Constructing a contexual collaborative recommending approach to social network system

Recommender system is mainly based on collaborative filtering algorithms in social network, where it takes folksonomy as basic data structure. Collaborative filtering as a classical method of information retrieval has been also used in helping people to deal with information overload in folksonomies system. When context is taken into account, there might be difficulties when it comes to making recommendations to users who are placed in a context other than the usual one, since these main elements of folksonomy are dependent on their context informations. In this paper, a contextual collaborative filtering model is proposed, which produces recommendations based on the context, and may be better solution to folksonomies in the recommender system. In order to solve the contextual problems emerging in the process of recommendational application, this paper offers a feasible means for developers to handle context problems for folksonomy application.