A two-level information filtering model in generating warning information

Jun, M; Jie, L; Guangquan, Z

A two-level information filtering model in generating warning information

Jun, M Jie, L

Guangquan, Z

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Publication Type:: Conference Proceeding
Citation:: Proceedings of the 2007 IEEE Symposium on Computational Intelligence in Multicriteria Decision Making, MCDM 2007, 2007, pp. 354 - 359
Issue Date:: 2007-09-25

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Field	Value	Language
dc.contributor.author	Jun, M	en_US
dc.contributor.author	Jie, L https://orcid.org/0000-0003-0690-4732	en_US
dc.contributor.author	Guangquan, Z	en_US
dc.date.issued	2007-09-25	en_US
dc.identifier.citation	Proceedings of the 2007 IEEE Symposium on Computational Intelligence in Multicriteria Decision Making, MCDM 2007, 2007, pp. 354 - 359	en_US
dc.identifier.isbn	1424407028	en_US
dc.identifier.isbn	9781424407026	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. ©2007 IEEE.	en_US
dc.relation	http://purl.org/au-research/grants/arc/DP0559213
dc.relation.ispartof	Proceedings of the 2007 IEEE Symposium on Computational Intelligence in Multicriteria Decision Making, MCDM 2007	en_US
dc.relation.isbasedon	10.1109/MCDM.2007.369113	en_US
dc.title	A two-level information filtering model in generating warning information	en_US
dc.type	Conference Proceeding
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
dc.location.activity	Hawaii, USA	en_US
pubs.embargo.period	Not known	en_US
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/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

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. ©2007 IEEE.

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http://hdl.handle.net/10453/2529