Seleção de Anúncios Pervasivos Baseada na Segmentação de Mercado e Comportamento do Consumidor
Resumo
Neste trabalho propõe-se um método de seleção de anúncios pervasivos, que não demanda interação e feedback dos consumidores, baseado em segmentação de mercado e no comportamento do consumidor. Foi realizado um experimento no qual o método foi comparado a outras abordagens de mesmo propósito, com a participação de 112 pessoas. Os resultados mostram a eficiência da abordagem no processo de recomendação de anúncios.Referências
Burke, R. (2002). Hybrid recommender systems: Survey and experiments. User modeling and user-adapted interaction, 12(4):331–370.
Conti, M., Das, S. K., Bisdikian, C., Kumar, M., Ni, L. M., Passarella, A., Roussos, G., Tröster, G., Tsudik, G., and Zambonelli, F. (2012). Looking ahead in pervasive computing: Challenges and opportunities in the era of cyber–physical convergence. Pervasive and Mobile Computing, 8(1):2–21.
Di Ferdinando, A., Rosi, A., Lent, R., Manzalini, A., and Zambonelli, F. (2009). Myads: A system for adaptive pervasive advertisements. Pervasive and Mobile Computing, 5(5):385–401.
Froehlich, J., Chen, M., Smith, I., and Potter, F. (2006). Voting with your feet: An investigative study of the relationship between place visit behavior and preference. UbiComp 2006: Ubiquitous Computing, pages 333–350.
Gunawardana, A. and Shani, G. (2009). A survey of accuracy evaluation metrics of recommendation tasks. The Journal of Machine Learning Research, 10:2935–2962.
Ihlström Eriksson, C., Akesson, M., and Hakeröd, J. (2007). Advertising in ubiquitous media environments. In Proceedings of the 30th Information Systems Research Seminar in Scandinavia, IRIS 30. Department of Computer Sciences, University of Tampere, Finland.
Jain, R. (2008). The art of computer systems performance analysis. Wiley-India.
Kasabov, N. (1996). Foundations of neural networks, fuzzy systems, and knowledge engineering. The MIT Press.
Kostakos, V. and Ojala, T. (2013). Public displays invade urban spaces. Pervasive Computing, IEEE, 12(1):8–13.
Krumm, J. (2011). Ubiquitous advertising: The killer application for the 21st century. Pervasive Computing, IEEE, 10(1):66–73.
McCarthy, J., Costa, T., and Liongosari, E. (2001). Unicast, outcast & groupcast: Three steps toward ubiquitous, peripheral displays. In Ubicomp 2001: Ubiquitous Computing, pages 332–345. Springer.
Müller, J., Alt, F., and Michelis, D. (2011). Pervasive Advertising. Springer.
Müller, J. and Krüger, A. (2009). Mobidic: Context adaptive digital signage with coupons. Ambient Intelligence, pages 24–33.
Phillip, K. and Keller, K. (2008). Marketing Management. Prentice Hall, 13th edition.
Real, R. and Vargas, J. M. (1996). The probabilistic basis of jaccard’s index of similarity. Systematic Biology, 45(3):380–385.
Ribeiro, F. (2010). Escalonamento autónomo e sensível ao contexto para ecrãs públicos. PhD thesis, Universidade do minho Portugal.
Shari, M., Payne, T., and David, E. (2006). Public display advertising based on bluetooth device presence. In Mobile Interaction with the Real World (MIRW 2006) in conjunction with the 8th International Conference on Human Computer Interaction with Mobile Devices and Services.
Strohbach, M. and Martin, M. (2011). Towards a platform for pervasive display applications in retail environments. Pervasive Computing, IEEE, (99).
Su, X. and Khoshgoftaar, T. M. (2009). A survey of collaborative ltering techniques. Advances in Articial Intelligence, 2009:4.
Yu, K., Yu, C., Yeh, B., Hsu, C., and Hsieh, H. (2010). The design and implementation of a mobile location-aware digital signage system. In Mobile Ad-hoc and Sensor Networks (MSN), pages 235–238. IEEE.
