Aspect-Based Tagging for Collaborative Media Organization
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Organizing multimedia data is very challenging. One of the most important approaches to support users in searching and navigating media collections is collaborative filtering. Recently, systems as flickr or last.fm have become popular. They allow users to not only rate but also tag items with arbitrary labels. Such systems replace the concept of a global common ontology, as envisioned by the Semantic Web, with a paradigm of heterogeneous, local “folksonomies”. The problem of such tagging systems is, however, that resulting taggings carry only little semantics. In this paper, we present an extension to the tagging approach. We allow tags to be grouped into aspects. We show that introducing aspects does not only help the user to manage large numbers of tags, but also facilitates data mining in various ways. We exemplify our approach on Nemoz, a distributed media organizer based on tagging and distributed data mining.
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