Open AccessO Problema de Escassez de Matchings em Recomendações nos Domínios de Recrutamento
Author(s) -
Alan Cardoso,
Fernando Mourão,
Leonardo Rocha
Publication year - 2021
Language(s) - English
Resource type - Conference proceedings
DOI - 10.5753/webmedia_estendido.2021.17604
Subject(s) - heuristics , computer science , heuristic , rss , matching (statistics) , recommender system , artificial intelligence , machine learning , mathematics , world wide web , statistics , operating system
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.