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Identifying Maps on the World Wide Web

Published: 23 September 2008 Publication History

Abstract

This paper presents an automatic approach to mining collections of maps from the Web. Our method harvests images from the Web and then classifies them as maps or non-maps by comparing them to previously classified map and non-map images using methods from Content-Based Image Retrieval (CBIR). Our approach outperforms the accuracy of the previous approach by 20% in F<Subscript>1</Subscript>-measure. Further, our method is more scalable and less costly than previous approaches that rely on more traditional machine learning techniques.

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Cited By

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  • (2012)A deformation analysis method for artificial maps based on geographical accuracy and its applicationsProceedings of the 2nd Joint WICOW/AIRWeb Workshop on Web Quality10.1145/2184305.2184310(19-26)Online publication date: 16-Apr-2012
  • (2009)Classification of raster maps for automatic feature extractionProceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems10.1145/1653771.1653793(138-147)Online publication date: 4-Nov-2009
  1. Identifying Maps on the World Wide Web

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      Published In

      cover image Guide Proceedings
      GIScience '08: Proceedings of the 5th international conference on Geographic Information Science
      September 2008
      392 pages

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      Springer-Verlag

      Berlin, Heidelberg

      Publication History

      Published: 23 September 2008

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      • (2012)A deformation analysis method for artificial maps based on geographical accuracy and its applicationsProceedings of the 2nd Joint WICOW/AIRWeb Workshop on Web Quality10.1145/2184305.2184310(19-26)Online publication date: 16-Apr-2012
      • (2009)Classification of raster maps for automatic feature extractionProceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems10.1145/1653771.1653793(138-147)Online publication date: 4-Nov-2009

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