Collaborative Team Recommendation for Skilled Users: Objectives, Techniques, and New Perspectives
Mahdis Saeedi, Christine Wong, Hossein Fani · 2024
Collaborative team recommendation involves selecting users with certain skills to form a team who will, more likely than not, accomplish a complex task successfully. To automate the traditionally tedious and error-prone manual process of team formation, researchers from several scientific spheres have proposed methods to tackle the problem. In this tutorial, while providing a taxonomy of team recommendation works based on their algorithmic approaches to model skilled users in collaborative teams, we perform a comprehensive and hands-on study of the graph-based approaches that comprise the mainstream in this field, then cover the neural team recommenders as the cutting-edge class of approaches. Further, we provide unifying definitions, formulations, and evaluation schema. Last, we introduce details of training strategies, benchmarking datasets, and open-source tools, along with directions for future works.