Abstract
GPS has become a widely deployed and useful tool for commerce, scientific uses, tracking, and surveillance. It can be used to obtain accurate information about a location fairly easily using Global Positioning System (GPS) enabled devices. The increasing availability of location-acquisition technologies (GPS, GSM networks, etc.) enables people to log the location histories with spatio-temporal data. Such real-world location histories imply, to some extent, users’ interests in places, and bring us opportunities to understand the correlation between users and locations. The goal of this paper is to use both the spatial as well as temporal aspects to group the GPS data. We begin by calculating the stay points and then grouping them temporally and determining the location visited most number of times within a time period.
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Srivastava, S., Ahuja, S., Mittal, A. (2012). Determining Most Visited Locations Based on Temporal Grouping of GPS Data. In: Deep, K., Nagar, A., Pant, M., Bansal, J. (eds) Proceedings of the International Conference on Soft Computing for Problem Solving (SocProS 2011) December 20-22, 2011. Advances in Intelligent and Soft Computing, vol 131. Springer, New Delhi. https://doi.org/10.1007/978-81-322-0491-6_6
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DOI: https://doi.org/10.1007/978-81-322-0491-6_6
Publisher Name: Springer, New Delhi
Print ISBN: 978-81-322-0490-9
Online ISBN: 978-81-322-0491-6
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