Classification of a Large Web Page Collection Applying a GRNN Architecture

Anagnostopoulos, I; Anagnostopoulos, C; Vergados, D; Loumos, V; Kayafas, E

dc.contributor.author	Anagnostopoulos, I	en
dc.contributor.author	Anagnostopoulos, C	en
dc.contributor.author	Vergados, D	en
dc.contributor.author	Loumos, V	en
dc.contributor.author	Kayafas, E	en
dc.date.accessioned	2014-03-01T02:49:18Z
dc.date.available	2014-03-01T02:49:18Z
dc.date.issued	2003	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/34497
dc.subject	Information System	en
dc.subject	Search Engine	en
dc.subject	Web Pages	en
dc.subject	Neural Network	en
dc.title	Classification of a Large Web Page Collection Applying a GRNN Architecture	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1007/978-3-540-39737-3_5	en
heal.identifier.secondary	http://dx.doi.org/10.1007/978-3-540-39737-3_5	en
heal.publicationDate	2003	en
heal.abstract	This paper proposes an information system that classifies web pages according a taxonomy, which is mainly used from seven search engines/ directories. The proposed classifier is a four-layer Generalised Regression Neural Network (GRNN) that aims to perform the information segmentation according to web page features. Many types of web pages were used in order to evaluate the robustness of the	en
heal.journalName	International Symposium on Computer and Information Sciences	en
dc.identifier.doi	10.1007/978-3-540-39737-3_5	en