Extracting Visited Points of Interest from Vehicle Trajectories

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3 Citations (Scopus)

Abstract

Identifying visited points of interest (PoIs) from vehicle trajectories remains an open problem that is difficult due to vehicles parking often at some distance from the visited PoI and due to some regions having a high PoI density. We propose a visited PoI extraction (VPE) method that identifies visited PoIs using a Bayesian network. The method considers stay duration, weekday, arrival time, and PoI category to compute the probability that a PoI is visited. We also provide a method to generate labeled data from unlabeled GPS trajectories. An experimental evaluation shows that VPE achieves a precision@3 value of 0.8, indicating that VPE is able to model the relationship between the temporal features of a stop and the category of the visited PoI.
Original languageEnglish
Title of host publicationProceedings of the Fourth International ACM Workshop on Managing and Mining Enriched Geo-Spatial Data
Number of pages6
PublisherAssociation for Computing Machinery
Publication date2017
Article number2
ISBN (Electronic)978-1-4503-5047-1
DOIs
Publication statusPublished - 2017
EventFourth International ACM SIGMOD Workshop on Managing and Mining Enriched Geo-Spatial Data - Chicago, United States
Duration: 14 May 201719 May 2017

Workshop

WorkshopFourth International ACM SIGMOD Workshop on Managing and Mining Enriched Geo-Spatial Data
CountryUnited States
CityChicago
Period14/05/201719/05/2017

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