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Discusion-1 Comment 150 words

In the past few years, the emergence of new technologies has brought together different models based on the internet. companies have also adapted approaches to the new digital ecosystem by creating and improving abilities in knowledge and information extraction. Big data, that may help in implementing the innovation-driven approach as well as promote industrial upgrading and transformation (Mityushev, 2018). In the world where large sets of data are generated daily, data science and data analytics have become quite an essential tool for extracting knowledge from the collections of data to formulate the best strategy and understand the environment of a business. In the 3F method, the cross-validated error of prediction is used in place of significance levels within the reference approach.

The productive, healthy and educated workers are key to the development of big data in the USA, particularly top-talents are important. 3F method can be introduced to help in defining the distribution of the talents across the world and making informed decisions whether they are required in the US. The method depends on calculating the index of the brain gain to the analysis of the top-talent introductory demand of a nation (Zhao et al., 2017). First, it should concentrate on high-frequency keywords of a certain field by deriving the keywords of high frequency. Second, use the keywords to find top-talents in a certain field. Lastly, determine the index for brain gain to approximate if a nation requires to introduce top-talents in big data.

 

References

Mityushev, V. (2018). Cluster method in composites and its convergence. Applied Mathematics Letters, 77, 44-48.

Zhao, L., Huang, Y., Wang, Y., & Liu, J. (2017). Analysis on the Demand of Top Talent Introduction in Big Data and Cloud Computing Field in China Based on 3-F Method. In 2017 Portland International Conference on Management of Engineering and Technology (PICMET) (pp. 1-3). IEEE.

Discusion-2 Comment 150 words

COLLAPSE

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Concept of 3-F method

In the past decade, we have seen pretty rapid germination of big data and cloud computing, where it is needed many best talents globally. The 3-F bibliometric method introduced and applied to draw the marketing of top young talents globally and analysis of their demand to a country (Zhao, Huang, Wang & Liu, 2017). First of all, fetch the history database of the high-impact summary collection in a specific field with the method of text analysis. Where these collections ranked in the top place during that fiscal year with in the same area (Zhao et al., 2017). Then try to search with the keywords to identify the top talents in that specific field through the web of science and gather their information based on the abilities that they have, the country as well as institution distributions. By using this collected information, it is easy to specify the communication or first author of high-impact collection. Finally, it is time to decide where these top talents needed to a country in the specific field with the brain gain index formula (Zhao et al., 2017).

The bibliometric analysis primarily depends on the significant methods of multiple correspondence analysis (MCA). These methods classified into three ways are human-scored systems, single word count systems, and computerized systems (Dabic, Maley, Leo-Paul, Novak, Pellegrini & Caputo, 2019). According to the 3-F method analysis, its already introduction of top talents distributed. Still, if we do the study based on the MCA, it may change the report, which results from introducing the top young skills to the united states with the current emerging field of big data and cloud computing. Because the usage of technology rapidly increasing with the high expectations where it is still required top talents to full fill these expectations within the specific field. By using MCA will result from the consistency in one area, and also it is possible to count that number of top talents distributed to the united states (Dabic et al., 2019).

 

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