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A Survey on Web Personalisation and Recommendation Techniques

International Journal of Knowledge Based Computer Systems

Volume 2 Issue 2

Published: 2014
Author(s) Name: Dhaval Patel, Amit Ganatra, C. K. Bhensdadia | Author(s) Affiliation:
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Abstract

The quantity of accessible information on the web continues to grow rapidly and has exceeded human processing capabilities. The sheer amount of the information increases the complexity for users from discovering desired information. Recommendation systems have become a valuable resource for users seeking intelligent ways to search through enormous volume of information available to them. Web logs are important information repository which records users activates on search results. The mining of these logs can improve the performance of search engines, since user has a specific goal when searching for information. In this paper, a survey is provided on the different recommendation techniques with their advantage and drawbacks. A brief comparison of different personalisation techniques based on certain parameters is done.

Keywords: Log Mining, Personalisation, Recommendation Techniques, Web Usage Mining

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