Ilkcan Keles

Learn More
Predicting the location of people from their mobile phone logs is becoming an attractive research area. Due to two main reasons this problem is very challenging: the log data is very large and there is a variety of granularity levels both for specifying the location and the time, especially with low granularity level it becomes much more complicated to(More)
Due to the increasing use of mobile phones and their increasing capabilities, huge amount of usage and location data can be collected. Location prediction is an important task for mobile phone operators and smart city administrations to provide better services and recommendations. In this work, we propose a sequence mining based approach for location(More)
Predicting the next location of people from their mobile phone logs has become an active research area. Due to two main reasons this problem is very challenging: the log data is very large and there are variety of granularity levels for specifying the spatial and the temporal attributes. In this work, we focus on predicting the next location change of the(More)
The web is increasingly being accessed from mobile devices, and studies suggest that a large fraction of keyword-based search engine queries have local intent, meaning that users are interested in local content and that the underlying ranking function should take into account both relevance to the query keywords and the query location. A key challenge in(More)
  • 1