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Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.GIScience.2023.84
URN: urn:nbn:de:0030-drops-189794
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2023/18979/
Wiedemann, Nina ;
Hong, Ye ;
Raubal, Martin
Predicting visit frequencies to new places (Short Paper)
Abstract
Human mobility exhibits power-law distributed visitation patterns; i.e., a few locations are visited frequently and many locations only once. Current research focuses on the important locations of users or on recommending new places based on collective behaviour, neglecting the existence of scarcely visited locations. However, assessing whether a user will return to a location in the future is highly relevant for personalized location-based services. Therefore, we propose a new problem formulation aimed at predicting the future visit frequency to a new location, focusing on the previous mobility behaviour of a single user. Our preliminary results demonstrate that visit frequency prediction is a difficult task, but sophisticated learning models can detect insightful patterns in the historic mobility indicative of future visit frequency. We believe these models can uncover valuable insights into the spatial factors that drive individual mobility behaviour.
BibTeX - Entry
@InProceedings{wiedemann_et_al:LIPIcs.GIScience.2023.84,
author = {Wiedemann, Nina and Hong, Ye and Raubal, Martin},
title = {{Predicting visit frequencies to new places}},
booktitle = {12th International Conference on Geographic Information Science (GIScience 2023)},
pages = {84:1--84:6},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-288-4},
ISSN = {1868-8969},
year = {2023},
volume = {277},
editor = {Beecham, Roger and Long, Jed A. and Smith, Dianna and Zhao, Qunshan and Wise, Sarah},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/opus/volltexte/2023/18979},
URN = {urn:nbn:de:0030-drops-189794},
doi = {10.4230/LIPIcs.GIScience.2023.84},
annote = {Keywords: Human mobility, Visitation patterns, Place recommendation, Next location prediction}
}