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Case Study: Efficient Faculty Recruitment Using Genetic Algorithm
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Author(s): Amit Verma (Chandigarh Engineering College, India), Iqbaldeep Kaur (Chandigarh Engineering College, India), Dolly Sharma (Chandigarh Group of Colleges, India)and Inderjeet Singh (Chandigarh Group of Colleges, India)
Copyright: 2019
Pages: 13
Source title:
Extracting Knowledge From Opinion Mining
Source Author(s)/Editor(s): Rashmi Agrawal (Manav Rachna International Institute of Research and Studies, India)and Neha Gupta (Manav Rachna International Institute of Research and Studies, India)
DOI: 10.4018/978-1-5225-6117-0.ch014
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Abstract
Recruitment process takes place based on needed data while certain limiting factors are ignored. The objective of the chapter is to recruit best employees while taking care of limiting factors from the cluster for resource management and scheduling. Various parameters of the recruits have been selected to find the maximum score achieved by them. Recruitment process makes a database as cluster in the software environment perform the information retrieval on the database and then perform data mining using genetic algorithm while taking care of the positive values in contrast to limiting values received from the database. A bigger level recruitment process finds required values of a person, so negative points are ignored earlier in the recruitment process because there is no direct way to compare them. Genetic algorithm will create output in the form of chromosomal form. Again, apply information retrieval to get actual output. Major application of this process is that it will improve the selection process of candidates to a higher level of perfection in less time.
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