Research on the Personal Recommendation Algorithm Based on Grey Relationship

With the rapid development of Internet technology, personal recommendation systems have become effective in the search for massive data on the user´s most important tool useful information. Personal recommendation algorithm is the core of the recommendation system and is paid more attention by many researchers. Collaborative filtering algorithm is proposed firstly and is used widely. This paper analyzes the traditional collaborative filtering algorithms firstly and presents some shortcomings in it. Through the introduction of the gray relational coefficient, this paper presents the calculation method of grey relational similarity for personal recommendation, and analyzes its properties. By using Movie-Lens data set, the paper compares the advantages and disadvantages of the two algorithms. The numerical results show that the grey personal recommendation algorithm greatly improved the accuracy of recommendation system, At last, some conclusions are presented in the paper.