O Problema de Escassez de Matchings em Recomendações nos Domínios de Recrutamento

  • Alan Cardoso UFSJ
  • Fernando Mourão Seek AIPS
  • Leonardo Rocha UFSJ


Candidates and job vacancies may remain for long periods without real opportunities in Recommendation Systems (RSs) for online recruitment. We refer to these scenarios as the Matching Scarcity Problem (MaSP). We formalize the MaSP and propose a strategy to identify candidates and vacancies suffering from it. We also propose five heuristics, which suggest changes in CVs and jobs descriptions, to mitigate the MaSP. The best heuristic was able to reduce up to 50% the number of CVs and jobs suffering from MaSP.

Palavras-chave: Job Recommendation, Matching Scarcity, User Modeling


Alan Cardoso, Fernando Mourão, and Leonardo Rocha. 2019. A Characterization Methodology for Candidates and Recruiters Interaction in Online Recruitment Services. In Proceedings of the 25th WebMedia’19. 8 pages. https://doi.org/10.1145/3323503.3349541

Alan Cardoso, Fernando Mourão, and Leonardo Rocha. 2020. Mitigating Matching Scarcity in Recruitment Recommendation Domains. In Proceedings of the 26th WebMedia’20. https://doi.org/10.1145/3428658.3430968

Alan Cardoso, Fernando Mourão, and Leonardo Rocha. 2021. The Matching Scarcity Problem: When recommenders do not connect the edges in recruitment services. Expert Systems with Applications (2021). https://doi.org/10.1016/j.eswa.2021.114764

Diego Carvalho, Nícollas Silva, Alan Cardoso, Elverton Fazzion, Adriano C. M. Pereira, and Leonardo Rocha. [n.d.]. Understanding Users-Contents Interaction in Non-Linear Multimedia Streaming Services. In Proceedings of the 24th WebMedia 2018. 229–232. https://doi.org/10.1145/3243082.3264661

Papiya Das, Kashyap Barua, Manjusha Pandey, and Siddharth Swarup Routaray. 2018. Context Level Entity Extraction Using Text Analytics with Big Data Tools. In IEMIS 2018.

Arthur P. Dempster. 2008. A Generalization of Bayesian Inference. Springer Berlin Heidelberg, Berlin, Heidelberg, 73–104. https://doi.org/10.1007/978-3-540-44792-4_4

Maryam Fazel-Zarandi and Mark Fox. 2009. Semantic Matchmaking for Job Recruitment: An Ontology-Based Hybrid Approach. International Semantic Web Conference (01 2009).

Yao Lu, Sandy El Helou, and Denis Gillet. 2013. A Recommender System for Job Seeking and Recruiting Website. In Proceedings of the WWW 2013.

J. Malinowski, T. Keim, O. Wendt, and T. Weitzel. 2006. Matching People and Jobs: A Bilateral Recommendation Approach. In HICSS’06.

XIAO-LI MENG and DONALD B. RUBIN. 1993. Maximum likelihood estimation via the ECM algorithm: A general framework. Biometrika (1993). https://doi.org/10.1093/biomet/80.2.267

Ioannis Paparrizos, B. Barla Cambazoglu, and Aristides Gionis. 2011. Machine Learned Job Recommendation. In Proc. of the ACM RecSys 2011.

Luiz Pizzato, Tomek Rej, Thomas Chung, Irena Koprinska, and Judy Kay. 2010. RECON: A Reciprocal Recommender for Online Dating. In Proc. of the ACM RecSys 2010.
Como Citar

Selecione um Formato
CARDOSO, Alan; MOURÃO, Fernando; ROCHA, Leonardo. O Problema de Escassez de Matchings em Recomendações nos Domínios de Recrutamento. In: CONCURSO DE TESES E DISSERTAÇÕES - SIMPÓSIO BRASILEIRO DE SISTEMAS MULTIMÍDIA E WEB (WEBMEDIA), 27. , 2021, Minas Gerais. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2021 . p. 15-18. ISSN 2596-1683. DOI: https://doi.org/10.5753/webmedia_estendido.2021.17604.