COMPARING CLASSIFICATION METHODS FOR LINK CONTEXT BASED FOCUSED CRAWLERS
Küçük Resim Yok
Tarih
2013
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Ieee
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Focused 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.
Açıklama
10th International Conference on Electronics, Computer and Computation (ICECCO) -- NOV 07-09, 2013 -- Turgut Ozal Univ, Ankara, TURKEY
Anahtar Kelimeler
focused crawling; classification; link context
Kaynak
2013 International Conference On Electronics, Computer And Computation (Icecco)
WoS Q Değeri
N/A
