Labeling images with a computer game
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Classifying tags using open content resources
Proceedings of the Second ACM International Conference on Web Search and Data Mining
Supporting subject matter annotation using heterogeneous thesauri
International Journal of Human-Computer Studies
Enrichment and Ranking of the YouTube Tag Space and Integration with the Linked Data Cloud
ISWC '09 Proceedings of the 8th International Semantic Web Conference
Sindice.com: weaving the open linked data
ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
Search behavior of media professionals at an audiovisual archive: A transaction log analysis
Journal of the American Society for Information Science and Technology
On the role of user-generated metadata in audio visual collections
Proceedings of the sixth international conference on Knowledge capture
An evaluation of labelling-game data for video retrieval
ECIR'13 Proceedings of the 35th European conference on Advances in Information Retrieval
TAG4VD: a game for collaborative video annotation
Proceedings of the 2013 ACM international workshop on Immersive media experiences
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In the audiovisual domain tagging games are explored as a method to collect user-generated metadata. For example, the Netherlands Institute for Sound and Vision deployed the video labelling game Waisda? to collect user tags for videos from their collection. These tags are potentially useful to improve the access to the content within the videos. However, the uncontrolled tags allow for multiple interpretations, preventing long term access. In this paper we investigate a semi-automatic process to define the interpretation of the tags by linking them to concepts from the Linked Open Data cloud. More specifically, we investigate if existing web services are suited to find a number of candidate concepts, and if human users can select the most appropriate concept from these suggestions. We present a prototype application that supports this process and discuss the results of a user experiment where this application is used with different data sources.