Web content extraction by using decision tree learning

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dc.authorscopusid54783608800
dc.authorscopusid55293388500
dc.authorscopusid16232085100
dc.contributor.authorUzun E.
dc.contributor.authorAgun H.V.
dc.contributor.authorYerlikaya T.
dc.date.accessioned2024-06-12T10:25:24Z
dc.date.available2024-06-12T10:25:24Z
dc.date.issued2012
dc.description2012 20th Signal Processing and Communications Applications Conference, SIU 2012 -- 18 April 2012 through 20 April 2012 -- Fethiye, Mugla -- 90786en_US
dc.description.abstractVia information extraction techniques, web pages are able to generate datasets for various studies such as natural language processing, and data mining. However, nowadays the uninformative sections like advertisement, menus, and links are in increase. The cleaning of web pages from uninformative sections, and extraction of informative content has become an important issue. In this study, we present an decision tree learning approach over DOM based features which aims to clean the uninformative sections and extract informative content in three classes: title, main content, and additional information. Through this approach, differently from previous studies, the learning model for the extraction of the main content constructed on DIV and TD tags. The proposed method achieved 95.58% accuracy in cleaning uninformative sections and extraction of the informative content. Especially for the extraction of the main block, 0.96 f-measure is obtained. © 2012 IEEE.en_US
dc.identifier.doi10.1109/SIU.2012.6204476
dc.identifier.isbn9.78147E+12
dc.identifier.scopus2-s2.0-84863462457en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://doi.org/10.1109/SIU.2012.6204476
dc.identifier.urihttps://hdl.handle.net/20.500.14551/16328
dc.indekslendigikaynakScopusen_US
dc.language.isotren_US
dc.relation.ispartof2012 20th Signal Processing and Communications Applications Conference, SIU 2012, Proceedingsen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectData Sets; Decision Tree Learning; F-Measure; Information Extraction Techniques; Learning Models; Natural Language Processing; Web Content; Computational Linguistics; Data Mining; Decision Trees; Natural Language Processing Systems; Signal Processing; Websites; Information Retrieval Systemsen_US
dc.titleWeb content extraction by using decision tree learningen_US
dc.title.alternativeKarar a?aci ö?renmesik? kullanarak web i?çeri?k çikarimien_US
dc.typeConference Objecten_US

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