The Design And Implementation Of Weibo Application Recommendation System Based On TOPSIS

With the progress of the society, great changes have taken place in our lives.Social platform network have been paid attention in recent years. It can make peopleput their own mood or experience into the Internet. In order to raise the efficiency ofpopularizing applications of Micro-blogs and achieve the goal that both business andusers get what they what, this paper focus on investing recommendation system ofMicro-blog applications.In this paper, we analyze the data from KDD CUP2012in order to predict theinterests of users. After getting the interesting point of users and the characteristic ofapplications of Micro-blog, we compare them to see if they could mate to each other.According to the user data analysis and the potential keywords, It can helpcompanies to develop products and more close to user needs, more convenient to meetuser requirements. And it enables users to have more good experience. And a goodrecommendation system can help the company reduce the waste of resources and gainmore benefits. At the same time, it has a better user experience. The users will bringmore traffic and better conversion rates for the company, which can bring more profitsfor the company. All in all, recommendation system in many aspects obtain win-winbetween the company and users.And use the result to predict the possibility that a user might accept theapplication which was recommended by the website. In this paper, we choose vitality,@ratio, the number of keywords and the matching number of keywords to test anduse AHP and TOPSIS to establish the model. The program is based on themathematical model. We use the program to do the experiment. The experimentalresult shows that the model is able to predict the interests of users.