Proposing a Machine Learning Approach to Analyze and Predict Employment and its Factors

Author
Keywords
Abstract
This paper presents an original study with the aim of propose and test a machine learning approach to research about employability and employment. To understand how the graduates get employed, researchers propose to build predictive models using machine learning algorithms, extracting after that the most relevant factors that describe the model and employing further analysis techniques like clustering to get deeper insights. To test the proposal, is presented a case study that involves data from the Spanish Observatory for Employability and Employment (OEEU). Using data from this project (information about 3000 students), has been built predictive models that define how these students get a job after finalizing their degrees. The results obtained in this case study are very promising, and encourage authors to refine the process and validate it in further research.
Year of Publication
2018
Journal
International Journal of Interactive Multimedia and Artificial Intelligence
Volume
5
Issue
Special Issue on Big Data and Open Education
Number
2
Number of Pages
39-45
Date Published
09/2018
ISSN Number
1989-1660
Citation Key
URL
http://www.ijimai.org/journal/sites/default/files/files/2018/02/ijimai_5_2_5_pdf_12552.pdf
DOI
10.9781/ijimai.2018.02.002
Attachment