A study to enhance candidate screening process using similarity analysis. (27th March 2019)

• Record Type: Journal Article
• Authors: Ujlayan, Anshul; Sharma, Manisha
• Is Part Of: International journal of business and data analytics. Volume 1:Number 1(2019)
• Page Start: 41
• Page End: 53
• Publication Date: 2019-03-27
• Subjects: recruitment process -- similarity analysis -- latent Dirichlet allocation -- LDA -- candidates' profile -- IT sector; 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

Recruitment process is always continuous and open positions mostly have short time to get filled thereby for any such open position, organisations generally have to deal with higher incremental costs. Many advanced recruitment processes/methodologies are directly associated with the risk of failure, loss of effort, loss of time and money. Every organisation in any industry always aims to hire the best suitable candidate to the open position with right skillsets in the shortest possible time and with the lowest costs. Therefore, there is a need to experiment and explore the existing approaches, which can help in reducing the time and the screening effort in initial stage of recruitment practices. Consequently this paper attempts to implement the similarity analysis approach for a random sample of resumes from IT sector in National Capital Region (NCR), India to provide the best match of candidates' profile as per the required job description. The latent Dirichlet allocation (LDA) is used to find the similarity between job description and candidate's profile. The study will help the IT industry in identifying and selecting the best matched candidates' profile based on the key features in job description.