Location prediction in location-based social networks

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Published: Dec 24, 2017
Updated: 2017-12-24
Versions:
2017-12-24 (1)
DOI: https://doi.org/10.18844/gjit.v7i3.2835

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Mucahit Baydar
Department of Computer Engineering, Yildiz Technical University, 34349 Istanbul, Turkey, and Department of Nanotechnology, Anadolu University, 26470 Eskişehir, Turkey
Songul Albayrak
Department of Computer Engineering, Yildiz Technical University, 34220 İstanbul, Turkey.

Abstract

Abstract
Developments in mobile devices and wireless networks have led to the increasing popularity of location-based social networks. These networks allow users to explore new places, share their location, videos and photos and make friends. They give information about the mobility of users, which can be used to improve the networks. This paper studies the problem of predicting the next check-in of users of location-based social networks. For an accurate prediction, we first analyse the datasets that are obtained from the social networks, Foursquare and Gowalla. Then we obtain some features like place popularity, place popular time range, place distance to user’s home, user’s past visits, category preferences and friendships ,which are used for prediction and deeper understanding of the user behaviours. We use each feature individually, and then in combination, using the new method. Finally, we compare the acquired results and observe the improvement with the new method.
Keywords: Location prediction, location-based social network, check-in data.

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How to Cite
Baydar, M., & Albayrak, S. (2017). Location prediction in location-based social networks. Global Journal of Information Technology: Emerging Technologies, 7(3), 149–156. https://doi.org/10.18844/gjit.v7i3.2835
Issue
Vol. 7 No. 3 (2017): December
Section
Articles
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