Integration and Recommendation System of Profiles based on Professional Social Networks

Authors

DOI:

https://doi.org/10.4108/eetcasa.4500

Keywords:

Integration system, job recommender system, social recommendations, personalized recommendations, bilateral matching problem

Abstract

The aim of our investigation is to personalize bilateral recommendation of job-related proposals based on existing professional social networks. In a context where the points of view of job seekers and employers can be contradictory, our approach consists in trying to bring the both in a best possible matching. To this end, we propose an integration system that gives a minimum of credit to the users’ data in order to facilitate the discovery of relevant proposals based on the users’ behaviors, on the characteristics of the proposals and on possible relationships. The main contribution is the proposal of an architecture for the recommendation of profiles and job offers including social and administrative factors. The particularity of our approach lies in the freedom from the recommendation problem by using metrics proven in the literature for the estimation of similarity rates. We have used these metrics as default values to appropriate data dimensions. It emerges that, the user’s behavior is exclusively responsible for the recommendations. However, the cross-analysis of randomly generated behaviors on real profiles collected on Cameroonian sites dedicated to job offers, shows the influence of the most active users. But, for requests via the search bar (interface with the script respecting the path of our architecture) the central subject remains the user. Our current work is limited by a data set that is not very representative of changing socio-economic conditions.

Author Biographies

Paul Dayang, University of Ngaoundéré

University of Ngaoundere · Computer Science · Head of Department · Associate Professor

Ulriche Mbouche Bomda, University of Ngaoundéré

University of Ngaoundere . Compter Science . Researcher . Msc Computer Engineering

References

Renaud-Deputter, S. (2013) Système de recommandations utilisant une combinaison de filtrage collaboratif et de segmentation pour des données implicites. Ph.D. thesis, Université de Sherbrooke.

Jannach, D. and Zanker, M. (2019) Collaborative filtering: matrix completion and session-based recommendation tasks. In Collaborative Recommendations: Algorithms, Practical Challenges and Applications (World Scientific), 1–34.

Ticha, S.B. (2015) Recommandation personnalisée hybride. Ph.D. thesis, Université de Lorraine.

Werner, D., Hassan, T., Bertaux, A., Cruz, C. and Silva, N. (2014) Semantic-based recommender system with human feeling relevance measure. In Science and Information Conference (Springer): 177–191. DOI: https://doi.org/10.1007/978-3-319-14654-6_11

Bouzayane, S., Inès, S., Kassel, G. and Gargouri, F. (2017) Recommandation basée sur l’aide multicritère à la décision pour personnaliser l’échange d’information. Ingenierie des Systemes d’Information 22(6): 71.

Wang, J., Zhuang, H., Li, C., Chen, H., Xu, B., He, Z. and Zhou, X. (2016) A fast and better hybrid recommender system based on spark. In IFIP International Conference on Network and Parallel Computing (Springer): 147–159. DOI: https://doi.org/10.1007/978-3-319-47099-3_12

Reusens, M., Lemahieu, W., Baesens, B. and Sels, L. (2017) A note on explicit versus implicit information for job recommendation. Decision Support Systems 98: 26– 35. DOI: https://doi.org/10.1016/j.dss.2017.04.002

de Ruijt, C. and Bhulai, S. (2021) Job recommender systems: A review. arXiv preprint arXiv:2111.13576 .

Tsopze, N. and Jiechieu Kameni, F.F. (2019) Approche hiérarchique d’indextraction des compétences dans des cvs en format pdf. Revue Africaine de la Recherche en Informatique et Mathématiques Appliquées 32. DOI: https://doi.org/10.46298/arima.4964

Zaroor, A., Maree, M. and Sabha, M. (2017) A hybrid approach to conceptual classification and ranking of resumes and their corresponding job posts. In International Conference on Intelligent Decision Technologies (Springer): 107–119. DOI: https://doi.org/10.1007/978-3-319-59421-7_10

Rivas, A., Chamoso, P., González-Briones, A., CasadoVara, R. and Corchado, J.M. (2019) Hybrid job offer recommender system in a social network. Expert Systems 36(4): e12416.

Hill, W., Stead, L., Rosenstein, M. and Furnas, G. (1995) Recommending and evaluating choices in a virtual community of use. In Proceedings of the SIGCHI conference on Human factors in computing systems: 194– 201. DOI: https://doi.org/10.1145/223904.223929

Shardanand, U. and Maes, P. (1995) Social information filtering: Algorithms for automating "word of mouth". In Proceedings of the SIGCHI conference on Human factors in computing systems: 210–217. DOI: https://doi.org/10.1145/223904.223931

Liu, R., Ouyang, Y., Rong, W., Song, X., Tang, C. and Xiong, Z. (2016) Rating prediction based job recommendation service for college students. In International conference on computational science and its applications (Springer): 453–467. DOI: https://doi.org/10.1007/978-3-319-42092-9_35

Dave, V.S., Zhang, B., Al Hasan, M., AlJadda, K. and Korayem, M. (2018) A combined representation learning approach for better job and skill recommendation. In Proceedings of the 27th ACM International Conference on Information and Knowledge Management: 1997–2005.

Belsare, R.G. and Deshmukh, D. (2018) Employment recommendation system using matching, collaborative filtering and content based recommendation. Int. J. Comput. Appl. Technol. Res 7(6): 215–220.

Chifu, A.G., Espinasse, B., Fournier, S., Kuehn, A. et al. (2021) Vers un système de recommandation de profils experts dans l’industrie des procédés. In CORIA 2021.

