Fuzzification Technique for Candidate Rating and Selection
Author:
Affiliation:
1. Department of Software Engineering, Federal University of Technology, Nigeria
2. Department of Computer Science, Federal University of Technology, Nigeria
3. Department of Information Technology, Federal University of Technology, Nigeria
Abstract
The traditional ways of candidate selection and recruitment are prone to subjectivity, imprecision and vagueness. With a view to achieving objective and precise selection and recruitment while keeping up with technological improvement and changes, this paper discusses a fuzzification-based technique for candidate rating and selection. The technique comprises a fuzzy logic component that is an extension of Boolean logic and used for establishing accurate selection process and precise solutions to multi-variable problems. There is a knowledge base component which forms the database of multi-level information and rule base which composes a set of if-then statements for decision making. Its inference engine applies a pre-defined procedure on input from the rule base and fuzzy logic interfaces for final recommendations. The proposed methodology performs pre-defined procedures that are based on some input sets which stores multi-level information derived from several pre-specified scores. Results from the implementation of the proposed technique established its practical function.
Publisher
IGI Global
Subject
Modeling and Simulation,General Computer Science
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