TY - JOUR
T1 - Inferring long-term user properties based on users' location history
AU - Matsuo, Yutaka
AU - Okazaki, Naoaki
AU - Izumi, Kiyoshi
AU - Nakamura, Yoshiyuki
AU - Nishimura, Takuichi
AU - Hasida, Kôiti
AU - Nakashima, Hideyuki
PY - 2007/12/1
Y1 - 2007/12/1
N2 - Recent development of location technologies enables us to obtain the location history of users. This paper proposes a new method to infer users' long-term 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.
AB - Recent development of location technologies enables us to obtain the location history of users. This paper proposes a new method to infer users' long-term 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.
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M3 - Conference article
AN - SCOPUS:84880865034
SP - 2159
EP - 2165
JO - IJCAI International Joint Conference on Artificial Intelligence
JF - IJCAI International Joint Conference on Artificial Intelligence
SN - 1045-0823
T2 - 20th International Joint Conference on Artificial Intelligence, IJCAI 2007
Y2 - 6 January 2007 through 12 January 2007
ER -