文章基本信息

标题：Scalable Service for Predictive Learning based on the Professional Social Networking Sites
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作者：Evgeny Nikulchev ; Dmitry Ilin ; Gregory Bubnov 等
期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2017
卷号：8
期号：5
DOI：10.14569/IJACSA.2017.080502
出版社：Science and Information Society (SAI)
摘要：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.
关键词：Online social networks; Social networking sites; Technology life cycle; Predictive learning; Patent activity analysis; Professional skills; Topic detection; LinkedIn; ResearchGate