Istituto di Scienza e Tecnologie dell'Informazione     
De Alencar L. A., Alvares L. O., Bogorny V., Renso C., Raffaetą A. A rule-based method for discovering trajectory profiles. In: SEKE - The 27th International Conference on Software Engineering and Knowledge Engineering (Pittsburgh, USA, 6-8 July 2015). Proceedings, pp. 244 - 249. Knowledge Systems Institute Graduate School, 2015.
The discovery of people profiles such as work- ers, students, families with kids, etc, is of interest for several application domains. For decades, such information has been extracted using census data, and more recently, from social networks, where people's profile is clearly defined. A new type of data that has not been explored for discovering profiles, but which stores the real movement of people, are trajectories of moving objects. In this paper we propose a rule-based method to represent socio-demographic profiles, a moving object history model to summarize the daily movement of individuals, and define similarity functions for matching the profile model and the history model. We evaluate the method for single and multiple profile discovery.
DOI: 10.18293/SEKE2015-143
Subject Trajectories
Profile identification
H.2.8 DATABASE MANAGEMENT. Database Applications
68U35 Information systems

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