Title :
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
fDate :
Sept. 30 2011-Oct. 2 2011
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;
Conference_Titel :
Informatics (PCI), 2011 15th Panhellenic Conference on
Conference_Location :
Kastonia
Print_ISBN :
978-1-61284-962-1
DOI :
10.1109/PCI.2011.52
