Conversation pattern-based anticipation of teammates' information needs via overhearing

Xiaocong Fan, John Yen

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

5 Scopus citations

Abstract

One research focus of human-centered teamwork is on advanced decision architectures that can help people make effective and timely decisions. This requires distributed team members to effectively establish shared situation awareness and to collaboratively develop explanations on how an unfamiliar situation might have been emerging. One key to achieve this goal is the ability to anticipate others' future information needs and to offer help proactively. In this paper we investigate a novel approach to anticipating teammates' information needs based on stepwise conversation pattern recognition, leveraging the idea of multi-party communication. This approach can be further extended to build a computational model for collaborative story building as needed in Recognition-Primed, naturalistic decision architectures.

Original languageEnglish (US)
Title of host publicationProceedings - 2005 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT'05
Pages316-322
Number of pages7
DOIs
Publication statusPublished - Dec 1 2005
Event2005 IEEE/WIC/ACM International Conference on Intelligent Agent Technology - France, France
Duration: Sep 19 2005Sep 22 2005

Publication series

NameProceedings - 2005 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT'05
Volume2005

Other

Other2005 IEEE/WIC/ACM International Conference on Intelligent Agent Technology
CountryFrance
CityFrance
Period9/19/059/22/05

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All Science Journal Classification (ASJC) codes

  • Engineering(all)

Cite this

Fan, X., & Yen, J. (2005). Conversation pattern-based anticipation of teammates' information needs via overhearing. In Proceedings - 2005 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT'05 (pp. 316-322). [1565560] (Proceedings - 2005 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT'05; Vol. 2005). https://doi.org/10.1109/IAT.2005.58