A Comparable Study Employing WEKA Clustering/Classification Algorithms for Web Page Classification

Author

Charalampopoulos, Ioannis ; Anagnostopoulos, Ioannis

Author_Institution

Dept. of Inf. & Commun. Syst. Eng., Univ. of the Aegean, Karlovassi, Greece

fYear

2011

fDate

Sept. 30 2011-Oct. 2 2011

Firstpage

235

Lastpage

239

Abstract

Documents and web pages share many similarities. Thus classification methods used in documents can be applied to advanced web content, with or even without modifications. Algorithms for document and web classification are presented as an introduction. One out of many tools that can be used in method evaluation, application and modification is WEKA (Waikato Environment for Knowledge Analysis). Testing results and conclusions strengthen the principles and bases of classification, while demonstrating the need for a new interlayer in the evaluation of classification methods.

Keywords

Internet; document handling; pattern classification; pattern clustering; WEKA classification algorithm; WEKA clustering algorithm; Waikato environment for knowledge analysis; Web page classification; document classification method; Algorithm design and analysis; Classification algorithms; Clustering algorithms; Indexing; Internet; Machine learning; Web pages; Classification; Clustering; WEKA;

fLanguage

English

Publisher

ieee

Conference_Titel

Informatics (PCI), 2011 15th Panhellenic Conference on

Conference_Location

Kastonia

Print_ISBN

978-1-61284-962-1

Type

conf

DOI

10.1109/PCI.2011.52

Filename

6065094