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Xirong Li receives SIGMM Best Ph.D. Thesis Award 2013

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Article from http://www.ceessnoek.info/

Congratulations to dr. Xirong Li for receiving the SIGMM Award for Outstanding PhD Thesis in Multimedia Computing, Communications and Applications 2013. The committee considered Xirong’s dissertation titled “Content-based visual search learned from social media” as worthy of the award as it substantially extends the boundaries for developing content-based multimedia indexing and retrieval solutions. In particular, it provides fresh new insights into the possibilities for realizing image retrieval solutions in the presence of vast information that can be drawn from the social media.

The committee considered the main innovation of Xirong’s work to be in the development of the theory and algorithms providing answers to the following challenging research questions:
(a) what determines the relevance of a social tag with respect to an image,
(b) how to fuse tag relevance estimators,
(c) which social images are the informative negative examples for concept learning,
(d) how to exploit socially tagged images for visual search and
(e) how to personalize automatic image tagging with respect to a user’s preferences.

The significance of the developed theory and algorithms lies in their power to enable effective and efficient deployment of the information collected from the social media to enhance the datasets that can be used to learn automatic image indexing mechanisms (visual concept detection) and to make this learning more personalized for the user.

Xirong’s thesis is available from the UvA digital academic repository.

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