DocumentCode
2728938
Title
Recognising Professional-Activity Groups and Web Usage Mining for Web Browsing Personalisation
Author
Mrabet, Yassine ; Khelif, Khaled ; Dieng-Kuntz, Rose
Author_Institution
INRIA Sophia Antipolis, Nice
fYear
2007
fDate
2-5 Nov. 2007
Firstpage
719
Lastpage
722
Abstract
Web usage mining can play an important role in supporting the navigation on the future Web. In fact detection of common or professional profiles allows browsers and web sites to personalise the user session and to recommend specific resources to the interested people. Semantic web approach seems interesting for this task. We propose in this paper a generic approach for profile detection relying on semantic web technologies. It takes advantages from ontologies, semantic annotations on web resources and inference engines.
Keywords
data mining; online front-ends; search engines; semantic Web; Web browsing personalisation; Web resources; Web sites; Web usage mining; inference engines; ontologies; professional-activity groups; profile detection; semantic Web; semantic annotations; Buildings; Electronic equipment testing; Engines; Intelligent networks; Kernel; Keyword search; Navigation; Ontologies; Semantic Web; Software libraries; annotations; ontologies; profile learning; semantic web browsing.;
fLanguage
English
Publisher
ieee
Conference_Titel
Web Intelligence, IEEE/WIC/ACM International Conference on
Conference_Location
Fremont, CA
Print_ISBN
978-0-7695-3026-0
Type
conf
DOI
10.1109/WI.2007.46
Filename
4427179
Link To Document