Northampton Electronic Collection of Theses and Research

Presence Analytics: Density-based Social Clustering for Mobile Users

Eldaw, M. H. S., Levene, M. and Roussos, G. (2016) Presence Analytics: Density-based Social Clustering for Mobile Users. In: Proceedings of the 13th International Joint Conference on e-Business and Telecommunications (ICETE 2016) : Volume 6: WINSYS. PRT: SCITEPRESS. pp. 52-62.

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Eldaw_etal_ICETE_2016_Presence_Analytics_Density_based_Social_Clustering_for_Mobile_Users.pdf - Published Version
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Abstract:
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.
Creators:
Eldaw, M. H. S., Levene, M. and Roussos, G.
Publisher:
SCITEPRESS
Date:
26 July 2016
Date Type:
Publication
Page Range:
pp. 52-62
Title of Book:
Proceedings of the 13th International Joint Conference on e-Business and Telecommunications (ICETE 2016) : Volume 6: WINSYS
Volume:
6
Event Title:
13th International Joint Conference on e-Business and Telecommunications
Event Dates:
2016-07-26 - 2016-07-28
Place of Publication:
PRT
Language:
English
ISBN:
9789897581960
DOI:
10.5220/0005970200520062
Status:
Published / Disseminated
Refereed:
Yes
Related URLs:
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