The team formation problem has existed for many years in various guises. One important challenge in the team formation problem is to produce small teams that have a required set of skills. We propose a framework that incorporates machine learning to augment a collaboration graph with latent links between collaborators. This is combined with the solution of Steiner tree problems to form small teams that cover a specified set of tasks. Our framework not only considers the size of the team but also the likelihood that team members are going to collaborate with each other. We demonstrate our results using data from the US Patent office covering two different companies’ inventor networks. The results show that this technique can reduce the size of suggested teams.

中文翻译：

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使用机器学习预测链接并改进Steiner树解决方案以解决团队形成问题-跨公司研究

团队组建问题已经以各种形式存在了多年。团队组建问题中的一个重要挑战是建立具有所需技能的小型团队。我们提出了一个框架，该框架结合了机器学习功能，以利用协作者之间的潜在链接来扩大协作图。这与Steiner树问题的解决方案相结合，组成了涵盖指定任务集的小型团队。我们的框架不仅考虑团队的规模，而且还考虑团队成员之间进行协作的可能性。我们使用来自美国专利局的数据证明了我们的结果，该数据涵盖了两家公司的发明人网络。结果表明，该技术可以减少建议团队的规模。