Multi-Temporal Aspects on Contextual Variability Modeling
Resumo
O tempo é um dos aspectos mais relevantes quando modelamos a variabilidade contextual. A perspectiva temporal orienta a modelagem de sistemas sensíveis ao contexto. Apesar da percepção natural e consensual do tempo, a modelagem integrada de suas dimensões para o desenvolvimento de software sensível ao contexto é um tema recente de estudo. O Passado é armazenado em Contextos Históricos, o Presente é modelado através do Gerenciamento de Perfis e o Futuro é antecipado usando a Previsão de Contexto. Este artigo discute a modelagem dessas três dimensões nos sistemas sensíveis ao contexto, indica desafios para cada dimensão e propõe uma arquitetura de sistema para gerenciar a variabilidade contextual em sistemas multitemporais. Acredito que este texto possa ser um artigo seminal para estimular e orientar futuras pesquisas sobre aspectos temporais de ambientes computacionais.
Palavras-chave:
Context awareness, Context History, Profile Management, Context Prediction
Referências
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Burbey, I. and Martin, T. L. (2012) “A Survey on Predicting Personal Mobility”. International Journal of Pervasive Computing and Communications. 8(1), p.5–22. http://dx.doi.org/10.1108/17427371211221063
Baur, D., Seiffert, F., Sedlmair, M. and Boring, S. (2010) “The streams of our lives: Visualizing listening histories in context”. IEEE Transactions on Visualization and Computer Graphics. 16(6), p.1119–1128. http://dx.doi.org/10.1109/TVCG.2010.206
Ciaramella, A., Cimino, M. G. C. A., Lazzerini, B. and Marcelloni, F. (2010) “Using context history to personalize a resource recommender via a genetic algorithm”, in Proceedings of the 10th International Conference on Intelligent Systems Design and Applications. Cairo, Egypt, p.965–970. http://dx.doi.org/10.1109/ISDA.2010.5687064
Dey, A., Salber, D. and Abowd, G. (2001). “A conceptual framework and a toolkit for supporting the rapid prototyping of context-aware application”, Human-Computer Interaction, 16(2), p. 97–166. http://dx.doi.org/10.1207/S15327051HCI16234_02
Doherty, A. R., Caprani, N., Conaire, C. O., Kalnikaite, V., Gurrin, V. C., Smeaton, A. F. and O’Connor, N. E. (2011) “Passively recognising human activities through lifelogging”. Computers in Human Behavior. 27(5), p.1948–1958. http://dx.doi.org/10.1016/j.chb.2011.05.002
Fischer, G. (2011) “User modeling in human–computer interaction. User Modeling and User-Adapted Interaction”. 11(1), p.65–86. http://dx.doi.org/10.1023/A:1011145532042
Hong, J., Suh, E.-H., Kim, J. and Kim, S. (2009) “Context-aware system for proactive personalized service based on context history”. Expert Systems with Applications. 36(4), p.7448–7457. http://dx.doi.org/10.1016/j.eswa.2008.09.002
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Rosa, J., Barbosa, J. and Barcelos, G. (2016) “ORACON: An Adaptive Model For Context Prediction”, Expert Systems with Applications, 45(1), p.56–70. http://dx.doi.org/10.1016/j.eswa.2015.09.016
Satyanarayanan, M. (2001) “Pervasive computing: vision and challenges”, IEEE Personal Communications, 8(4), p. 10–17. http://dx.doi.org/10.1109/98.943998
Sellen, A. J. and Whittaker, S. (2010) “Beyond total capture: a constructive critique of lifelogging”, Communications of the ACM. 53(5), p.70–77. http://dx.doi.org/10.1145/1735223.1735243
Silva, J., Rosa, J., Barbosa, J. Barbosa, D. and Palazzo, L. (2010) “Content Distribution in Trail-aware Environments”, Journal of the Brazilian Computer Society”, 16(3), p.163–176. http://link.springer.com/article/10.1007/s13173-010-0015-1
Sigg, S., Haseloff, S., and David, K. (2010). “An alignment approach for context prediction tasks in ubicomp environments”. IEEE Pervasive Computing. 9(4), p.90– 97. http://dx.doi.org/10.1109/MPRV.2010.23
Sigg, S. et al. (2011) “Investigation of context prediction accuracy for different context abstraction levels”. IEEE Transactions on Mobile Computing. 11(6), p.1047–1059. http://dx.doi.org/10.1109/TMC.2011.170
Smith, S. (2008) “Who controls the past controls the future - life annotation in principle and practice”, University of Southampton, School of Electronics and Computer Science, PhD Thesis. http://expertise.ecs.soton.ac.uk/16554/1/thesis.pdf
Souza, R., Lopes, J., Geyer, C., João, L., Cardozo, A., Yamin, A., Gadotti, G. and Barbosa, J. (2019). “Continuous Monitoring Seed Testing Equipaments Using Internet of Things”, Computers and Electronics in Agriculture, 158, p.122-132. http://dx.doi.org/10.1016/j.compag.2019.01.024
Vianna, H. and Barbosa, J. (2014) “A Model for Ubiquitous Care of Noncommunicable Diseases”, IEEE Journal of Biomedical and Health Informatics, 18(5), p. 1597–1606. http://dx.doi.org/10.1109/JBHI.2013.2292860
Vianna, H. and Barbosa, J. (2017) “In the Pursuit of Hygge Software”, IEEE Software, 34, p. 48-52. https://doi.org/10.1109/MS.2017.4121208
Vianna, H. and Barbosa, J. (2019) “A scalable model for building context-aware applications for noncommunicable diseases prevention”, Information Processing Letters, p.1-10. http://dx.doi.org/10.1016/j.ipl.2019.03.010
Wagner, A., Barbosa, J. and Barbosa, D. (2014) “A Model for Profile Management Applied to Ubiquitous Learning Environments”, Expert Systems with Applications, 41(4), p. 2023–2034. http://dx.doi.org/10.1016/j.eswa.2013.08.098
Weiser, M. (1991) “The Computer for the 21st Century”, Scientific American, 265(3), p. 94–104. http://dx.doi.org/10.1145/329124.329126.
