International Journal of Advanced Culture Technology

The International Promotion Agency of Culture Technology (국제문화기술진흥원)
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Utilization and Analysis of Big-data

  • Received : 2019.10.02
  • Accepted : 2019.11.22
  • Published : 2019.12.31
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Abstract

This study reviews the analysis and characteristics of databases from big data and then establishes representational strategy. Thus, analysis has continued for a long time in the quantity and quality of data, and there are changes in the location of data in the social sciences, past trends and the emergence of big data. The introduction of big data is presented as a prototype of new social science and is a useful practical example that empirically shows the need, basis, and direction of analysis through trend prediction services. Big data provides a future perspective as an important foundation for social change within the framework of basic social sciences.

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References

  1. Brutlag, J. Speed Matters. Google. Research Blog. June 23, 2009; http://googleresearch.blogspot./com/2009/06/speed-matters.html
  2. Gray, W. D., and Boehm-Davis, D. A. Milliseconds matter: An introduction to microstrategies and to their use in describing and predicting interactive behavior. Journal of Experimental Psychology:Applied 6, 4 (2000),322-335. https://doi.org/10.1037/1076-898X.6.4.322
  3. Dasu, T., and Johnson, T. Exploratory Data Mining and Data Cleaning. John Wiley & Sons, Inc., New York, 2003.
  4. Raman, V., and Hellerstein, J. M. Potter's wheel: An interactive data cleaning system. In Proceedings of the 27th International Conference on Very Large Data Bases (Rome, Sept. 11-14). Morgan Kaufmann, San Francisco, 2001, 381-390.
  5. Cypher, A. Watch What I Do: Programming by Demonstration. MIT Press, Cambridge, MA, 1993.
  6. Gulwani, S. Automating string processing in spreadsheets using input-output examples. In Proceedings of the 38th annual ACM SIGPLANSIGACT Symposium on Principles of Programming Languages (Austin, Jan. 26-28). ACM Press, New York, 2011, 317-330.
  7. Kandel, S., Paepcke, S., Hellerstein, J. M., and Heer, J. Wrangler: Interactive visual specification of data transformation scripts. In Proceedings of the 2011Annual Conference of Human Factors in Computing Systems (Vancouver, May 7-12). ACM Press, New York, 2011, 3363-3372.
  8. Horvitz, E. Principles of mixed-initiative user interfaces. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Pittsburgh, May 15-20). ACM Press, New York, 1999, 159-166.
  9. Kang, H., Getoor, L., Shneiderman, B., Bilgic, M., and Licamele, L. Interactive entity resolution in relational data: A visual analytic tool and its evaluation. IEEE Transactions on Visualization & Computer Graphics 14, 5 (2008),999-1014. https://doi.org/10.1109/TVCG.2008.55
  10. Robertson, G. G., Czerwinski, M. P., and Churchill, J. E. Visualization of mappings between schemas. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Portland, April 2-7). ACM Press, New York, 2005, 431-439.