WordNet: a lexical database for English
Communications of the ACM
The Semantics of Semantic Annotation
On the Move to Meaningful Internet Systems, 2002 - DOA/CoopIS/ODBASE 2002 Confederated International Conferences DOA, CoopIS and ODBASE 2002
Usage patterns of collaborative tagging systems
Journal of Information Science
Towards automatic extraction of event and place semantics from flickr tags
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Flickr tag recommendation based on collective knowledge
Proceedings of the 17th international conference on World Wide Web
Ontologies are us: a unified model of social networks and semantics
ISWC'05 Proceedings of the 4th international conference on The Semantic Web
Modeling Human Judgment of Digital Imagery for Multimedia Retrieval
IEEE Transactions on Multimedia
Tag-based algorithms can predict human ratings of which objects a picture shows
Multimedia Tools and Applications
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Many online platforms allow users to describe resources with freely chosen keywords, so called tags. The specific meaning of a tag as well as its specific relation to the tagged resource are left open for interpretation to the user. Although human users mostly have a fair chance at interpreting it, machines do not. An algorithmic approach for identifying descriptive tags however could prove useful for intelligent search for pictures and providing first-cut overviews over tagged picture repositories. In this paper we investigate the characteristics of the problem to decide which tags describe visible entities on a given picture. Based on a systematic user study, we are able to discuss in detail the problems involved for both humans and machines when identifying descriptive tags. Furthermore, we investigate the general feasibility of developing a tag-based algorithm tackling this question. Finally, a concrete implementation and its evaluation are presented.