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    Creating a Large-Scale Digital Library for Georeferenced Information

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    Author
    Zhu, Bin
    Ramsey, Marshall C.
    Ng, Tobun Dorbin
    Chen, Hsinchun
    Schatz, Bruce R.
    Issue Date
    1999-07
    Submitted date
    2004-09-04
    Keywords
    Geographic Digital Libraries
    Geographic Information Science
    Digital Libraries
    Local subject classification
    National Science Digital Library
    NSDL
    Artificial intelligence lab
    AI lab
    Geospatial Knowledge Representation System
    GKRS
    
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    Citation
    Creating a Large-Scale Digital Library for Georeferenced Information 1999-07, 5(7/8) D-Lib Magazine
    Journal
    D-Lib Magazine
    Description
    Artificial Intelligence Lab, Department of MIS, University of Arizona
    URI
    http://hdl.handle.net/10150/105172
    Abstract
    Digital libraries with multimedia geographic content present special challenges and opportunities in today's networked information environment. One of the most challenging research issues for geospatial collections is to develop techniques to support fuzzy, concept-based, geographic information retrieval. Based on an artificial intelligence approach, this project presents a Geospatial Knowledge Representation System (GKRS) prototype that integrates multiple knowledge sources (textual, image, and numerical) to support concept-based geographic information retrieval. Based on semantic network and neural network representations, GKRS loosely couples different knowledge sources and adopts spreading activation algorithms for concept-based knowledge inferencing. Both textual analysis and image processing techniques have been employed to create textual and visual geographical knowledge structures. This paper suggests a framework for developing a complete GKRS-based system and describes in detail the prototype system that has been developed so far.
    Type
    Journal Article (On-line/Unpaginated)
    Language
    en
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