Enhancing scientific collaboration through knowledge base population and linking for meetings

Ning Gao, Mark Dredze, Douglas W. Oard

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Recent research on scientific collaboration shows that distributed interdisciplinary collaborations report comparatively poor outcomes, and the inefficiency of the coordination mechanisms is partially responsible for the problems. To improve information sharing between past collaborators and future team members, or reuse of collaboration records from one project by future researchers, this paper describes systems that automatically construct a knowledge base of the meetings from the calendars of participants, and that then link reference to those meetings found in email messages to the corresponding meeting in the knowledge base. This is work in progress in which experiments with a publicly available corporate email collection with calendar entries show that the knowledge base population function achieves high precision (0.98, meaning that almost all knowledge base entities are actually meetings) and that the accuracy of the linking from email messages to knowledge base entries (0.90) is already quite good.

Original languageEnglish (US)
Title of host publicationProceedings of the 51st Annual Hawaii International Conference on System Sciences, HICSS 2018
EditorsTung X. Bui
PublisherIEEE Computer Society
Pages597-606
Number of pages10
ISBN (Electronic)9780998133119
StatePublished - 2018
Event51st Annual Hawaii International Conference on System Sciences, HICSS 2018 - Big Island, United States
Duration: Jan 2 2018Jan 6 2018

Publication series

NameProceedings of the Annual Hawaii International Conference on System Sciences
Volume2018-January
ISSN (Print)1530-1605

Conference

Conference51st Annual Hawaii International Conference on System Sciences, HICSS 2018
Country/TerritoryUnited States
CityBig Island
Period1/2/181/6/18

ASJC Scopus subject areas

  • General Engineering

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