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Keyword: Recruitment
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Open AccessArticle
10 Pages, 1,011 KB Download PDF

Innovations in Recruitment—Social Media

Advances in Science, Technology and Engineering Systems Journal, Volume 6, Issue 6, Page # 88–97, 2021; DOI: 10.25046/aj060613
Abstract:

The main objective and contribution of the paper is to describe the creation of a model to support recruitment using social media information and its deployment in practice. The model includes the design of an automated solution for downloading social media data and a proposal for the subsequent analysis and creation of a predictive model…

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(This article belongs to the SP11 (Special Issue on Innovation in Computing, Engineering Science & Technology 2021) & Section Interdisciplinary Applications of Computer Science (CSI))
Open AccessArticle
11 Pages, 1,495 KB Download PDF

Need of E-Recruitment System for Universities: Case of Pulchowk Campus, Nepal

Advances in Science, Technology and Engineering Systems Journal, Volume 5, Issue 5, Page # 902–912, 2020; DOI: 10.25046/aj0505110
Abstract:

This paper highlights the importance of on-campus online job recruitment system and its role in helping students grab the available job opportunities. It highlights the problems associated with the traditional way of hiring, especially for college students. It also presents some findings and results obtained through various surveys conducted within the campus before and after…

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(This article belongs to the SP9 (Special Issue on Multidisciplinary Innovation in Engineering Science & Technology 2020) & Section Interdisciplinary Applications of Computer Science (CSI))
Open AccessArticle
7 Pages, 382 KB Download PDF

Hybrid Discriminant Neural Networks for Performance Job Prediction

Advances in Science, Technology and Engineering Systems Journal, Volume 8, Issue 2, Page # 116–122, 2023; DOI: 10.25046/aj080213
Abstract:

Determining the best candidates for a certain job rapidly has been one of the most interesting subjects for recruiters and companies due to high costs and times that takes the process. The accuracy of the models, particularly, is heavily influenced by the discriminant variables that are chosen for predicting the candidates scores. This study aims…

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(This article belongs to the SP14 (Special Issue on Computing, Engineering and Multidisciplinary Sciences 2022-23) & Section Operations Research & Management Science (ORM))

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