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Preference-Based Trajectory Clustering - An Application of Geometric Hitting Sets

Authors Florian Barth, Stefan Funke, Claudius Proissl

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Author Details

Florian Barth
  • Universiät Stuttgart, Germany
Stefan Funke
  • Universität Stuttgart, Germany
Claudius Proissl
  • Universität Stuttgart, Germany

Funding

This work was in part supported by the Deutsche Forschungsgemeinschaft (DFG) within the priority program 1894: Volunteered Geographic Information: Interpretation, Visualization and Social Computing.

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Florian Barth, Stefan Funke, and Claudius Proissl. Preference-Based Trajectory Clustering - An Application of Geometric Hitting Sets. In 32nd International Symposium on Algorithms and Computation (ISAAC 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 212, pp. 15:1-15:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
https://doi.org/10.4230/LIPIcs.ISAAC.2021.15

Abstract

In a road network with multicriteria edge costs we consider the problem of computing a minimum number of driving preferences such that a given set of paths/trajectories is optimal under at least one of these preferences. While the exact formulation and solution of this problem appears theoretically hard, we show that in practice one can solve the problem exactly even for non-homeopathic instance sizes of several thousand trajectories in a road network of several million nodes. We also present a parameterized guaranteed-polynomial-time scheme with very good practical performance.

Subject Classification

ACM Subject Classification
  • Theory of computation → Discrete optimization
  • Theory of computation → Computational geometry
Keywords
  • Route planning
  • personalization
  • computational geometry

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Supplementary Materials

References

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