International Journal of Information and Communication Technology Research

International Journal of Information and Communication Technology Research>> Call for Papers(CFP)>>Volume 7, Number 7, July 2017

International Journal of Information and Communication Technology Research


A New Model for Recommender Systems based on Data Sources Integration

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Author(s) Ali Hashemi, Mohammad Nadimi, Mohammad Naderi
On Pages 27-33
Volume No. 3
Issue No. 1
Issue Date January, 2013
Publishing Date January, 2013
Keywords Recommender system, Web personalization, Web usage mining, Data sources integration, Usersí location, Search engines.


Abstract


The goal of Web recommender system is the process of selecting web pages shown to user based on his navigation patterns and interests. In this paper, a new model for recommender system is proposed to increase the accuracy of recommendations. In this model, some effective data sources are integrated to know the user interestingness. The sources used the proposed model are user spent times on pages, the count of each page views per session, userís location and data referred extracted from search engines. This data sources, combined through proposed model and then clustering operation is performed on it and recommendations are presented to the user through classification operation. In this paper some algorithms are proposed to extract userís interest from each of data sources. The approach is implemented as an experimental system, and its accuracy is evaluated based on F1 criterion.

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