Project Lachesis: Parsing and Modeling Location Histories

  • Ramaswamy Hariharan
  • Kentaro Toyama
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3234)


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.


Location History Stay Duration Recur Time Interval Real Number Line Subject Destination 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Ramaswamy Hariharan
    • 1
  • Kentaro Toyama
    • 2
  1. 1.School of Information and Computer ScienceUniversity of California, IrvineIrvineUSA
  2. 2.Microsoft ResearchRedmondUSA

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