Detecting Spam Tags Against Collaborative Unfair Through Trust Modelling
In the past few years sharing photos, within social networks has become very popular. In order to make this huge collection easier to explore, images are usually tagged with representative keywords such as persons, events, objects and locations. In order to speed up the time consuming tag annotation process, tags can be propagated based on the similarity between image content and context. In this paper, daily and continuous communication implies the exchange of several types of content, including free text, image, audio and video data.
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