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    Presence analytics: density-based social clustering for mobile users

    Eldaw, Habib Sarnoub and Levene, Mark and Roussos, George (2016) Presence analytics: density-based social clustering for mobile users. In: UNSPECIFIED (ed.) ICETE 2016: Proceedings of the 13th International Joint Conference on e-Business and Telecommunications. Setúbal, Portugal: SCITEPRESS - Science and Technology Publications, Lda, pp. 52-62. ISBN 9789897581960.


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    We demonstrate how social density-based clustering of WLAN traces can be utilised to detect granular social groups of mobile users within a university campus. Furthermore, the ability to detect such social groups, which can be linked to the learning activities taking place at target locations, provides an invaluable opportunity to understand the presence and movement of people within such an environment. For example, the proposed density-based clustering procedure, which we call Social-DBSCAN, has real potential to support human mobility studies such as the optimisation of space usage strategies. It can automatically detect the academic term period, the classes, and the attendance data. From a large Eduroam log of an academic site, we chose as a proof concept, selected locations with known capacity for the evaluation of our proposed method, which we successfully utilise to detect the regular learning activities at those locations, and to provide accurate estimates about the attendance levels over the academic term period.


    Item Type: Book Section
    Keyword(s) / Subject(s): Presence Analytics, Density-based Clustering, Social-DBSCAN, WLAN Traces, Wireless Network Traces, Eduroam, Social Groups, Class Attendance, Human Presence, Learning Activity, Mobile Data, Mobile Users
    School: School of Business, Economics & Informatics > Computer Science and Information Systems
    Research Centres and Institutes: Birkbeck Knowledge Lab, Data Analytics, Birkbeck Institute for
    Depositing User: Muawya Eldaw
    Date Deposited: 02 Dec 2016 10:16
    Last Modified: 10 Jun 2021 02:05


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