A fuzzy expert system based recommendation model for nuclear wastewater research collaborators

In order to help scholars in the field of nuclear wastewater explore potential research collaborators more efficiently, this paper proposes a fuzzy expert system-based research collaborator recommendation model (FCR-NWR) to address the problems of existing collaboration recommendation models in terms of textual representation, incomplete extraction of scholars' features, and the lack of diversified information and reasoning decision-making methods. The model fully obtains text features through multilevel text analysis, combines with new methods to calculate scholars' comprehensive academic ability and scientific research cooperation intensity, and finally utilizes the expert system to simulate the knowledge and decision-making process of human experts for collaborator recommendation. Through this model, scholars in the field of nuclear wastewater can integrate into the academic community faster, find potential collaborators, and promote academic co-development. The experimental results show that FCR-NWR outperforms traditional methods in terms of precision, recall and F1 value.