Resume searching to decide best candidate based on RELIEF method

Open Science Journal

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Field Value
Title Resume searching to decide best candidate based on RELIEF method
Creator Nasr, Sara
German, Oleg
resume; job description search; text with mistakes; short text processing; searching methods; fuzzy text; semantic blocks
Description             Nowadays the number of people searching work is increasing and the number of university graduates is also getting larger. Companies searching for a perfect job candidate for a person working in the informatics domain may be lost between different resumes with different formats and big quantity. Selecting the best curriculum vitae (CV) is a considered a big step to help any company decide whether a job seeker is suitable or not. The criteria that should be taken into consideration is divided between a block of private information and another block of professional data. The blocks are based on age, education, participating in real projects, availability of published papers or research activities, possessing modern programming languages and technologies and so on. Selecting the perfect candidate needs an estimation based on a choice function similar to the utility function which weighs the different criteria and helps in evaluating them numerically. But since we may be dealing with some fuzzy or uncertain information we proposed the use of modified Boyer Moore algorithm and RELIEF method to reach the target.
Publisher Open Science Journal
Date 2020-06-10
Type info:eu-repo/semantics/article

Format application/pdf
Source Open Science Journal; Vol 5, No 2 (2020): Open Science Journal
Language eng
Rights Copyright (c) 2020 Open Science Journal

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