DocumentCode :
2918329
Title :
Comparative Classification of Semantic Web Challenges and Data Mining Techniques
Author :
Keyvanpour, MohammadReza ; Hassanzadeh, Hamed ; Khoshroo, Babak Mohammadizadeh
Author_Institution :
Dept. of Comput. Eng., Alzahra Univ., Tehran, Iran
fYear :
2009
fDate :
7-8 Nov. 2009
Firstpage :
200
Lastpage :
203
Abstract :
The semantic Web is an extension of the current Web in which information is given well-defined meaning, and with changing Web contents into machine understandable form, would promote quality and intelligence of the Web. Since the semantic Web mainly focuses on the data and information, different data mining techniques can address some significant challenges in the semantic Web. The goal of this article is to analyze and classify the application of divers data mining techniques in different challenges of the semantic Web. For this goal, the article attempts to categorize and analyze related researches for better understanding and to reach a framework that can map data mining techniques into the semantic Web challenges and requirements.
Keywords :
data mining; semantic Web; Web contents; comparative classification; data mining techniques; semantic Web challenges; Computer science; Data engineering; Data mining; Humans; Information systems; Machine intelligence; Ontologies; Search engines; Semantic Web; Web sites; Data Mining; Ontology engineering; Semantic Web;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Web Information Systems and Mining, 2009. WISM 2009. International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-0-7695-3817-4
Type :
conf
DOI :
10.1109/WISM.2009.48
Filename :
5369485
Link To Document :
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