We introduce an emerging AI-based approach and prototype system for assisting team formation when researchers respond to calls for proposals from funding agencies. This is an instance of the general problem of building teams when demand opportunities come periodically and potential members may vary over time. The novelties of our approach are that we: (a) extract technical skills needed about researchers and calls from multiple data sources and normalize them using Natural Language Processing (NLP) techniques, (b) build a prototype solution based on matching and teaming based on constraints, (c) describe initial feedback about system from researchers at a University to deploy, and (d) create and publish a dataset that others can use.
翻译:在研究人员响应供资机构的建议要求时,我们采用新的以AI为基础的方法和协助团队组建的原型系统,这是当需求机会定期出现,潜在成员可能随时间而变化时,建立团队这一普遍问题的一个实例,我们的方法的新颖之处是,我们:(a) 从多种数据来源提取研究人员和呼叫所需的技术技能,并使用自然语言处理技术,使这些技能正常化;(b) 建立基于基于制约的匹配和团队化的原型解决方案;(c) 描述大学研究人员关于部署系统的初步反馈,以及(d) 创建和公布可供他人使用的数据集。