Abstract
We propose a kernel convolution method to predict similar locations (wormholes) based on human travel behaviour. A scaling parameter can be used to define a set of relevant users to the target location and we show how the geotags of these users can effectively be aggregated to predict a ranking of similar locations. We evaluate results on world and city level using several independent test collections. © 2010 Springer-Verlag Berlin Heidelberg.
Cite
CITATION STYLE
Clements, M., Serdyukov, P., De Vries, A. P., & Reinders, M. J. T. (2010). Finding wormholes with flickr geotags. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5993 LNCS, pp. 658–661). Springer Verlag. https://doi.org/10.1007/978-3-642-12275-0_70
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