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.
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Michelson, M., Goel, A., Knoblock, C.A. (2008). Identifying Maps on the World Wide Web. In: Cova, T.J., Miller, H.J., Beard, K., Frank, A.U., Goodchild, M.F. (eds) Geographic Information Science. GIScience 2008. Lecture Notes in Computer Science, vol 5266. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87473-7_16
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DOI: https://doi.org/10.1007/978-3-540-87473-7_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-87472-0
Online ISBN: 978-3-540-87473-7
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