Research on Personalized Application Recommendation System in the OTA System Based on Mining Users´ Interests

At present, mobile network operators pay much more attention to personalized service than they used to. It is necessary to provide pertinent service to different customers who may have different demands. To meet the need of personalized recommendation system and aim at implementing personalized application recommendation, a new model in the OTA (Over the Air) system is proposed at the beginning of this paper. Then the paper focuses on the relationship between user´s behavior of using this system and their preference and discusses the interests reflected by their behavior, and gives an algorithm of mining users´ preference. And then the paper introduces a personalized application recommendation engine based on the methods of clustering and mining association rules to implement recommendation about valuable application items for users.