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Intelligent search system for resume and labor law.

Authors :
Hien Nguyen
Vuong Pham
Ngo, Hung Q.
Anh Huynh
Binh Nguyen
Machado, José
Source :
PeerJ Computer Science; Jan2024, p1-35, 35p
Publication Year :
2024

Abstract

Labor and employment are important issues in social life. The demand for online job searching and searching for labor regulations in legal documents, particularly regarding the policy for unemployment benefits, is essential. Nowadays, each function has some programs for its working. However, there is no program that combines both functions. In practice, when users seek a job, they may be unemployed or want to transfer to another work. Thus, they are required to search for regulations about unemployment insurance policies and related information, as well as regulations about workers working smoothly and following labor law. Ontology is a useful technique for representing areas of practical knowledge. This article proposes an ontology-based method for solving labor and employment-related problems. First, we construct an ontology of job skills to match curriculum vitae (CV) and job descriptions (JD). In addition, an ontology for representing labor law documents is proposed to aid users in their search for legal labor law regulations. These ontologies are combined to construct the knowledge base of a job-searching and labor law-searching system. In addition, this integrated ontology is used to study several issues involving the matching of CVs and JDs and the search for labor law issues. A system for intelligent resume searching in information technology is developed using the proposed method. This system also incorporates queries pertaining to Vietnamese labor law policies regarding unemployment and healthcare benefits. The experimental results demonstrate that the method designed to assist job seekers and users searching for legal labor documents is effective. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
23765992
Database :
Complementary Index
Journal :
PeerJ Computer Science
Publication Type :
Academic Journal
Accession number :
175477543
Full Text :
https://doi.org/10.7717/peerj-cs.1786