“eRReBIS” Business Intelligence based Intelligent Recommender System for e-Recruitment Process

Siwar Ayadi, Manel Bensassi, Henda Ben Ghezala

2022

Abstract

Due to the continuous and growing spread of the corona virus worldwide, it is important, especially in the business era, to develop accurate data driven decision-aided system to support business decision-makers in processing, managing large amounts of information in the recruitment process. In this context, e-Recruitment Recommender systems emerged as a decision support systems and aims to help stakeholders in finding items that match their preferences. However, existing solutions do not afford the recruiter to manage the whole process from different points of view. Thus, the main goal of this paper is to build an accurate and generic data driven system based on Business intelligence architecture. The strengths of our proposal lie in the fact that it allows decision makers to (1) consider multiple and heterogeneous data sources, access and manage data in order to generate strategic reports and recommendations at all times (2) combine many similarity’s measure in the recommendation process (3) apply prescriptive analysis and machine learning algorithms to offer adapted and efficient recommendations.

Paper Citation

in Harvard Style

Ayadi S., Bensassi M. and Ben Ghezala H. (2022). “eRReBIS” Business Intelligence based Intelligent Recommender System for e-Recruitment Process. In Proceedings of the 18th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST, ISBN 978-989-758-613-2, pages 373-380. DOI: 10.5220/0011530200003318

in Bibtex Style

@conference{webist22,
author={Siwar Ayadi and Manel Bensassi and Henda Ben Ghezala},
title={“eRReBIS” Business Intelligence based Intelligent Recommender System for e-Recruitment Process},
booktitle={Proceedings of the 18th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,},
year={2022},
pages={373-380},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011530200003318},
isbn={978-989-758-613-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 18th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,
TI - “eRReBIS” Business Intelligence based Intelligent Recommender System for e-Recruitment Process
SN - 978-989-758-613-2
AU - Ayadi S.
AU - Bensassi M.
AU - Ben Ghezala H.
PY - 2022
SP - 373
EP - 380
DO - 10.5220/0011530200003318