Meeting Analytics: Creative Activity Support Based on Knowledge Discovery from Discussions

dc.contributor.author Nagao, Katashi
dc.date.accessioned 2017-12-28T00:41:12Z
dc.date.available 2017-12-28T00:41:12Z
dc.date.issued 2018-01-03
dc.description.abstract We are researching a mechanism to promote innovation by supporting discussions based on the premise that innovation results from discussions. Ideas are created and developed mainly by conversations in creative meetings like those in brainstorming. Ideas are also refined in the process of repeated discussions. Our previous research called discussion mining was specifically used to collect various data on meetings (statements and their relationships, presentation materials such as slides, audio and video, and participants’ evaluations on statements). We extracted important statements to be considered especially after the meetings had been held and actions had been undertaken, such as investigations and implementations that were performed in relation to these statements by using the collected data. Here, we present high-probability statements that should lead to innovations during meetings and facilitate creative discussions. We also propose a creative activity support system that should help users to discover and execute essential tasks.
dc.format.extent 10 pages
dc.identifier.doi 10.24251/HICSS.2018.103
dc.identifier.isbn 978-0-9981331-1-9
dc.identifier.uri http://hdl.handle.net/10125/49990
dc.language.iso eng
dc.relation.ispartof Proceedings of the 51st Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Business Intelligence, Analytics and Cognitive: Case Studies and Applications (COGS)
dc.subject Creative activity support, Discussion mining, Innovation acceleration, Machine learning, Meeting analytics
dc.title Meeting Analytics: Creative Activity Support Based on Knowledge Discovery from Discussions
dc.type Conference Paper
dc.type.dcmi Text
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