Probabilistic latent semantic indexing
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
The Philosophy of Information Retrieval Evaluation
CLEF '01 Revised Papers from the Second Workshop of the Cross-Language Evaluation Forum on Evaluation of Cross-Language Information Retrieval Systems
The Journal of Machine Learning Research
Labeling images with a computer game
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Designing games with a purpose
Communications of the ACM - Designing games with a purpose
Today's and tomorrow's retrieval practice in the audiovisual archive
Proceedings of the ACM International Conference on Image and Video Retrieval
On the role of user-generated metadata in audio visual collections
Proceedings of the sixth international conference on Knowledge capture
Contextual keyword extraction by building sentences with crowdsourcing
Multimedia Tools and Applications
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In recent years, crowdsourcing has gained attention as an alternative method for collecting video annotations. An example is the internet video labeling game Waisda? launched by the Netherlands Institute for Sound and Vision. The goal of this PhD research is to investigate the value of the user tags collected with this video labeling game. To this end, we address the following four issues. First, we perform a comparative analysis between user-generated tags and professional annotations in terms of what aspects of videos they describe. Second, we measure how well user tags are suited for fragment retrieval and compare it with fragment search based on other sources like transcripts and professional annotations. Third, as previous research suggested that user tags predominately refer to objects and rarely describe scenes, we will study whether user tags can be successfully exploited to generate scene-level descriptions. Finally, we investigate how tag quality can be characterized and potential methods to improve it.