Please use this identifier to cite or link to this item: http://www.repositorio.ufop.br/handle/123456789/8826
Title: Workload characterization of a location-based social network.
Authors: Lins, Theo Silva
Pereira, Adriano César Machado
Souza, Fabrício Benevenuto de
Keywords: Workload characterization
Location-based social networks
Issue Date: 2014
Citation: LINS, T. S.; PEREIRA, A. C. M.; BEVENUTO, F. R. Workload characterization of a location-based social network. Social Network Analysis and Mining, v. 4, p. 209, 2014. Disponível em: <https://link.springer.com/article/10.1007/s13278-014-0209-1>. Acesso em: 28 jul. 2017.
Abstract: Recently, there has been a large popularization of location-based social networks, such as Foursquare and Apontador, in which users can share their current locations, upload tips and make comments about places. Part of this popularity is due to facility access to the Internet through mobile devices with GPS. Despite the various efforts towards understanding characteristics of these systems, little is known about the access pattern of users in these systems. Providers of this kind of services need to deal with different challenges that could benefit of such understanding, such as content storage, performance and scalability of servers, personalization and service differentiation for users. This article aims at characterizing and modeling the patterns of requests that reach a server of a locationbased social network. To do that, we use a dataset obtained from Apontador, a Brazilian system with characteristics similar to Foursquare and Gowalla, where users share information about their locations and can navigate on existent system locations. As results, we identified models that describe unique characteristics of the user sessions on this kind of system, patterns in which requests arrive on the server as well as the access profile of users in the system.
URI: http://www.repositorio.ufop.br/handle/123456789/8826
metadata.dc.identifier.uri2: https://link.springer.com/article/10.1007/s13278-014-0209-1
ISSN: 18695469
Appears in Collections:DECSI - Artigos publicados em periódicos

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