Machine learning and artificial intelligence as a decision support systems for human capital management


Human capital and human resources are key success factors for multiple knowledge-based companies. Managing competences of employees is one of the most important areas for modern management science. This paper presents, an innovative algorithm based on natural language processing (NLP) and association analysis for recognition, assignment and evaluation of competences in a knowledge-rich organizations. An algorithm performs keywords extraction from applicant’s and employees resumes, which are used later on in a supervised phase. Achieved results - 71% of balanced accuracy in a case study suggest, that a system can recognize important correlations between competences and assigned projects.

Poznan, Poland


Filip Wójcik
Senior Data Scientist and PhD candidate

Data scientist and University researcher, passionate of machine learning and statistical analysis. In the same time - experienced software developer with experience in different technologies (from .NET to open-source).