Recommendation system as a business intelligence tool developed in the Jupyter notebook. Case: selection of productive personnel

Abstract

Recommendation Systems are a useful tool in an organization's decision-making process, because they base their recommendations on applied mathematical models. The organization's historical information-based Recommendation Systems make it possible to make even more accurate decisions because of the personal nature of the information that feeds them. Thanks to the various information technologies that exist, the creation of Customized Recommendation Systems according to the needs of the organization is of relative ease. The purpose of this article is to show the procedure for creating and operating a recommendation system developed in the Jupyter Notebook as a business intelligence tool that supports business decision-making applied to an organization-specific personnel selection case.