Wiedemann, T., Barbosa, J., Rigo, S. and Barbosa, D. (2016) “RecSim: A Model for Learning Objects Recommendation using Similarity of Sessions”, Journal of Universal Computer Science, 22(8), p.1175–1200. http://www.jucs.org/jucs_22_8/recsim_a_model_for
Bala, A. and Chana, I. (2015) “Intelligent failure prediction models for scientific workflows”. Expert Systems with Applications. 42(3), p.980–989. http://dx.doi.org/10.1016/j.eswa.2014.09.014
Ballings, M., Van den Poel, D., Hespeels, N. and Gryp, R. (2015). “Evaluating multiple classifiers for stock price direction prediction”. Expert Systems with Applications. 42(20), p.7046–7056. http://dx.doi.org/10.1016/j.eswa.2015.05.013
Barbosa, J., Martins, C., Franco, L. and Barbosa, D. (2016) “TrailTrade: a model for trail-aware commerce support”, Computers in Industry, 80, p.43–53. http://dx.doi.org/10.1016/j.compind.2016.04.006
Barbosa, J., Tavares, J., Cardoso, I., Mota, B. and Martini, B. (2018). “TrailCare: na Indoor and Outdoor Context-aware System to Assit Wheelchair Users”. Internacional Journal of Human-Computer Studies. 116, p.1–14. https://doi.org/10.1016/j.ijhcs.2018.04.001
Burbey, I. and Martin, T. L. (2012) “A Survey on Predicting Personal Mobility”. International Journal of Pervasive Computing and Communications. 8(1), p.5–22. http://dx.doi.org/10.1108/17427371211221063
Baur, D., Seiffert, F., Sedlmair, M. and Boring, S. (2010) “The streams of our lives: Visualizing listening histories in context”. IEEE Transactions on Visualization and Computer Graphics. 16(6), p.1119–1128. http://dx.doi.org/10.1109/TVCG.2010.206
Ciaramella, A., Cimino, M. G. C. A., Lazzerini, B. and Marcelloni, F. (2010) “Using context history to personalize a resource recommender via a genetic algorithm”, in Proceedings of the 10th International Conference on Intelligent Systems Design and Applications. Cairo, Egypt, p.965–970. http://dx.doi.org/10.1109/ISDA.2010.5687064
Dey, A., Salber, D. and Abowd, G. (2001). “A conceptual framework and a toolkit for supporting the rapid prototyping of context-aware application”, Human-Computer Interaction, 16(2), p. 97–166. http://dx.doi.org/10.1207/S15327051HCI16234_02
Doherty, A. R., Caprani, N., Conaire, C. O., Kalnikaite, V., Gurrin, V. C., Smeaton, A. F. and O’Connor, N. E. (2011) “Passively recognising human activities through lifelogging”. Computers in Human Behavior. 27(5), p.1948–1958. http://dx.doi.org/10.1016/j.chb.2011.05.002
Fischer, G. (2011) “User modeling in human–computer interaction. User Modeling and User-Adapted Interaction”. 11(1), p.65–86. http://dx.doi.org/10.1023/A:1011145532042
Hong, J., Suh, E.-H., Kim, J. and Kim, S. (2009) “Context-aware system for proactive personalized service based on context history”. Expert Systems with Applications. 36(4), p.7448–7457. http://dx.doi.org/10.1016/j.eswa.2008.09.002
Konig, I., Voigtmann, C., Klein, B. N. and David, K. (2011) “Enhancing alignment based context prediction by using multiple context sources: experiment and analysis”, in Proceedings of the 7th International and Interdisciplinary Conference on Modeling and Using Context, Karlsruhe, Germany, p.159-172. http://dx.doi.org/10.1007/978-3-642-24279-3_18
Larentis, A., Barbosa, J., Barbosa, D., Silva, C. and Barbosa, J. (2019) “Applied Computing to Education on Noncommunicable Chronic Diseases: A Systematic Mapping Study”, Telemedicine and e-Health, 1, p.1-10, 2019. https://doi.org/10.1016/j.ipl.2019.03.010
Lee, S. and Lee, K. C. (2012) “Context-prediction performance by a dynamic Bayesian network: Emphasis on location prediction in ubiquitous decision support environment”. Expert Systems with Applications. 39(5), p.4908–4914. http://dx.doi.org/10.1016/j.eswa.2011.10.026
