Abstract
Data has increased in a large scale in various fields leading to the coin of the term Big Data. Big data is mainly used to describe enormous datasets that typically includes masses of unstructured data that may need real-time analysis. As human behaviour and personality can be captured through human-computer interaction a massive opportunity opens for providing wellness services. Through the use of interaction data, behavioral biometrics can be obtained. The usage of biometrics has increased due to several factors such as the rise of power and availability of computational power. One of the challenges in this kind of approaches has to do with handling the acquired data. The growing volumes, variety and velocity brings challenges in the tasks of pre-processing, storage and providing analytics. In this sense, the problem can be framed as a Big Data problem. In this work it is intended to provide an architecture that accommodates the data pipeline of data generated by human-computer interaction, providing real time data analytics on behavioral biometrics.
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References
Bertino, E., Bernstein, P., Agrawal, D., Davidson, S., Dayal, U., Franklin, M., Gehrke, J., Haas, L., Halevy, A., Han, J., et al.: Challenges and opportunities with big data (2011)
Gartner: What is big data? http://www.gartner.com/it-glossary/big-data (accessed: 2015-12-20)
Mayer-Schönberger, V., Cukier, K.: Big Data: A Revolution that will Transform How We Live, Work, and Think. Houghton Mifflin Harcourt (2013)
Gantz, J., Reinsel, D.: Extracting value from chaos. IDC iview 1142, 9–10 (2011)
Pimenta, A., Carneiro, D., Novais, P., Neves, J.: Monitoring mental fatigue through the analysis of keyboard and mouse interaction patterns. In: Hybrid Artificial Intelligent Systems, pp. 222–231. Springer (2013)
Carneiro, D., Castillo, J.C., Novais, P., Fernández-Caballero, A., Neves, J.: Multimodal behavioral analysis for non-invasive stress detection. Expert Systems with Applications 39(18), 13376–13389 (2012)
Kejariwal, A., Kulkarni, S., Ramasamy, K.: Real time analytics: algorithms and systems. Proceedings of the VLDB Endowment 8(12), 2040–2041 (2015)
Chaudhuri, S., Dayal, U.: An overview of data warehousing and olap technology. ACM Sigmod record 26(1), 65–74 (1997)
Khazaei, H., Fokaefs, M., Zareian, S., Beigi-Mohammadi, N., Ramprasad, B., Shtern, M., Gaikwad, P., Litoiu, M.: How do i choose the right nosql solution? a comprehensive theoretical and experimental survey. Submitted to Journal of Big Data and Information Analytics (BDIA) (2015)
Stonebraker, M.: Sql databases v. nosql databases. Communications of the ACM 53(4), 10–11 (2010)
Pritchett, D.: Base: An acid alternative. Queue 6(3), 48–55 (2008)
Cattell, R.: Scalable sql and nosql data stores. ACM SIGMOD Record 39(4), 12–27 (2011)
Chang, F., Dean, J., Ghemawat, S., Hsieh, W.C., Wallach, D.A., Burrows, M., Chandra, T., Fikes, A., Gruber, R.E.: Bigtable: A distributed storage system for structured data. ACM Transactions on Computer Systems (TOCS) 26(2) (2008)
Lourenço, J.R., Cabral, B., Carreiro, P., Vieira, M., Bernardino, J.: Choosing the right nosql database for the job: a quality attribute evaluation. Journal of Big Data 2(1), 1–26 (2015)
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Araújo, D., Pimenta, A., Carneiro, D., Novais, P. (2016). Providing Wellness Services Using Real Time Analytics. In: Lindgren, H., et al. Ambient Intelligence- Software and Applications – 7th International Symposium on Ambient Intelligence (ISAmI 2016). ISAmI 2016. Advances in Intelligent Systems and Computing, vol 476. Springer, Cham. https://doi.org/10.1007/978-3-319-40114-0_19
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DOI: https://doi.org/10.1007/978-3-319-40114-0_19
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