Abstract
The emergence of Big Data due to spread of the 21st century digital economy can provide a clue to the solution of the problems in our society and economy. Especially, one of the areas where Big Data can be highly useful is the medical and health industry. The development of IT is leading a new era of innovation in the field of medicine as well. Nevertheless, the level of Big Data application in this field is still low as the unstructured data included in Big Data are difficult to search and gather their statistics so that there have been some limits in utilizing it widely. The merit of Big Data is that it can present a variety of meaningful results depending on the data collection and analysis methods. Thus, in this study, a Big Data has been created for text mining by using the crawling technique and analyzed with R Studio, followed by its visualization to devise an individualized health plan with different perspectives.
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References
Kim, H.-B., Bae, G.-P., Huh, J.-H.: A keyword-based big data analysis for individualized health activity: focusing on methodological approach. Spring Conf. Kips 24(1), 540–543 (2017)
Ngu, H.C.V., Huh, J.-H.: B+-tree construction on massive data with Hadoop. Cluster Comput. 1–11 (2017). Springer, US
Battré, D., Hovestadt, M., Lohrmann, B., Stanik, A., Warneke, D.: Detecting bottlenecks in parallel dag-based data flow programs. In: 2010 3rd Workshop on Many-Task Computing on Grids and Supercomputers, pp. 1–10 (2010)
Behm, A., Borkar, V.R., Carey, M.J., et al.: Asterix: towards a scalable, semistructured data platform for evolving-world models. Distrib. Parallel Databases 29(3), 185–216 (2011)
Beyer, K.S., et al.: Jaql: a scripting language for large scale semistructured data analysis. Proc. VLDB Endowment 4(12), 1272–1283 (2011)
Boden, C., et al.: Large-scale social media analytics on stratosphere. In: Proceedings of the 22nd International Conference on World Wide Web - WWW 2013 Companion, pp. 257–260. ACM (2013)
Borkar, V.R., et al.: Hyracks: a flexible and extensible foundation for data-intensive computing. In: IEEE 27th International Conference on Data Engineering, pp. 1151–1162 (2011)
Birkenmeier, G.F., Park, J.-K., Tariq Rizvi, S.: Ring hulls of semiprime homomorphic images, modules and comodules. Trends in Mathematics, pp. 101–111. Springer, Birkhäuser Verlag Basel, Switzerland (2008)
Birkenmeier, G.F., Park, J.-K., Tariq Rizvi, S.: Principally quasi-baer ring hulls, advances in ring theory. Trends in Mathematics, pp. 47–61. Springer, Birkhäuser Verlag Basel, Switzerland (2010)
Huh, J.-H., Kim, H.-B., Le, H.-S.: A keyword-based big data analysis for individualized health activity using keyword analysis technique: a methodological approach using national health data of the Republic of Korea. In: SCECR 2017, Ho Chi Minh City, p. 1 (2017)
Acknowledgments
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2017R1C1B5077157).
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Lee, S., Le, HS., Huh, JH. (2018). A Keyword-Based Big Data Analysis for Individualized Health Activity Using Keyword Analysis Technique: A Methodological Approach Using National Health Data. In: Park, J., Loia, V., Yi, G., Sung, Y. (eds) Advances in Computer Science and Ubiquitous Computing. CUTE CSA 2017 2017. Lecture Notes in Electrical Engineering, vol 474. Springer, Singapore. https://doi.org/10.1007/978-981-10-7605-3_197
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DOI: https://doi.org/10.1007/978-981-10-7605-3_197
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