Voronoi diagrams—a survey of a fundamental geometric data structure
ACM Computing Surveys (CSUR)
Using GPS to learn significant locations and predict movement across multiple users
Personal and Ubiquitous Computing
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Introduction to Information Retrieval
Introduction to Information Retrieval
Mining interesting locations and travel sequences from GPS trajectories
Proceedings of the 18th international conference on World wide web
SeMiTri: a framework for semantic annotation of heterogeneous trajectories
Proceedings of the 14th International Conference on Extending Database Technology
Towards geosocial recommender systems
Proceedings of the 4th International Workshop on Web Intelligence & Communities
Location-based recommendation system using Bayesian user's preference model in mobile devices
UIC'07 Proceedings of the 4th international conference on Ubiquitous Intelligence and Computing
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Trajectories of people contain a vast amount of information on users' interests and popularity of locations. To obtain this information, the places visited by the owner of the device on such a trajectory need to be recognized. However, the location information on a point of interest (POI) in a database is normally limited to an address and a coordinate pair, rather than a polygon describing its boundaries. A region of interest can be used to intersect trajectories to match trajectories with objects of interest. In the absence of expensive and often not publicly available detailed spatial data like cadastral data, we need to approximate this ROI. In this paper, we present several approaches to approximate the size and shape of ROIs, by integrating data from multiple public sources, a validation technique, and a validation of these approaches against the cadastral data of the city of Enschede, The Netherlands.