Related papers: Data to Decisions: A Computational Framework to Identify skill requirements from Advertorial Data

Data to Decisions: A Computational Framework to Identify skill requirements from Advertorial Data

URL: http://arxiv.org/abs/2503.17424v1
Date: Fri, 21 Mar 2025 09:49:31 GMT
Title: Data to Decisions: A Computational Framework to Identify skill requirements from Advertorial Data
Authors: Aakash Singh, Anurag Kanaujia, Vivek Kumar Singh,
Abstract summary: The proposed framework uses techniques of statistical analysis, data mining and natural language processing for the purpose.<n>The analytical results not only provide useful insights about current state of skill needs in CS&IT industry but also provide practical implications to prospective job applicants, training agencies, and institutions of higher education & professional training.
Score: 1.5621498886998335
License: http://creativecommons.org/licenses/by-nc-nd/4.0/
Abstract: Among the factors of production, human capital or skilled manpower is the one that keeps evolving and adapts to changing conditions and resources. This adaptability makes human capital the most crucial factor in ensuring a sustainable growth of industry/sector. As new technologies are developed and adopted, the new generations are required to acquire skills in newer technologies in order to be employable. At the same time professionals are required to upskill and reskill themselves to remain relevant in the industry. There is however no straightforward method to identify the skill needs of the industry at a given point of time. Therefore, this paper proposes a data to decision framework that can successfully identify the desired skill set in a given area by analysing the advertorial data collected from popular online job portals and supplied as input to the framework. The proposed framework uses techniques of statistical analysis, data mining and natural language processing for the purpose. The applicability of the framework is demonstrated on CS&IT job advertisement data from India. The analytical results not only provide useful insights about current state of skill needs in CS&IT industry but also provide practical implications to prospective job applicants, training agencies, and institutions of higher education & professional training.

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