processing (Computer science) Electronic data processing sug: subj: Text processing (Computer science) Electronic data processing ab: The problem of automatically determining the gender of a document's author would appear to be a more subtle problem than those of categorization by topic or authorship attribution. Nevertheless, it is shown that automated text categorization techniques can exploit combinations of simple lexical and syntactic features to infer the gender of the author of an unseen formal written document with approximately 80 per cent accuracy. The same techniques can be used to determine if a document is fiction or non-fiction with approximately 98 per cent accuracy. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: © 2019 EADH: The European Association for Digital Humanities. item: Literary & Linguistic Computing holder: Oxford University Press / USA dt: @attributes: year: 2002 holdings: @attributes: islocal: N |
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