An example of the application of artificial intelligence models in human resources processes

Authors : Selim Sürücü, Berk Küçük, Mustafa Kemal Aydın

Pages : 101-116

Doi:10.33707/akuiibfd.1443940

View : 224 | Download : 179

Publication Date : 2024-10-21

Article Type : Research Paper

Abstract :Creating job postings and selecting suitable candidates among these job postings is a challenging process. This process increases the workload of human resources and causes the process to proceed slowly. It is of great importance for human resources departments to utilize information processing technologies to create job postings effectively and to evaluate the CVs of applicants to these postings. This study introduces and analyzes two different technologies that can help human resources. In the process of preparing job advertisements in the field of IT, in the first stage, the word cloud method is used to decide which keywords should be emphasized in the advertisement texts. In the second stage, the resumes of the applicants are analyzed using three different deep learning models such as CNN (Convolutional Neural Network), GRU (Gated Recurrent Unit), and LSTM (Long Short-Term Memory) for classification purposes. While the performance of these models is evaluated using metrics such as accuracy, MCC, F_1 score, and MSE, the decision-making processes of the models with explainable artificial intelligence are also analyzed. In this context, the GRU model, which achieved an accuracy of 99%, provided the most superior result in this study and the literature. This research shows that deep learning models provide high accuracy rates and efficiency in human resources resume classification and candidate matching processes. It also explains that using the word cloud method, the most appropriate keywords can be identified, and advertisements can be created.
Keywords : Özgeçmiş sınıflandırma, Yapay zekâ destekli insan kaynakları otomasyonu, Öneri sistemi, Doğal dil işleme, Metin sınıflandırması

ORIGINAL ARTICLE URL