International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies

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:: International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies

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ISSN 2228-9860
eISSN 1906-9642
CODEN: ITJEA8


FEATURE PEER-REVIEWED ARTICLE

Vol.12(5) (2021)

References

  1. Brock, V., & Khan, H. U. (2017). Big data analytics: does organizational factor matters impact technology acceptance?. Journal of Big Data, 4(1), 1-28. DOI 10.1186/s40537-017-0081-8
  2. Bughin, J. (2016). Big data, Big bang?. Journal of Big Data, 3(1), 1-14.
  3. Dinh, L. T. N., Karmakar, G., & Kamruzzaman, J. (2020). A survey on context awareness in big data analytics for business applications. Knowledge and Information Systems, 62(9), 3387-3415.
  4. Banu, N. S., & Swamy, S. (2016). Prediction of heart disease at early stage using data mining and big data analytics: A survey. In 2016 International Conference on Electrical, Electronics, Communication, Computer and Optimization Techniques (ICEECCOT) (pp. 256-261). IEEE.
  5. Wang, L., & Alexander, C. A. (2015). Big data in medical applications and health care. American Medical Journal, 6(1), 1-8.
  6. Palit, I., & Reddy, C. K. (2011). Scalable and parallel boosting with mapreduce. IEEE Transactions on Knowledge and Data Engineering, 24(10), 1904-1916.
  7. Sahoo, P. K., Mohapatra, S. K., & Wu, S. L. (2016). Analyzing healthcare big data with prediction for future health condition. IEEE Access, 4, 9786-9799.
  8. Becker, D., King, T. D., & McMullen, B. (2015). Big data, big data quality problem. In 2015 IEEE International Conference on Big Data (Big Data) (pp. 2644-2653). IEEE.
  9. Aslam, M. A., & Abdullah, A. (2015). A Methodology and a Tool to Prepare Agro-Meteorological Maps as a Source of Big Data. In 2015 IEEE International Conference on Multimedia Big Data (pp. 208-211). IEEE.
  10. Uddin, M. F., & Gupta, N. (2014). Seven V's of Big Data understanding Big Data to extract value. In Proceedings of the 2014 zone 1 conference of the American Society for Engineering Education (pp. 1-5). IEEE.
  11. Bilalli, B., Abell?, A., Aluja-Banet, T., & Wrembel, R. (2016). Towards Intelligent Data Analysis: The Metadata Challenge. In IoTBD (pp. 331-338). http://www.essi.upc.edu/~aabello/publications/16.IoTBD.Besim.pdf Accessed May 2020.
  12. Curcin, V. (2017). Embedding data provenance into the learning health system to facilitate reproducible research (Vol. 1(2), p. e10019). Chichester, UK: John Wiley.
  13. Dean, J., & Ghemawat, S. (2008). MapReduce: simplified data processing on large clusters. Communications of the ACM, 51(1), 107-113. DOI: 10.1145/1327452.1327492.
  14. Farhangmehr, F. (2014). Statistical Approaches for Big Data Analytics and Machine Learning: Data-Driven Network Reconstruction and Predictive Modelling of Time Series Biological Systems. University of California, San Diego.
  15. Metair, H. A. (2020). The Role of Social Networks in Supporting e-learning. Acta Scientiae et Intellectus, 6(3), 270-283.


Other issues:
Vol.12(3)(2021)
Vol.12(2)(2021)
Vol.12(1)(2021)
Vol.11(16)(2020)
Vol.11(15)(2020)
Vol.11(14)(2020)
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