Conti, M., Das, S. K., Bisdikian, C., Kumar, M., Ni, L. M., Passarella, A., Roussos, G., Tröster, G., Tsudik, G., and Zambonelli, F. (2012). Looking ahead in pervasive computing: Challenges and opportunities in the era of cyber–physical convergence. Pervasive and Mobile Computing, 8(1):2–21.
Di Ferdinando, A., Rosi, A., Lent, R., Manzalini, A., and Zambonelli, F. (2009). Myads: A system for adaptive pervasive advertisements. Pervasive and Mobile Computing, 5(5):385–401.
Froehlich, J., Chen, M., Smith, I., and Potter, F. (2006). Voting with your feet: An investigative study of the relationship between place visit behavior and preference. UbiComp 2006: Ubiquitous Computing, pages 333–350.
Gunawardana, A. and Shani, G. (2009). A survey of accuracy evaluation metrics of recommendation tasks. The Journal of Machine Learning Research, 10:2935–2962.
Ihlström Eriksson, C., Akesson, M., and Hakeröd, J. (2007). Advertising in ubiquitous media environments. In Proceedings of the 30th Information Systems Research Seminar in Scandinavia, IRIS 30. Department of Computer Sciences, University of Tampere, Finland.
Jain, R. (2008). The art of computer systems performance analysis. Wiley-India.
Kasabov, N. (1996). Foundations of neural networks, fuzzy systems, and knowledge engineering. The MIT Press.
Kostakos, V. and Ojala, T. (2013). Public displays invade urban spaces. Pervasive Computing, IEEE, 12(1):8–13.
Krumm, J. (2011). Ubiquitous advertising: The killer application for the 21st century. Pervasive Computing, IEEE, 10(1):66–73.
McCarthy, J., Costa, T., and Liongosari, E. (2001). Unicast, outcast & groupcast: Three steps toward ubiquitous, peripheral displays. In Ubicomp 2001: Ubiquitous Computing, pages 332–345. Springer.
Müller, J., Alt, F., and Michelis, D. (2011). Pervasive Advertising. Springer.
Müller, J. and Krüger, A. (2009). Mobidic: Context adaptive digital signage with coupons. Ambient Intelligence, pages 24–33.
Phillip, K. and Keller, K. (2008). Marketing Management. Prentice Hall, 13th edition.
Real, R. and Vargas, J. M. (1996). The probabilistic basis of jaccard’s index of similarity. Systematic Biology, 45(3):380–385.
Ribeiro, F. (2010). Escalonamento autónomo e sensível ao contexto para ecrãs públicos. PhD thesis, Universidade do minho Portugal.
Shari, M., Payne, T., and David, E. (2006). Public display advertising based on bluetooth device presence. In Mobile Interaction with the Real World (MIRW 2006) in conjunction with the 8th International Conference on Human Computer Interaction with Mobile Devices and Services.
Strohbach, M. and Martin, M. (2011). Towards a platform for pervasive display applications in retail environments. Pervasive Computing, IEEE, (99).
Su, X. and Khoshgoftaar, T. M. (2009). A survey of collaborative ltering techniques. Advances in Articial Intelligence, 2009:4.
Yu, K., Yu, C., Yeh, B., Hsu, C., and Hsieh, H. (2010). The design and implementation of a mobile location-aware digital signage system. In Mobile Ad-hoc and Sensor Networks (MSN), pages 235–238. IEEE.
Publicado
23/07/2013
Como Citar
SOARES, Leonardo; ALMEIDA, Hyggo; PERKUSICH, Angelo; BUBLITZ, Fred; ROSNER, Marco.
Seleção de Anúncios Pervasivos Baseada na Segmentação de Mercado e Comportamento do Consumidor. In: SIMPÓSIO BRASILEIRO DE COMPUTAÇÃO UBÍQUA E PERVASIVA (SBCUP), 5. , 2013, Maceió.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2013
.
p. 1962-1971.
ISSN 2595-6183.
