Abstract

AbstractWith the increase of media-sharing web sites such as YouTube and Flickr, there are more and more shared multimedia resources on the Web. Multimedia search becomes more important and challenging, as users demand higher retrieval quality. To achieve this goal, multimedia search needs to take users’ personalized information into consideration. Collaborative tagging systems allow users to annotate resources with their own tags, which provide a simple but powerful way for organizing, retrieving and sharing different types of social media. The user profiles obtained from collaborative tagging systems should be very useful for resource retrieval. In this paper, we propose a new method to model user profiles and resource profiles from wider perspectives and apply them to personalized resource search in a collaborative tagging environment. We implement a prototype system named as FMRS. Experiments in FMRS show that our proposed method outperforms baseline methods.KeywordsBaseline MethodPreference DegreePersonalized SearchMultimedia ResourceMean Reciprocal RankThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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