Predictive Analytics in Recruitment Allows Organizations to become Proactive, Advancing, Anticipating Outcomes & Behaviors based on Actual Data, Data-Driven Recruitment Strategy
Gayathri Denis1, T Krishna Kumar2, Karthikeyan3, S Sasipriya4
1Gayathri Denis*, Research Scholar, Bharath Institute of Higher Education and Research, Chennai, India.
2T Krishna Kumar, Assistant Professor, Department of Computer Science and Engineering, Bharath Institute of Higher Education and Research, Chennai, India.
3Karthikeyan, Professor and Principal, Department of Computer Science and Engineering, Tamil Nadu College of Engineering, Coimbatore, India.
4S Sasipriya, Professor, Department of Computer Science and Engineering, Sri Krishna College of Engineering and Technology, Coimbatore, India
Manuscript received on November 15, 2019. | Revised Manuscript received on 20 November, 2019. | Manuscript published on December 10, 2019. | PP: 2329-2332 | Volume-9 Issue-2, December 2019. | Retrieval Number: B7768129219/2019©BEIESP | DOI: 10.35940/ijitee.B7768.129219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Recruitment Analytics is highly important of an organization since which plays vital role. There are new recruitment processes analyzed but still found hard to find the perfectly fitted employee in an organization in order to improve the Hiring Process To do sourcing best for the sort of skills worker this paper represents the Predictive analytics and which takes this to a in addition level by using supporting you get more insights based totally on each useful resource you use to find applicants. Data may be mined from social media sites, popular task aggregators and many others. This paper illustrates data driven strategy. so that the personality can be predicted and the most suitable employee can be recruited.
Keywords: Big Data, Modern Recruitment, Clustering and Data Mining.
Scope of the Article: Clustering