A two-level information filtering model for warning systems

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dc.contributor.author Ma, J
dc.contributor.author Lu, J
dc.contributor.author Zhang, G
dc.contributor.editor Bonissone, PP
dc.date.accessioned 2009-11-09T05:35:51Z
dc.date.issued 2007-01
dc.identifier.citation IEEE Symposium on Computational Intelligence in Multi-criteria Decision-Making, 2007, pp. 354 - 359
dc.identifier.isbn 1-4244-0698-6
dc.identifier.other E1 en_US
dc.identifier.uri http://hdl.handle.net/10453/2529
dc.description.abstract Information filtering is an important component in warning systems. This paper proposes a two-level information filtering model for generating warning information. In this model, information is represented by n-tuple, whose elements are values of information features. The features of information are divided into critical and uncritical features. Within this model, the collected information is filtered in two stages by users at different levels. At the first stage, exceptions are separated from normal information. And at the second stage, critical exceptions are separated from uncritical information. To illustration the proposed model, an example is discussed
dc.publisher IEEE
dc.relation.isbasedon 10.1109/MCDM.2007.369113
dc.subject alarm systems information filtering
dc.subject alarm systems information filtering
dc.title A two-level information filtering model for warning systems
dc.type Conference Proceeding
dc.parent IEEE Symposium on Computational Intelligence in Multi-criteria Decision-Making
dc.journal.number en_US
dc.publocation USA en_US
dc.publocation USA
dc.publocation USA
dc.publocation USA
dc.identifier.startpage 354 en_US
dc.identifier.endpage 359 en_US
dc.cauo.name FEIT.School of Software en_US
dc.conference Verified OK en_US
dc.conference IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making
dc.conference IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making
dc.conference IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making
dc.conference.location Hawaii, USA en_US
dc.for 0801 Artificial Intelligence and Image Processing
dc.personcode 999403 en_US
dc.personcode 001038 en_US
dc.personcode 020014 en_US
dc.percentage 100 en_US
dc.classification.name Artificial Intelligence and Image Processing en_US
dc.classification.type FOR-08 en_US
dc.custom IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making en_US
dc.date.activity 20070401 en_US
dc.date.activity 2007-04-01
dc.date.activity 2007-04-01
dc.date.activity 2007-04-01
dc.location.activity Hawaii, USA en_US
dc.location.activity Hawaii, USA
dc.location.activity Hawaii, USA
dc.location.activity Hawaii, USA
dc.description.keywords alarm systems information filtering en_US
dc.description.keywords alarm systems information filtering
dc.description.keywords alarm systems information filtering
dc.description.keywords alarm systems information filtering
dc.staffid 020014 en_US
pubs.embargo.period Not known
pubs.organisational-group /University of Technology Sydney
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group /University of Technology Sydney/Strength - Quantum Computation and Intelligent Systems


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