Rafter, R., Bradley, K. and Smyth, B. (2000) Personalised retrieval for online recruitment services. In The BCS/IRSG 22nd Annual Colloquium on Information Retrieval (IRSG 2000), Cambridge, UK, 5-7 April, 2000.

Malinowski, J., Keim, T., Wendt, O. and Weitzel, T. (2006) Matching people and jobs: A bilateral recommendation approach. In Proceedings of the 39th Annual Hawaii International Conference on System Sciences (HICSS’06) (IEEE), 6: 137c–137c. DOI: https://doi.org/10.1109/HICSS.2006.266

Lee, D.H. and Brusilovsky, P. (2007) Fighting information overflow with personalized comprehensive information access: A proactive job recommender. In Third International Conference on Autonomic and Autonomous Systems (ICAS’07) (IEEE): 21–21. DOI: https://doi.org/10.1109/CONIELECOMP.2007.76

Casagrande, A., Gotti, F. and Lapalme, G. (2017) Cerebra, un système de recommandation de candidats pour l’e-recrutement. In AISR2017.

Tondji, L.N. (2018) Web recommender system for job seeking and recruiting. Partial Fulfillment of a Masters II at AIMS .

Boumane, A., Talbi, A., Tahon, C. and Bouami, D. (2006) Contribution à la modélisation de la compétence. In MOSIM conference.

Savoie, L. (2014) Comment l’intermédiation guide-t-elle le consommateur sur Internet? Application aux services paysagers. Ph.D. thesis, Mon Eden, Parc d’activités du Vert Galant, 1 rue Saint-Simon, Saint-Ouen l’Aumône, 95041 Cergy Pontoise cedex.

Thierry, S., Gauthier, P.D. and Pollet, M. Concepts, données et réflexions autour des réseaux sociaux .

Tang, J., Hu, X. and Liu, H. (2013) Social recommendation: a review. Social Network Analysis and Mining 3(4): 1113–1133. DOI: https://doi.org/10.1007/s13278-013-0141-9

Lemdani, R. (2016) Système hybride d’adaptation dans les systèmes de recommandation. Ph.D. thesis, Université Paris-Saclay (ComUE).

Wan, J., Sun, Q., Li, X., Ding, J. and Zhu, Q. (2018) Personalized professional recommendation system based on undergraduate questionnaires. In 2018 17th International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES) (IEEE): 140–143.

Candillier, L., Chai, É. and Delpech, E. (2012) Systèmes de recommandation et recherche d’information. In Journée d’étude" Systèmes de recommandation"(CNAM) (Hermès Sciences): 6–pages. URL https://hal. archives-ouvertes.fr/hal-00912323.

Tran, M.L., Nguyen, A.T., Nguyen, Q.D. and Huynh, T. (2017) A comparison study for job recommendation. In 2017 International Conference on Information and Communications (ICIC) (IEEE): 199–204. DOI: https://doi.org/10.1109/INFOC.2017.8001667

Nguyen, A.T. (2006) COCoFil2: Un nouveau système de filtrage collaboratif basé sur le modèle des espaces de communautés. Ph.D. thesis, Université Joseph-Fourier- Grenoble I. URL https://tel.archives-ouvertes.fr/ tel-00353945.

Singh, A., Rose, C., Visweswariah, K., Chenthamarakshan, V. and Kambhatla, N. (2010) Prospect: a system for screening candidates for recruitment. In Proceedings of the 19th ACM international conference on Information and knowledge management: 659–668. DOI: https://doi.org/10.1145/1871437.1871523

Cappi, C., Chapdelaine, C., Gardes, L., Jenn, E., Lefevre, B., Picard, S. and Soumarmon, T. (2021) Dataset definition standard (dds). arXiv preprint arXiv:2101.03020 .

Jannach, D., Resnick, P., Tuzhilin, A. and Zanker, M. (2016) Recommender systems beyond matrix completion. Communications of the ACM 59(11): 94–102. DOI: https://doi.org/10.1145/2891406

Shalaby, W., AlAila, B., Korayem, M., Pournajaf, L., AlJadda, K., Quinn, S. and Zadrozny, W. (2017) Help me find a job: A graph-based approach for job recommendation at scale. In 2017 IEEE international conference on big data (big data) (IEEE): 1544–1553. DOI: https://doi.org/10.1109/BigData.2017.8258088

Coelho, B., Costa, F. and Gonçalves, G.M. (2015) Hyred: hybrid job recommendation system. In 2015 12th International Joint Conference on e-Business and Telecommunications (ICETE) (IEEE), 2: 29–38. DOI: https://doi.org/10.5220/0005569200290038

Kamga, F.B., Mboutchouang, V.d.P., Fotie, A., Nono, D.C., Wamba, T.P.J. and Fokou, C. (2019) Améliorer les Politiques d’Emploi des Jeunes en Afrique Francophone (Cameroun, Congo, Tchad, Côte d’Ivoire, Sénégal) - Rapport d’enquête Cameroun. Tech. Rep. (Projet CRDI - 108229001), Centre de Recherche pour le Développement International (CRDI), Benjamin FOMBA KAMGA, Email: fomba1@yahoo.fr - Tél: (237)677 320835.

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Published

15-01-2024

How to Cite

1.
Dayang P, Mbouche Bomda U. Integration and Recommendation System of Profiles based on Professional Social Networks. EAI Endorsed Trans Context Aware Syst App [Internet]. 2024 Jan. 15 [cited 2024 Feb. 22];10(1). Available from: https://publications.eai.eu/index.php/casa/article/view/4500