Publication:
A tree learning approach to web document sectional hierarchy extraction

dc.contributor.authorPembe, F.Canan
dc.contributor.authorGöngör, Tunga
dc.date.accessioned2020-03-11T14:11:17Z
dc.date.available2020-03-11T14:11:17Z
dc.date.issued2010
dc.description.abstractThere is an increasing availability of documents in electronic form due to the widespread use of the Internet. Hypertext Markup Language (HTML) which is mostly concerned with the presentation of documents is still the most commonly used format on the Web, despite the appearance of semantically richer markup languages such as XML. Effective processing of Web documents has several uses such as the display of content on small-screen devices and summarization. In this paper, we investigate the problem of identifying the sectional hierarchy of a given HTML document together with the headings in the document. We propose and evaluate a learning approach suitable to tree representation based on Support Vector Machines.
dc.identifier.isbn978-989-674-021-4
dc.identifier.urihttps://hdl.handle.net/11413/6307
dc.identifier.wos000392361600072
dc.identifier.wos392361600072en
dc.language.isoen_UStr_TR
dc.relation.journalCAART 2010: PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON AGENTS AND ARTIFICIAL INTELLIGENCE, VOL 1: ARTIFICIAL INTELLIGENCEtr_TR
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.subjectMachine Learning
dc.subjectDocument Structure
dc.subjectWorld Wide Web
dc.subjectHypertext Markup Language
dc.subjectMakine Öğrenme
dc.subjectBelge Yapısı
dc.subjectDünya Çapında Ağ
dc.subjectKöprü Metni Biçimlendirme Dili
dc.titleA tree learning approach to web document sectional hierarchy extraction
dc.typeBook chapter
dspace.entity.typePublication
local.indexed.atwos
local.journal.endpage450tr_TR
local.journal.startpage447

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