Comparing classification methods for link context based focused crawlers

Basit Öğe Kaydı
dc.contributor.authorCaliskan, Kamil
dc.contributor.authorOzcan, Rifat
dc.date.accessioned2025-10-24T18:06:41Z
dc.date.available2025-10-24T18:06:41Z
dc.date.issued2013
dc.departmentMalatya Turgut Özal Üniversitesi
dc.description2013 10th International Conference on Electronics, Computer and Computation, ICECCO 2013 -- -- Ankara -- 102696
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 (naïve bayes, decision tree, and support vector machines) for the task of link context based focused crawling. © 2013 IEEE. © 2014 Elsevier B.V., All rights reserved.
dc.identifier.doi10.1109/ICECCO.2013.6718249
dc.identifier.endpage146
dc.identifier.isbn9781479933433
dc.identifier.scopus2-s2.0-84894219579
dc.identifier.scopusqualityN/A
dc.identifier.startpage143
dc.identifier.urihttps://doi.rog/10.1109/ICECCO.2013.6718249
dc.identifier.urihttps://hdl.handle.net/20.500.12899/3135
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherIEEE Computer Society help@computer.org
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzScopus_20251023
dc.subjectclassification
dc.subjectfocused crawling
dc.subjectlink context
dc.titleComparing classification methods for link context based focused crawlers
dc.typeConference Object

Dosyalar

Koleksiyon

Scopus İndeksli Yayınlar Koleksiyonu