Research On Personalized Application Recommendation System In The OTA System

With the rapid increase of number of mobile users and the development of mobile technology, it is the fact that many kinds of application provided through OTA(Over The Air) emerged.Meanwhile, different users have different requests. The large number of application may bring users a trouble which one is suitable for them. Therefore, personalized application recommendation system which can meet users' demands effectively needs to be established and should be implemented.As a thesis, the article introduces a model of application recommendation system in the OTA system. It involves current research about personalized recommendation, building the model of the system and the model of mobile users. And concerned algorithms about personalized recommendation are also purposed. Besides, it emphasizes on recommending valuable application for mobile users.In this article, after introducing the significance of this research topic and other backgrounds, it describes a new mobile application recommendation system based on mining user's interests. Some basic principles of data mining and personalized recommendation are introduced at first. And then some details of modeling users, predicting users' interests, and personalized recommending are discussed and the association between users' behavior and their true interests are analyzed. Then a detailed algorithm for finding users' interests and some methods to implement each module are purposed. At last, concerned experiments and analysis are described. Conclusion and future works are also introduced at the end of this article.