Design & Study Of Mobile Internet App Recommend System Base On Complex Network

In the’information explosion’age, huge amounts of information not only bring value also binds confusion together, people are lost themselves in mass information when they want to accurately and quickly search effective information and knowledge. Now, search system and recommend engine are changing the view of life and the world, especially the more intelligent recommended systems have penetrated into all aspects of our doing in the network.Complex network is a raise and cross discipline in recent years, it’s a special view and theory that influences our academic and practice. Some concept and theory such as small world, no scale, network power and evolution, link prediction, have help many subjects in-depth understanding of the complexity of the world.Mobile Internet is the future of the Internet, the user number has reported more than the traditional’s, the App application recommendation system is service in mobile Internet that use to help App users find suitable for or likely App application in the huge App application.Complex network theory can be use as a very good describes way of recommend system. Follow the content of the recommender and Complex network, this paper presented a different to the previous traditional heterogeneous weighted bipartite network, using the complex network community classification concept work for the purpose of link prediction, paper puts forward a kind of homogeneous weighted degree dynamic community division method, narrow and refine data. Use a method that combined with interest and popular concept named’modified weighted resource allocation method’to calculate the similar results. At last, We design a hybrid algorithm recommendation system combined with a variety of other traditional recommendation algorithm, in order to help solve the problem of the users lost in App markets.