A Personalized Recommendation Algorithm for Mobile Application - SHANG Yan-fei; CHEN De-yun; YANG Hai-lu (Journal of Harbin University of Science and Technology)
For the problem of low precision to both experience satisfaction and personalized requirement of Internet mobile terminal, based on the recommendation method of analyzing information system, a method of mobile APP information recommendation based on user similarity and subject similarity is proposed, which generated information recommendation by the weighted combination of user similarity and personalized, that the recommended information is more personalized, and the recommended accuracy is improved. At the same time, a recommendation algorithm based on complex interest is proposed, which makes the recommendation information more accurate by mining the similarity between users, the behavior of users and the orientation of interest for the recommendation problem of multiuser public account and interest change. Compared with the Popular which has better performance, the algorithm improves the accuracy rate by 3.91%, the recall rate is 3.45%, the coverage rate is improved by 4.84%, and the performance is improved obviously. Therefore, the method proposed in this paper is used to the personalized recommendation of APP, which provides a new method for mobile APP′s personalized recommendation.