Pejovic, V. and Musolesi, M. (2015) “Anticipatory Mobile Computing: A Survey of the State of the Art and Research Challenges”. ACM Computing Surveys. 47(3), article n. 47. http://dx.doi.org/10.1145/2693843
Rigo, S., Cambruzzi, W. and Barbosa, J. (2015) “Dropout Prediction and Reduction in Distance Education Courses with the Learning Analytics Multitrail Approach”, Journal of Universal Computer Science, 21(1), p.23–47. http://dx.doi.org/10.3217/jucs-021-01-0023
Rosa, J., Barbosa, J., Kich, M. and Brito, L. (2015) “A Multi-Temporal Context-aware System for Competences Management”, International Journal of Artificial Intelligence in Education,25(4), p.455–492. http://dx.doi.org/10.1007/s40593-015-0047-y
Rosa, J., Barbosa, J. and Barcelos, G. (2016) “ORACON: An Adaptive Model For Context Prediction”, Expert Systems with Applications, 45(1), p.56–70. http://dx.doi.org/10.1016/j.eswa.2015.09.016
Satyanarayanan, M. (2001) “Pervasive computing: vision and challenges”, IEEE Personal Communications, 8(4), p. 10–17. http://dx.doi.org/10.1109/98.943998
Sellen, A. J. and Whittaker, S. (2010) “Beyond total capture: a constructive critique of lifelogging”, Communications of the ACM. 53(5), p.70–77. http://dx.doi.org/10.1145/1735223.1735243
Silva, J., Rosa, J., Barbosa, J. Barbosa, D. and Palazzo, L. (2010) “Content Distribution in Trail-aware Environments”, Journal of the Brazilian Computer Society”, 16(3), p.163–176. http://link.springer.com/article/10.1007/s13173-010-0015-1
Sigg, S., Haseloff, S., and David, K. (2010). “An alignment approach for context prediction tasks in ubicomp environments”. IEEE Pervasive Computing. 9(4), p.90– 97. http://dx.doi.org/10.1109/MPRV.2010.23
Sigg, S. et al. (2011) “Investigation of context prediction accuracy for different context abstraction levels”. IEEE Transactions on Mobile Computing. 11(6), p.1047–1059. http://dx.doi.org/10.1109/TMC.2011.170
Smith, S. (2008) “Who controls the past controls the future - life annotation in principle and practice”, University of Southampton, School of Electronics and Computer Science, PhD Thesis. http://expertise.ecs.soton.ac.uk/16554/1/thesis.pdf
Souza, R., Lopes, J., Geyer, C., João, L., Cardozo, A., Yamin, A., Gadotti, G. and Barbosa, J. (2019). “Continuous Monitoring Seed Testing Equipaments Using Internet of Things”, Computers and Electronics in Agriculture, 158, p.122-132. http://dx.doi.org/10.1016/j.compag.2019.01.024
Vianna, H. and Barbosa, J. (2014) “A Model for Ubiquitous Care of Noncommunicable Diseases”, IEEE Journal of Biomedical and Health Informatics, 18(5), p. 1597–1606. http://dx.doi.org/10.1109/JBHI.2013.2292860
Vianna, H. and Barbosa, J. (2017) “In the Pursuit of Hygge Software”, IEEE Software, 34, p. 48-52. https://doi.org/10.1109/MS.2017.4121208
Vianna, H. and Barbosa, J. (2019) “A scalable model for building context-aware applications for noncommunicable diseases prevention”, Information Processing Letters, p.1-10. http://dx.doi.org/10.1016/j.ipl.2019.03.010
Wagner, A., Barbosa, J. and Barbosa, D. (2014) “A Model for Profile Management Applied to Ubiquitous Learning Environments”, Expert Systems with Applications, 41(4), p. 2023–2034. http://dx.doi.org/10.1016/j.eswa.2013.08.098
Weiser, M. (1991) “The Computer for the 21st Century”, Scientific American, 265(3), p. 94–104. http://dx.doi.org/10.1145/329124.329126.
Wiedemann, T., Barbosa, J., Rigo, S. and Barbosa, D. (2016) “RecSim: A Model for Learning Objects Recommendation using Similarity of Sessions”, Journal of Universal Computer Science, 22(8), p.1175–1200. http://www.jucs.org/jucs_22_8/recsim_a_model_for
Publicado
12/07/2019
Como Citar
BARBOSA, Jorge .
Multi-Temporal Aspects on Contextual Variability Modeling. In: SIMPÓSIO BRASILEIRO DE COMPUTAÇÃO UBÍQUA E PERVASIVA (SBCUP), 11. , 2019, Belém.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2019
.
ISSN 2595-6183.
DOI: https://doi.org/10.5753/sbcup.2019.6590.
