Team formation is concerned with the identification of a group of experts who have a high
likelihood of effectively collaborating with each other to satisfy a collection of input skills …

The team discovery task is concerned with finding a group of experts from a collaboration
network who would collectively cover a desirable set of skills. Most prior work for team …

Network representation learning and its applications have received increasing attention.
Due to their various application areas, many research groups have developed a diverse …

We contribute OpeNTF, an open-source python-based benchmark library to support neural
team formation research. Team formation falls under social information retrieval (Social IR) …

Neural team recommendation models have utilized graph representation learning to
achieve state-of-the-art performance in forming teams of experts whose success in …

Team formation aims to automate forming teams of experts who can successfully solve
difficult tasks, which have firsthand effects on creating organizational performance. While …

Predicting future successful teams of experts who can effectively collaborate is challenging
due to the experts' temporality of skill sets, levels of expertise, and collaboration ties, which …

Neural team recommendation has brought state-of-the-art efficacy while enhancing
efficiency at forming teams of experts whose success in completing complex tasks is almost …

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 …

Neural team recommendation models have brought state-of-the-art efficacy while enhancing
efficiency at recommending collaborative teams of experts who, more likely than not, can …