Post: A machine learning based paper organization and scheduling tool

Publication date

2020-01-06

Authors

Moore, Nathan
Mayer, Sven
Molloy, Kevin
Woźniak, Paweł W.ISNI 0000000492960438
Lovo, William
Stewart, Michael

Editors

Advisors

Supervisors

Document Type

Part of book
Open Access logo

License

taverne

Abstract

Organizing and assigning papers into sessions within a large conference is a formidable challenge. Some conference organizers, who are typically volunteers, have utilized event planning software to ensure simple constraints, such as two people can not be scheduled to talk at the same time. In this work, we proposed utilizing natural language processing to find the topics within a corpus of conference submissions and then cluster them together into sessions. As a preliminary evaluation of this technique, we compare session assignments from previous conferences to ones generated with our proposed techniques.

Keywords

Taverne, General Computer Science

Citation

Moore, N, Mayer, S, Molloy, K, Woźniak, P W, Lovo, W & Stewart, M 2020, Post : A machine learning based paper organization and scheduling tool. in GROUP 2020 - Companion of the 2020 ACM International Conference on Supporting Group Work. Association for Computing Machinery, pp. 135-138, 21st ACM International Conference on Supporting Group Work, GROUP 2020, Sanibel Island, United States, 6/01/20. https://doi.org/10.1145/3323994.3369892, conference