Identifying Maps on the World Wide Web

Authors:
Matthew Michelson;Aman Goel;Craig A. Knoblock
Affiliations:
Information Sciences Institute, University of Southern California, Marina del Rey, USA CA 90292;Information Sciences Institute, University of Southern California, Marina del Rey, USA CA 90292;Information Sciences Institute, University of Southern California, Marina del Rey, USA CA 90292
Venue:
GIScience '08 Proceedings of the 5th international conference on Geographic Information Science
Year:
2008

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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 F1-measure. Further, our method is more scalable and less costly than previous approaches that rely on more traditional machine learning techniques.