f method ,” 2017 portland international conference W r i t i n g
In this week’s reading, the concept of 3-F Method is introduced. Discuss the purpose of this concept and how it is calculated. Also perform your own research/analysis using these factors and provide your assessment on whether the United States need to introduce top talents in the field of big data and cloud computing by using bibliometrics.
Please make your initial post and two response posts substantive. A substantive post will do at least two of the following:
- Ask an interesting, thoughtful question pertaining to the topic
- Answer a question (in detail) posted by another student or the instructor
- Provide extensive additional information on the topic
- Explain, define, or analyze the topic in detail
- Share an applicable personal experience
- Provide an outside source (for example, an article from the UC Library) that applies to the topic, along with additional information about the topic or the source (please cite properly in APA)
- Make an argument concerning the topic.
At least one scholarly source should be used in the initial discussion thread. Be sure to use information from your readings and other sources from the UC Library. Use proper citations and references in your post.
500 words, APA format and references are important
L. Zhao, Y. Huang, Y. Wang and J. Liu, “Analysis on the Demand of Top Talent Introduction in Big Data and Cloud Computing Field in China Based on 3-F Method,” 2017 Portland International Conference on Management of Engineering and Technology (PICMET), Portland, OR, 2017, pp. 1-3. https://doi.org/10.23919/PICMET.2017.8125463
Saiki, S., Fukuyasu, N., Ichikawa, K., Kanda, T., Nakamura, M., Matsumoto, S., Yoshida, S., & Kusumoto, S. (2018). A Study of Practical Education Program on AI, Big Data, and Cloud Computing through Development of Automatic Ordering System. 2018 IEEE International Conference on Big Data, Cloud Computing, Data Science & Engineering (BCD), Big Data, Cloud Computing, Data Science & Engineering (BCD), 2018 IEEE International Conference on, BCD, 31–36. https://doi.org/10.1109/BCD2018.2018.00013
Psomakelis, E., Aisopos, F., Litke, A., Tserpes, K., Kardara, M., & Campo, P. M. (2016). Big IoT and social networking data for smart cities: Algorithmic improvements on Big Data Analysis in the context of RADICAL city applications.
Piccialli, F., & Jung, J. E. (2017). Understanding customer experience diffusion on social networking services by big data analytics. Mobile Networks and Applications, 22(4), 605-612. doi:http://dx.doi.org/10.1007/s11036-016-0803-8