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A collection of visual thesauri for browsing large collections of geographic images

Author

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  • Marshall C. Ramsey
  • Hsinchun Chen
  • Bin Zhu
  • Bruce R. Schatz

Abstract

Digital libraries of geo‐spatial multimedia content are currently deficient in providing fuzzy, concept‐based retrieval mechanisms to users. The main challenge is that indexing and thesaurus creation are extremely labor‐intensive processes for text documents and especially for images. Recently, 800,000 declassified satellite photographs were made available by the United States Geological Survey. Additionally, millions of satellite and aerial photographs are archived in national and local map libraries. Such enormous collections make human indexing and thesaurus generation methods impossible to utilize. In this article we propose a scalable method to automatically generate visual thesauri of large collections of geo‐spatial media using fuzzy, unsupervised machine‐learning techniques.

Suggested Citation

  • Marshall C. Ramsey & Hsinchun Chen & Bin Zhu & Bruce R. Schatz, 1999. "A collection of visual thesauri for browsing large collections of geographic images," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 50(9), pages 826-834.
    • Handle: RePEc:bla:jamest:v:50:y:1999:i:9:p:826-834
    DOI: 10.1002/(SICI)1097-4571(1999)50:93.0.CO;2-H
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    Cited by:

    1. Frias-Martinez, E. & Magoulas, G. & Chen, S. & Macredie, R., 2006. "Automated user modeling for personalized digital libraries," International Journal of Information Management, Elsevier, vol. 26(3), pages 234-248.

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