A Multimedia Contents Recommendation for Mobile Web Users

As mobile market grows more and more fast, the mobile contents market, especially music contents for mobile phones have recorded remarkable growth. In spite of this rapid growth, mobile web users experience high levels of frustration to search the desired music. New musics are very profitable to the content providers, but the existing collaborative filtering (CF) system can't recommend them. To solve these problems, we propose an extended CF system to reflect the user's real preference by representing the characteristics of users and musics in the feature space. We represent the musics using the music contents based acoustic features in multi-dimensional feature space, and then select a neighborhood with the distance based function. Furthermore, this paper suggests a recommendation for procedure for new music by matching new music with other users' preference. The suggested procedure is explained step by step with an illustration example.