A multi-criteria Recommender System for Tag Annotation
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Web 2.0 signifies an altered use of the internet. Interaction and collaboration are standing in the spotlight. An important role in most Web 2.0 applications is ascribed to the tagging of user generated content. However, the simplicity of tagging entails some limitations. Since every user associates different things with an object, from an objective point of view, tags are often imprecise. We will present an approach that pursues the idea to disseminate a consistent vocabulary amongst all users by providing the users proactively suitable recommendations to tag images. In addition to existing tag-relation based approaches, we include the image analyzes of the image to get graphical and theatrical similar images and then extend the tag recommendation with the retrieved context information.