Personalized Multimedia Information Retrieval based on User Profile Mining

Abstract

This paper focuses on how to retrieve personalized multimedia information based on user interest which can be mined from user profile. After analyzing the related works, a general structure of the personalized multimedia information retrieval system is given, which combines online module and offline module. Firstly, we collect a large-sale of photos from multimedia information sharing websites. Then, we record the information of the users who upload the multimedia information. For a given user, we save his history data which could describe the multimedia data. Secondly, the relationship between contents of multimedia data and semantic information is analyzed and then the user interest model is constructed by a modified LDA model which can integrate all the influencing factors in the task of multimedia information retrieval. Thirdly, the query distributions of all the topics can be estimated by the proposed modified LDA model. Thirdly, based on the above offline computing process, the online personalized multimedia information ranking algorithm is given which utilize the user interest model and the query word. Fourthly, multimedia information retrieval results are obtained using the proposed personalized multimedia information ranking algorithm. Finally, performance evaluation is conducted by a series of experiments to test the performance of the proposed algorithm compared with other methods on different datasets.