COMPARING CLASSIFICATION METHODS FOR LINK CONTEXT BASED FOCUSED CRAWLERS

Basit Öğe Kaydı
dc.contributor.authorCaliskan, Kamil
dc.contributor.authorOzcan, Rifat
dc.date.accessioned2025-10-24T18:10:21Z
dc.date.available2025-10-24T18:10:21Z
dc.date.issued2013
dc.departmentMalatya Turgut Özal Üniversitesi
dc.description10th International Conference on Electronics, Computer and Computation (ICECCO) -- NOV 07-09, 2013 -- Turgut Ozal Univ, Ankara, TURKEY
dc.description.abstractFocused crawlers aim to fetch pages only related to a specific subject area from millions of web pages on the Internet. The essential task in a focused crawler is to predict whether a page is related to the target subject area or not without actually fetching the page content itself. Link context based focused crawlers focus on the surrounding text around each link to classify the page pointed by the URL. In this paper, we aim to compare three different classification methods (naive bayes, decision tree, and support vector machines) for the task of link context based focused crawling.
dc.description.sponsorshipInst Elect & Elect Engineers
dc.identifier.endpage146
dc.identifier.isbn978-1-4799-3343-3
dc.identifier.issn#DEĞER!
dc.identifier.startpage143
dc.identifier.urihttps://hdl.handle.net/20.500.12899/4121
dc.identifier.wosWOS:000336616500037
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.language.isoen
dc.publisherIeee
dc.relation.ispartof2013 International Conference On Electronics, Computer And Computation (Icecco)
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20251023
dc.subjectfocused crawling; classification; link context
dc.titleCOMPARING CLASSIFICATION METHODS FOR LINK CONTEXT BASED FOCUSED CRAWLERS
dc.typeConference Object

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu