Dynamically personalized music recommendation system for PDA

We introduce a novel personalized music service system through PDA. By providing only users' preferred web pages or smaller readable service pages, the problem of the limitation of resource of PDA can be solved. In this paper, the preferred service pages are obtained from the statistical preference transactions among web pages for each web site. In computing the preference, we consider the ratio of the different of time which was visited and users' real listening time of music recommended. We present a novel algorithm to compute the time weights for different items in a manner that will assign a decreasing weight to old data. Also, our system dynamically provides the personalized music service according to the different three cases such as the beginning stage, the positive feedback, and the negative feedback. In the experimental section, we demonstrate our personalized music service system and show how much the resource of mobile devices can be saved.