InFoLiS-based methods among top 4 finalists at Rich Context Competition

Researchers from GESIS participated in the Rich Context Competition organized by the Coleridge Initiative and were among the top 4 finalists.

The goal of this competition was to automate the identification of research datasets and the associated research methods and fields in research publications in the social science discipline by applying State of the Art machine learning and data analysis methods.

For their contribution to the competition, the GESIS team reused and extended methods that have been developed in the InFoLiS project.