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ULTRA: A Data-driven Approach for Recommending Team Formation in Response to Proposal Calls

Authors :
Srivastava, Biplav
Koppel, Tarmo
Paladi, Sai Teja
Valluru, Siva Likitha
Sharma, Rohit
Bond, Owen
Publication Year :
2022

Abstract

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.<br />Comment: 8 pages, Accepted to IEEE ICDM Workshop on AI for Nudging and Personalization (WAIN) 2022

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2201.05646
Document Type :
Working Paper