ABSTRACT
We propose a method to predict a user's favourite locations in a city, based on his Flickr geotags in other cities. We define a similarity between the geotag distributions of two users based on a Gaussian kernel convolution. The geotags of the most similar users are then combined to rerank the popular locations in the target city personalised for this user.
We show that this method can give personalised travel recommendations for users with a clear preference for a specific type of landmark.
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Index Terms
- Using flickr geotags to predict user travel behaviour
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