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Title

Multimedia Retrieval and Classification for Web Content

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Published in Proceedings of BCS IRSG Symposium: Future Directions in Information Access (FDIA). Glasgow (Scotland) - Aug 28-29 - . 2007
Abstract The population of the World Wide Web with media of all types such as texts, images, videos and audio files in recent years raised the attractiveness of multimedia retrieval. With our work on the influence of dependencies between modalities and features we investigate why these approaches still do not perform convincingly better than plain text search approaches when applied to large, noisy collections like web content, even though these approaches have more information at their hands. This article suggests that, due to the size and noise, the modality’s dependencies necessary for efficient information fusion becomes small and hard to exploit. Preliminary experiments with two multi modal collections underpin this statement.
Keywords Multimedia RetrievalMultimedia ClassificationMulti modal information fusion
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Research groups Viper group
Computer Vision and Multimedia Laboratory
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KLUDAS, Jana. Multimedia Retrieval and Classification for Web Content. In: Proceedings of BCS IRSG Symposium: Future Directions in Information Access (FDIA). Glasgow (Scotland). [s.l.] : [s.n.], 2007. https://archive-ouverte.unige.ch/unige:47782

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Deposited on : 2015-03-06

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