Image annotation refinement using Web-based keyword correlation
http://data.open.ac.uk/oro/23440
is a Article , Academic article

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Dataset Open Research Online
At Proceedings of the 4th International Conference on Semantic and Digital Media Technologies
Date 2009
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Status Peer reviewed
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  • http://data.open.ac.uk/oro/document/11051
  • http://data.open.ac.uk/oro/document/18065
  • http://data.open.ac.uk/oro/document/24950
  • http://data.open.ac.uk/oro/document/6056
Abstract This paper describes a novel approach that automatically refines the image annotations generated by a non-parametric density estimation model. We re-rank these initial annotations following a heuristic algorithm, which uses semantic relatedness measures based on keyword correlation on the Web. Existing approaches that rely on keyword co-occurrence can exhibit limitations, as their performance depend on the quality and coverage provided by the training data. Additionally, WordNet based correlation approaches are not able to cope with words that are not in the thesaurus. We illustrate the effectiveness of our Web-based approach by showing some promising results obtained on two datasets, Corel 5k, and ImageCLEF2009.
Authors authors
Type
Label Llorente, Ainhoa ; Motta, Enrico and Rüger, Stefan (2009). Image annotation refinement using Web-based keyword correlation. In: Semantic Multimedia.
Same as 978-3-642-10543-2_22
Title Image annotation refinement using Web-based keyword correlation