loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Bruno Coelho 1 ; Fernando Costa 2 and Gil M. Gonçalves 3

Affiliations: 1 INOVA+ and Centro de Inovação de Matosinhos, Portugal ; 2 Superior Institute of Engineering of Porto, Portugal ; 3 INOVA+, Centro de Inovação de Matosinhos, Faculty of Engineering and University of Porto, Portugal

Keyword(s): recommender systems, decision support systems, match-making algorithms, jobs, employment, work, teams, user modelling, content-based filtering, collaborative filtering

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Business Process Management ; Business-It Alignment ; Cloud Computing ; Collaboration and e-Services ; Collaborative Systems ; Complex Systems Modeling and Simulation ; Data Communication Networking ; e-Business ; Enterprise Engineering ; Enterprise Information Systems ; Knowledge Management and Information Sharing ; Knowledge-Based Systems ; Logistics ; Modeling and Frameworks ; Platforms and Applications ; Simulation and Modeling ; Social Networks ; Symbolic Systems ; Telecommunications

Abstract: Nowadays people search job opportunities or candidates mainly online, where several websites for this purpose already do exist (LinkedIn, Guru and oDesk, amongst others). This task is especially difficult because of the large number of items to look for and manual compatibility verification. What we propose in this paper is a Hybrid Job Recommendation System that considers the user model (content-based filtering) and social interactions (collaborative filtering) to improve the quality of its recommendations. Our solution is also able to generate adequate teams for a given job opportunity, based not only on the needed competences but also on the social compatibility between their members.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.238.161.165

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Coelho, B.; Costa, F. and M. Gonçalves, G. (2015). Hyred - HYbrid Job REcommenDation System. In Proceedings of the 12th International Conference on e-Business (ICETE 2015) - ICE-B; ISBN 978-989-758-113-7, SciTePress, pages 29-38. DOI: 10.5220/0005569200290038

@conference{ice-b15,
author={Bruno Coelho. and Fernando Costa. and Gil {M. Gon\c{C}alves}.},
title={Hyred - HYbrid Job REcommenDation System},
booktitle={Proceedings of the 12th International Conference on e-Business (ICETE 2015) - ICE-B},
year={2015},
pages={29-38},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005569200290038},
isbn={978-989-758-113-7},
}

TY - CONF

JO - Proceedings of the 12th International Conference on e-Business (ICETE 2015) - ICE-B
TI - Hyred - HYbrid Job REcommenDation System
SN - 978-989-758-113-7
AU - Coelho, B.
AU - Costa, F.
AU - M. Gonçalves, G.
PY - 2015
SP - 29
EP - 38
DO - 10.5220/0005569200290038
PB - SciTePress