Abstract
A datatype with increasing importance in GIS is what we call the location history–a record of an entity’s location in geographical space over an interval of time. This paper proposes a number of rigorously defined data structures and algorithms for analyzing and generating location histories. Stays are instances where a subject has spent some time at a single location, and destinations are clusters of stays. Using stays and destinations, we then propose two methods for modeling location histories probabilistically. Experiments show the value of these data structures, as well as the possible applications of probabilistic models of location histories.
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Hariharan, R., Toyama, K. (2004). Project Lachesis: Parsing and Modeling Location Histories. In: Egenhofer, M.J., Freksa, C., Miller, H.J. (eds) Geographic Information Science. GIScience 2004. Lecture Notes in Computer Science, vol 3234. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30231-5_8
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DOI: https://doi.org/10.1007/978-3-540-30231-5_8
Publisher Name: Springer, Berlin, Heidelberg
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