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Sensors 2017, 17(9), 1949; https://doi.org/10.3390/s17091949

Fuzzy Modelling for Human Dynamics Based on Online Social Networks

Department of Communications and Information Engineering, University of Murcia, Murcia 30100, Spain
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Received: 30 June 2017 / Revised: 17 August 2017 / Accepted: 21 August 2017 / Published: 24 August 2017
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Abstract

Human mobility mining has attracted a lot of attention in the research community due to its multiple implications in the provisioning of innovative services for large metropolises. In this scope, Online Social Networks (OSN) have arisen as a promising source of location data to come up with new mobility models. However, the human nature of this data makes it rather noisy and inaccurate. In order to deal with such limitations, the present work introduces a framework for human mobility mining based on fuzzy logic. Firstly, a fuzzy clustering algorithm extracts the most active OSN areas at different time periods. Next, such clusters are the building blocks to compose mobility patterns. Furthermore, a location prediction service based on a fuzzy rule classifier has been developed on top of the framework. Finally, both the framework and the predictor has been tested with a Twitter and Flickr dataset in two large cities. View Full-Text
Keywords: fuzzy clustering; urban mobility; online social networks fuzzy clustering; urban mobility; online social networks
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Cuenca-Jara, J.; Terroso-Saenz, F.; Valdes-Vela, M.; Skarmeta, A.F. Fuzzy Modelling for Human Dynamics Based on Online Social Networks. Sensors 2017, 17, 1949.

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