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Personalized Multimedia Retrieval in CADAL Digital Library

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Advances in Multimedia Information Processing - PCM 2008 (PCM 2008)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5353))

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Abstract

CADAL has been a large digital library including million digital books and large volumes of multimedia resources, e.g. videos, images. In this paper, in order to overcome the problem of information overload, we propose a framework of personalized cross-media retrieval in CADAL digital library and present the details of the algorithms used in the personalized cross-media retrieval, which is a new kind of retrieval technology by which query examples and search results can be of different modalities. In order to provide personalized cross-media retrieval, we construct the uniform cross-media correlation graph in terms of three kinds of information: low-level features of media objects, co-existence information between them and semantic correlations between MMDs that are mined out of large amounts of logs. Moreover, we also use the in-session relevance feedback approach to mine the hints in the positive and negative examples to boost the retrieval performance for the individuals.

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© 2008 Springer-Verlag Berlin Heidelberg

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Zhang, Y., Wu, J., Zhuang, Y. (2008). Personalized Multimedia Retrieval in CADAL Digital Library. In: Huang, YM.R., et al. Advances in Multimedia Information Processing - PCM 2008. PCM 2008. Lecture Notes in Computer Science, vol 5353. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89796-5_72

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  • DOI: https://doi.org/10.1007/978-3-540-89796-5_72

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-89795-8

  • Online ISBN: 978-3-540-89796-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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