Performance Based Novel Techniques for Semantic Web Mining
The explosive growth in the size and use of the World
Wide Web continuously creates new great challenges and
needs. The need for predicting the users preferences in
order to expedite and improve the browsing though a site
can be achieved through personalizing of the websites.
Most of the research efforts in web personalization
correspond to the evolution of extensive research in web
usage mining, i.e. the exploitation of the navigational
patterns of the web site visitors. When a personalization
system relies solely on usage-based results, however,
valuable information conceptually related to what is finally
recommended may be missed. Moreover, the structural
properties of the web site are often disregarded. In this
paper, we propose novel techniques that use the content
semantics and the structural properties of a web site in
order to improve the effectiveness of web personalization.
In the first part of our work we present standing for
Semantic Web Personalization, a personalization system
that integrates usage data with content semantics, expressed
in ontology terms, in order to compute semantically
enhanced navigational patterns and effectively generate
useful recommendations. To the best of our knowledge, our
proposed technique is the only semantic web
personalization system that may be used by non-semantic
web sites. In the second part of our work, we present a
novel approach for enhancing the quality of
recommendations based on the underlying structure of a
web site. We introduce UPR (Usage-based PageRank), a
PageRank-style algorithm that relies on the recorded usage
data and link analysis techniques. Overall, we demonstrate
that our proposed hybrid personalization framework results
in more objective and representative predictions than
existing techniques.
Keywords: Web personalization, Semantic web and Recommender systems
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ABOUT THE AUTHORS
Mahendra Thakur
Mr. Mahendra Thakur is a research scholar pursuing M.Tech in Computer Science & Engineering from Samrat Ashok Technological Institute Vidisha M.P India. He secured degree of B.E. in IT from Rajiv Gandhi Technical University, Bhopal (M.P.) India in 2007.
Geetika S. Pandey
Geetika S. Pandey presently working as Asst. Professor in Computer Science & Engineering at Samrat Ashok Technological Institute Vidisha M.P India. The degree of B.E. (Hons) secured in Computer Science & engineering. She secured M.Tech in Computer science and Engineering from Banasthali University. She is currently pursuing PHD in Computer science and engineering.
Mahendra Thakur
Mr. Mahendra Thakur is a research scholar pursuing M.Tech in Computer Science & Engineering from Samrat Ashok Technological Institute Vidisha M.P India. He secured degree of B.E. in IT from Rajiv Gandhi Technical University, Bhopal (M.P.) India in 2007.
Geetika S. Pandey
Geetika S. Pandey presently working as Asst. Professor in Computer Science & Engineering at Samrat Ashok Technological Institute Vidisha M.P India. The degree of B.E. (Hons) secured in Computer Science & engineering. She secured M.Tech in Computer science and Engineering from Banasthali University. She is currently pursuing PHD in Computer science and engineering.