Data mining techniques for web personalization: algorithms and applications

Uchyigit, G (2009) Data mining techniques for web personalization: algorithms and applications In: Xiang, Y and Ali, S, eds. Dynamic and Advanced Data Mining for Progressing Technological Development. IGI Global. ISBN 9781605669083

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Abstract

The increase in the information overload problem poses new challenges in the area of web personalization. Traditionally, data mining techniques have been extensively employed in the area of personalization, in particular data processing, user modeling and the classification phases. More recently the popularity of the semantic web has posed new challenges in the area of web personalization necessitating the need for more richer semantic based information to be utilized in all phases of the personalization process. The use of the semantic information allows for better understanding of the information in the domain which leads to more precise definition of the user’s interests, preferences and needs, hence improving the personalization process. data mining algorithms are employed to extract richer semantic information from the data to be utilized in all phases of the personalization process. This chapter presents a stateof- the-art survey of the techniques which can be used to semantically enhance the data processing, user modeling and the classification phases of the web personalization process.

Item Type:Chapter in book
Subjects:G000 Computing and Mathematical Sciences > G400 Computing
Faculties:Faculty of Science and Engineering > School of Computing, Engineering and Mathematics > Computational Intelligence
ID Code:8637
Deposited By:editor cmis
Deposited On:31 May 2011 10:36
Last Modified:11 Apr 2012 13:56

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