文章基本信息

标题：Smart job searching system based on information retrieval techniques and similarity of fuzzy parameterized sets
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作者：Malek Alksasbeh ; Tamer Abukhalil ; Bassam A. Y. Alqaralleh 等
期刊名称：International Journal of Electrical and Computer Engineering
电子版ISSN：2088-8708
出版年度：2021
卷号：11
期号：1
页码：636
DOI：10.11591/ijece.v11i1.pp636-645
出版社：Institute of Advanced Engineering and Science (IAES)
摘要：Job searching for the proper vacancy among several choices is one of the most important decision-making problems. The necessity of dealing with uncertainty in such real-world problems has been a long-term research challenge which has originated from different methodologies and theories. The main contribution of this work is to match the applicant curriculum vitae (CV) with the best available job opportunities based on certain criteria. The proposed job searching system (JSS) implements a series of approaches which can be broken down into segmentation, tokenization, part of speech, gazetteer, and fuzzy inference to extract and arrange the required data from the job announcements and CV. Moreover, this study designs a fuzzy parameterized structure to store such data as well as a measuring tool to calculate the degree of similarity between the job requirements and the applicant’s CV. In addition, this system analyses the computed similarity scores in order to get the optimal job opportunities for the job seeker in descending order. The performance evaluation of the proposed system shows high recall and precision percentages for the matching process. The results also confirm the viability of the JSS approach in handling the fuzziness that is associated with the problem of job searching.