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IJCAI
2007

Inferring Long-term User Properties Based on Users' Location History

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Inferring Long-term User Properties Based on Users' Location History
Recent development of location technologies enables us to obtain the location history of users. This paper proposes a new method to infer users’ longterm properties from their respective location histories. Counting the instances of sensor detection for every user, we can obtain a sensor-user matrix. After generating features from the matrix, a machine learning approach is taken to automatically classify users into different categories for each user property. Inspired by information retrieval research, the problem to infer user properties is reduced to a text categorization problem. We compare weightings of several features and also propose sensor weighting. Our algorithms are evaluated using experimental location data in an office environment.
Yutaka Matsuo, Naoaki Okazaki, Kiyoshi Izumi, Yosh
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2007
Where IJCAI
Authors Yutaka Matsuo, Naoaki Okazaki, Kiyoshi Izumi, Yoshiyuki Nakamura, Takuichi Nishimura, Kôiti Hasida, Hideyuki Nakashima
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