An Enhanced Similarity Measure for Utilizing Site Structure in Web Personalization Systems
S. Sahebi, F. Oroumchian, und R. Khosravi. WI-IAT '08: Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, Seite 82--85. Washington, DC, USA, IEEE Computer Society, (2008)
DOI: 10.1109/wiiat.2008.270
Zusammenfassung
The need for recommendation systems to ease user navigations has become evident by growth of information on the Web. There exist many approaches of learning for Web usage-based recommendation systems. In hybrid recommendation systems, other knowledge resources, like content, semantics, and hyperlink structure of the Web site, have been utilized to enhance usage-based personalization systems. In this study, we introduce a new structure-based similarity measure for user sessions. We also apply two clustering algorithms on this similarity measure to compare it to cosine and another structure-based similarity measures. Our experiments exhibit that adding structure information, leveraging the proposed similarity measure, enhances the quality of recommendations in both methods.
%0 Conference Paper
%1 citeulike:5343440
%A Sahebi, Shaghayegh
%A Oroumchian, Farhad
%A Khosravi, Ramtin
%B WI-IAT '08: Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology
%C Washington, DC, USA
%D 2008
%I IEEE Computer Society
%K clustering ontology personalization recommender
%P 82--85
%R 10.1109/wiiat.2008.270
%T An Enhanced Similarity Measure for Utilizing Site Structure in Web Personalization Systems
%U http://dx.doi.org/10.1109/wiiat.2008.270
%X The need for recommendation systems to ease user navigations has become evident by growth of information on the Web. There exist many approaches of learning for Web usage-based recommendation systems. In hybrid recommendation systems, other knowledge resources, like content, semantics, and hyperlink structure of the Web site, have been utilized to enhance usage-based personalization systems. In this study, we introduce a new structure-based similarity measure for user sessions. We also apply two clustering algorithms on this similarity measure to compare it to cosine and another structure-based similarity measures. Our experiments exhibit that adding structure information, leveraging the proposed similarity measure, enhances the quality of recommendations in both methods.
%@ 978-0-7695-3496-1
@inproceedings{citeulike:5343440,
abstract = {{The need for recommendation systems to ease user navigations has become evident by growth of information on the Web. There exist many approaches of learning for Web usage-based recommendation systems. In hybrid recommendation systems, other knowledge resources, like content, semantics, and hyperlink structure of the Web site, have been utilized to enhance usage-based personalization systems. In this study, we introduce a new structure-based similarity measure for user sessions. We also apply two clustering algorithms on this similarity measure to compare it to cosine and another structure-based similarity measures. Our experiments exhibit that adding structure information, leveraging the proposed similarity measure, enhances the quality of recommendations in both methods.}},
added-at = {2018-03-19T12:24:51.000+0100},
address = {Washington, DC, USA},
author = {Sahebi, Shaghayegh and Oroumchian, Farhad and Khosravi, Ramtin},
biburl = {https://www.bibsonomy.org/bibtex/26a79c407d2f1db88f8027f654c080e30/aho},
booktitle = {WI-IAT '08: Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology},
citeulike-article-id = {5343440},
citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1487258},
citeulike-linkout-1 = {http://dx.doi.org/10.1109/wiiat.2008.270},
doi = {10.1109/wiiat.2008.270},
interhash = {cf4e7749566ce38dd3375d4146cbb803},
intrahash = {6a79c407d2f1db88f8027f654c080e30},
isbn = {978-0-7695-3496-1},
keywords = {clustering ontology personalization recommender},
pages = {82--85},
posted-at = {2009-08-03 22:06:53},
priority = {0},
publisher = {IEEE Computer Society},
timestamp = {2018-03-19T12:24:51.000+0100},
title = {{An Enhanced Similarity Measure for Utilizing Site Structure in Web Personalization Systems}},
url = {http://dx.doi.org/10.1109/wiiat.2008.270},
year = 2008
}