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Towards completely automatized HTML form discovery on the web

The forms discovered by our proposal can be directly used as training data by some form classifiers. Our experimental validation used thousands of real Web forms, divided into six domains, including a representative subset of the publicly available DeepPeep form base (DEEPPEEP, 2010; DEEPPEEP REPOSITORY, 2011). Our results show that it is feasible to mitigate the demanding manual work required by two cutting-edge form classifiers (i.e., GFC and DSFC (BARBOSA; FREIRE, 2007a)), at the cost of a relatively small loss in effectiveness.

Identiferoai:union.ndltd.org:IBICT/oai:www.lume.ufrgs.br:10183/70194
Date January 2013
CreatorsMoraes, Maurício Coutinho
ContributorsHeuser, Carlos Alberto, Moreira, Viviane Pereira
Source SetsIBICT Brazilian ETDs
LanguageEnglish
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/publishedVersion, info:eu-repo/semantics/doctoralThesis
Formatapplication/pdf
Sourcereponame:Biblioteca Digital de Teses e Dissertações da UFRGS, instname:Universidade Federal do Rio Grande do Sul, instacron:UFRGS
Rightsinfo:eu-repo/semantics/openAccess

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