Perfil de Uso de Aplicativos Móveis: Caracterização e Aplicações
Resumo
O grande volume de dados gerados pelos avanços das tecnologias móveis tem feito com que os provedores de serviço se interessem cada vez mais pela sua coleta e análise. Neste trabalho, um conjunto de dados real e de larga escala relacionado ao uso detalhado de aplicativos móveis é investigado pela primeira vez com o objetivo de se identificar padrões de acesso, de tráfego de dados, de tempo de uso e de transição entre serviços. Além da caracterização, este trabalho contribui com a comunidade científica em outras duas frentes. Primeiramente, foi proposto e validado um modelo para geração de dados sintéticos, que poderá ser adotado por outros pesquisadores. Além disso, foi possível avaliar as métricas relevantes para a predição do próximo aplicativo a ser utilizado, o que permite a prévia preparação de algum aplicativo para reduzir o tempo de espera dos usuários, aumentando a sua satisfação.
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Yang, J., Qiao, Y., Zhang, X., He, H., Liu, F., e Cheng, G. (2015). Characterizing user IEEE Transactions on Emerging Topics in Computing, behavior in mobile internet. 3(1):95–106.
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Anderson, J. W., Kennedy, K., Ngo, L. B., Luckow, A., e Apon, A. W. (2014). Synthetic data generation for the internet of things. In Big Data (Big Data), 2014 IEEE International Conference on, pages 171–176. IEEE.
Chittaranjan, G., Blom, J., e Gatica-Perez, D. (2013). Mining large-scale smartphone data for personality studies. Personal and Ubiquitous Computing, 17(3):433–450.
de Almeida Oliveira, R., Brandão, W. C., e Marques-Neto, H. T. (2015). Characterizing user behavior on a mobile sms-based chat service. In Computer Networks and Distributed Systems (SBRC), 2015 XXXIII Brazilian Symposium on, pages 130–139. IEEE.
Do, T. M. T., Blom, J., e Gatica-Perez, D. (2011). Smartphone usage in the wild: a largescale analysis of applications and context. In Proceedings of the 13th international conference on multimodal interfaces, pages 353–360. ACM.
Fernandez, M., Scharl, A., Bontcheva, K., e Alani, H. (2014). User prole modelling in online communities. In Proceedings of the Third International Conference on Semantic Web Collaborative Spaces-Volume 1275, pages 1–15. CEUR-WS. org.
Fiadino, P., Casas, P., Schiavone, M., e D’Alconzo, A. (2015). Online social networks In IFIP anatomy: On the analysis of facebook and whatsapp in cellular networks. Networking Conference (IFIP Networking), 2015, pages 1–9. IEEE.
Hong, L., Zheng, Y., Yung, D., Shang, J., e Zou, L. (2015). Detecting urban black holes based on human mobility data. In Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems, page 35. ACM.
Huang, K., Zhang, C., Ma, X., e Chen, G. (2012). Predicting mobile application usage using contextual information. In Proceedings of the 2012 ACM Conference on Ubiquitous Computing, pages 1059–1065. ACM.
Iqbal, M. S., Choudhury, C. F., Wang, P., e González, M. C. (2014). Development of origin–destination matrices using mobile phone call data. Transportation Research Part C: Emerging Technologies, 40:63–74.
Jain, R. (1991). The art of computer systems performance analysis techniques for experimental design, measurement, simulation, and modeling. Wiley professional computing. Wiley.
Jin, L., Chen, Y., Wang, T., Hui, P., e Vasilakos, A. V. (2013). Understanding user behavior in online social networks: A survey. IEEE Communications Magazine, 51(9):144–150.
Laurila, J. K., Gatica-Perez, D., Aad, I., Bornet, O., Do, T.-M.-T., Dousse, O., Eberle, J., Miettinen, M., et al. (2012). The mobile data challenge: Big data for mobile computing research. In Pervasive Computing, number EPFL-CONF-192489.
Leo, Y., Busson, A., Sarraute, C., e Fleury, E. (2016). Call detail records to characterize usages and mobility events of phone users. Computer Communications, 95:43–53.
Li, H., Lu, X., Liu, X., Xie, T., Bian, K., Lin, F. X., Mei, Q., e Feng, F. (2015). Characterizing smartphone usage patterns from millions of android users. In Proceedings of the 2015 ACM Conference on Internet Measurement Conference, pages 459–472. ACM.
Lim, K.-W., Secci, S., Tabourier, L., e Tebbani, B. (2016). Characterizing and predicting mobile application usage. Computer Communications, 95:82–94.
Malmi, E. e Weber, I. (2016). You are what apps you use: Demographic prediction based on user’s apps. arXiv preprint arXiv:1603.00059.
Pavan, M., Mizzaro, S., e Scagnetto, I. (2015). Mining movement data to extract personal points of interest: A feature based approach.
Seneviratne, S., Seneviratne, A., Mohapatra, P., e Mahanti, A. (2014). Predicting user traits from a snapshot of apps installed on a smartphone. ACM SIGMOBILE Mobile Computing and Communications Review, 18(2):1–8.
Shin, C., Hong, J.-H., e Dey, A. K. (2012). Understanding and prediction of mobile application usage for smart phones. In Proceedings of the 2012 ACM Conference on Ubiquitous Computing, pages 173–182. ACM.
Srinivasan, V., Moghaddam, S., Mukherji, A., Rachuri, K. K., Xu, C., e Tapia, E. M. (2014). Mobileminer: Mining your frequent patterns on your phone. In Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing, pages 389–400. ACM.
Wang, H., Xu, F., Li, Y., Zhang, P., e Jin, D. (2015). Understanding mobile trafc patterns of large scale cellular towers in urban environment. In Proceedings of the 2015 ACM Conference on Internet Measurement Conference, pages 225–238. ACM.
Wang, L., Zhan, J., Luo, C., Zhu, Y., Yang, Q., He, Y., Gao, W., Jia, Z., Shi, Y., Zhang, S., et al. (2014). Bigdatabench: A big data benchmark suite from internet services. In High Performance Computer Architecture (HPCA), 2014 IEEE 20th International Symposium on, pages 488–499. IEEE.
Xavier, F. H. Z., Silveira, L. M., Almeida, J. M. d., Ziviani, A., Malab, C. H. S., e Marques-Neto, H. T. (2012). Analyzing the workload dynamics of a mobile phone network in large scale events. In Proceedings of the rst workshop on Urban networking, pages 37–42. ACM.
Xu, R., Frey, R. M., Vuckovac, D., e Ilic, A. (2015). Towards understanding the impact of personality traits on mobile app adoption-a scalable approach. In 23rd European Conference on Information Systems.
Yang, J., Qiao, Y., Zhang, X., He, H., Liu, F., e Cheng, G. (2015). Characterizing user IEEE Transactions on Emerging Topics in Computing, behavior in mobile internet. 3(1):95–106.
Zou, X., Zhang, W., Li, S., e Pan, G. (2013). Prophet: What app you wish to use next. In Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication, pages 167–170. ACM.
Publicado
10/05/2018
Como Citar
DOMINGUES, Augusto C. S. A.; SILVA, Fabrício A.; SILVA, Thais Regina M. B.; LOUREIRO, Antonio A. F..
Perfil de Uso de Aplicativos Móveis: Caracterização e Aplicações. In: SIMPÓSIO BRASILEIRO DE REDES DE COMPUTADORES E SISTEMAS DISTRIBUÍDOS (SBRC), 36. , 2018, Campos do Jordão.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2018
.
p. 617-630.
ISSN 2177-9384.
DOI: https://doi.org/10.5753/sbrc.2018.2446.
