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DOI: 10.14569/IJACSA.2017.080502
PDF

Scalable Service for Predictive Learning based on the Professional Social Networking Sites

Author 1: Evgeny Nikulchev
Author 2: Dmitry Ilin
Author 3: Gregory Bubnov
Author 4: Egor Mateshuk

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 8 Issue 5, 2017.

  • Abstract and Keywords
  • How to Cite this Article
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Abstract: Professional social networking sites are widely used as a tool for obtaining specific information such as technology trends and professional skills demand. The article is aimed to consider the evolution of services for professional communities through integration of analysis of the patent activity, analysis of the academic research activity and analysis of the labour market trends. Authors have developed the prototype of a predictive learning software service which intended to fill the gap between professional social networking sites and e-learning systems, including massive open online course systems. It includes functionality for monitoring of professional skills demand on the labour market and analysis of patents for each corresponding technology. The software service will help to determine demand for professional skills, to actualise an applicant’s skillset, to organise professional communities and to build individual learning programs for studying of skills and technologies which are predicted to grow in demand on the labour market.

Keywords: Online social networks; Social networking sites; Technology life cycle; Predictive learning; Patent activity analysis, Professional skills; Topic detection; LinkedIn; ResearchGate

Evgeny Nikulchev, Dmitry Ilin, Gregory Bubnov and Egor Mateshuk, “Scalable Service for Predictive Learning based on the Professional Social Networking Sites” International Journal of Advanced Computer Science and Applications(IJACSA), 8(5), 2017. http://dx.doi.org/10.14569/IJACSA.2017.080502

@article{Nikulchev2017,
title = {Scalable Service for Predictive Learning based on the Professional Social Networking Sites},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.080502},
url = {http://dx.doi.org/10.14569/IJACSA.2017.080502},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {5},
author = {Evgeny Nikulchev and Dmitry Ilin and Gregory Bubnov and Egor Mateshuk}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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