An analysis of employee skills and potency using machine learning. (22nd June 2022)

• Record Type: Journal Article
• Authors: Ujlayan, Anshul; Sharma, Manisha
• Is Part Of: International journal of business and data analytics. Volume 2:Number 1(2022)
• Page Start: 20
• Page End: 32
• Publication Date: 2022-06-22
• Subjects: latent Dirichlet allocation -- LDA -- skills -- machine learning -- natural language processing -- topic modelling; Commercial statistics -- Data processing -- Periodicals; Industrial management -- Mathematical models -- Periodicals; Business -- Mathematical models -- Periodicals; Management -- Statistical methods -- Periodicals; Business -- Research -- Periodicals; 658.403
• Languages: English
• ISSNs: 2515-9100

Abstract

In the current era of digital technology, the human resource department in every information technology company is working hard to find and retain the potential employees. To manage and retain potential employees within the company, they need to analyse employee profile constantly for their skills and potency. In this research paper, we are proposing an approach to analyse the employee skills and potency for an IT company using machine learning. To analyse employee's profile we used natural language processing and topic modelling to discover the hidden skills, knowledge and experience pattern in profile. The natural language processing is used in data preparation and latent Dirichlet allocation is applied to identify topics. The outcome of this study will provide the key topics to look at the potency of employees. The visualisation of the key topics through graphs will help to have a quick view of employees' skills and potency. The analysis will help organisations in identifying employees with potential domain knowledge, relevant experience and technical skills.