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Estimating Collaborative Filtering Technique for Web Personalization  
Faria Kanwal1,Komal Bashir2,Ayesha Haider Ali3
1, LCWU Lahore, Email : faria.kanwal@gmail.com
2, LCWU, Email : ko_junaid@yahoo.com
*3, LCWU, Email : ayesha.iqbal@gmail.com
Abstract .World Wide Web is rapidly growing in size and usability. Web personalization is the hub of many e-commerce websites and web portals. It is the process of getting and storing information about site users. Moreover, web personalization helps in analyzing the information and then delivering the required data to the user. A number of techniques are proposed to acquire the better results. Collaborative filtering technique among all technique is better in a way that it provides recommendation to new user, based on the preference of similar users. All personalization techniques suffer from sparsity and black box problem. Association retrieval technique helps in reducing the sparsity and black box problems causing the limited recommendations and results to the new users of the website. To overcome the problem in Collaborative filtering technique gain the better results through this technique by recommending the transitive dependencies of the user to the items selected. Recommender system problems are identified and estimated.
Keywords : world wide web ; sparsity ; web personalization ; World Wide Web, Web Personalization, Collaborative ; World Wide Web;Web Personalization;Collaborative
 URL: http://dx.doi.org/10.7321/jscse.v3.n11.3  

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