A Survey on Web Personalisation and Recommendation Techniques
Published: 2014
Author(s) Name: Dhaval Patel, Amit Ganatra, C. K. Bhensdadia |
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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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