Volume : IV, Issue : V, May - 2015

Cold Start Solving Recommender System with Social Contextual Information

Deepa Johny

Abstract :

 Recommender systems made people easier to find recommendations like posts, products, information, and even  other people. As the usage and popularity of social networking sites increases day by day, the recommender system  also becomes more demandable. It is significant and challenging to ing together all the social contextual factors from users based on psychology and sociology studies like individual preference and interpersonal influence. The existing approaches consider these social contextual factors but not the new user problem and the new item problem effectively. This paper answers the problem of the new user problem and  the new item problem in the probabilistic matrix factorization method so that it gives more effective recommendations. 

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Article: Download PDF   DOI : 10.36106/ijsr  

Cite This Article:

Deepa Johny Cold Start Solving Recommender System with Social Contextual Information International Journal of Scientific Research, Vol : 4, Issue : 5 May 2015

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