@inproceedings{Fan2008Novel-5599,
  year={2008},
  doi={10.1145/1460096.1460155},
  title={A Novel Approach to Enable Semantic and Visual Image Summarization for Exploratory Image Search},
  isbn={978-1-60558-312-9},
  publisher={ACM Press},
  address={New York, New York, USA},
  booktitle={Proceeding of the 1st ACM international conference on Multimedia information retrieval - MIR '08},
  pages={358--365},
  author={Fan, Jianping and Gao, Yuli and Luo, Hangzai and Keim, Daniel A. and Li, Zongmin}
}

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    <dc:language>eng</dc:language>
    <dc:creator>Li, Zongmin</dc:creator>
    <dc:creator>Fan, Jianping</dc:creator>
    <dc:creator>Keim, Daniel A.</dc:creator>
    <dc:contributor>Keim, Daniel A.</dc:contributor>
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    <bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/5599"/>
    <dcterms:bibliographicCitation>First publ. as paper  in: Proceeding of the 1st ACM international conference on Multimedia information retrieval, Vancouver, British Columbia, Canada, October 30-31, 2008</dcterms:bibliographicCitation>
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    <dc:contributor>Fan, Jianping</dc:contributor>
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    <dc:contributor>Gao, Yuli</dc:contributor>
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    <dcterms:abstract xml:lang="eng">In this paper, we have developed a novel scheme to incorporate topic network and representativeness-based sampling for achieving semantic and visual summarization and visualization of large-scale collections of Flickr images. First, topic network is automatically generated for summarizing and visualizing large-scale collections of Flickr images at a semantic level, so that users can select more suitable keywords for more precise query formulation. Second, the diverse visual similarities between the semantically-similar images are characterized more precisely by using a mixture-of-kernels and a representativeness-based image sampling algorithm is developed to achieve similarity-based summarization and visualization of large amounts of images under the same topic, so that users can find some particular images of interest more effectively. Our experiments on large-scale image collections with diverse semantics have provided very positive results.</dcterms:abstract>
    <dcterms:title>A Novel Approach to Enable Semantic and Visual Image Summarization for Exploratory Image Search</dcterms:title>
    <dc:contributor>Li, Zongmin</dc:contributor>
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    <dc:contributor>Luo, Hangzai</dc:contributor>
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    <dcterms:issued>2008</dcterms:issued>
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