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Spatial Ranking Methods for Geographic Information Retrieval (GIR) in Digital Libraries

  • Ray R. Larson
  • Patricia Frontiera
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3232)

Abstract

This paper presents results from an evaluation of algorithms for ranking results by probability of relevance for Geographic Information Retrieval (GIR) applications. We review the work done on GIR and especially on ranking algorithms for GIR. We evaluate these algorithms using a test collection of 2500 metadata records from a geographic digital library. We present an algorithm for GIR ranking based on logistic regression from samples of the test collection. We also examine the effects of different representations of the geographic regions being searched, including minimum bounding rectangles, and convex hulls.

Keywords

Convex Hull Digital Library Average Precision Ranking Method Test Collection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Ray R. Larson
    • 1
  • Patricia Frontiera
    • 2
  1. 1.School of Information Management and Systems 
  2. 2.College of Environmental DesignUniversity of California, BerkeleyBerkeleyUSA

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