A Personalized Recommendation Method Considering Local and Global Influences

Social Media is one of the largest media data storage in the website. Many researchers utilize this to do some research about user interest and recommendation system. This data is like a treasure vault waiting to be utilized to develop the recommendation systems. Social common interest is one of the methodologies to implement the recommendation system among users. It performs well in community with similar interest. The drawback of it ignores the outside influence from other communities. In this paper, a methodology to calculate the global influence from outside community and to implement the recommendation system is proposed. The results could be utilized to make the recommendation system not only in local communities but also notice the outside influence of item in social media.