Anytime Mining for Multi-User Applications

No, C

Anytime Mining for Multi-User Applications

No, C

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Publisher:: Institute of Electrical and Electronics Engineers
Publication Type:: Journal Article
Citation:: No, C. 2002 'Anytime Mining for Multi-User Applications', IEEE Transactions on Systems, Man and Cybernetics (Part A), vol. 32, no. 4, pp. 515-521.
Issue Date:: 2002

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Field	Value	Language
dc.contributor.author	No, C	en_US
dc.date.accessioned	2009-12-21T03:52:35Z
dc.date.available	2009-12-21T03:52:35Z
dc.date.issued	2002	en_US
dc.identifier	2004002924	en_US
dc.identifier.citation	No, C. 2002 'Anytime Mining for Multi-User Applications', IEEE Transactions on Systems, Man and Cybernetics (Part A), vol. 32, no. 4, pp. 515-521.	en_US
dc.identifier.issn	1083-4427	en_US
dc.identifier.other	C1	en_US
dc.identifier.uri	http://hdl.handle.net/10453/5766
dc.description.abstract	Database systems have been designed to serve multiusers in real-world applications. There are essential differences between mono- and multi-user applications when a database is very large. Therefore, this paper presents an “anytime” framework for mining very large databases which are shared by multi-users. Anytime mining has been designed to generate approximate results such that these results can be accessed at any time while the system is autonomously mining a database.	en_US
dc.publisher	Institute of Electrical and Electronics Engineers	en_US
dc.relation.ispartof	IEEE Transactions on Systems, Man and Cybernetics (Part A)	en_US
dc.relation.isbasedon	http://dx.doi.org/10.1109/TSMCA.2002.804793	en_US
dc.title	Anytime Mining for Multi-User Applications	en_US
dc.type	Journal article
utslib.citation.volume	32	en_US
utslib.citation.number	4	en_US
utslib.location	Piscataway, USA	en_US
utslib.citation.startpage	515	en_US
utslib.citation.endpage	521	en_US
utslib.identifier.org	Information Technology	en_US
utslib.copyright.status	closed_access

Abstract:

Database systems have been designed to serve multiusers in real-world applications. There are essential differences between mono- and multi-user applications when a database is very large. Therefore, this paper presents an “anytime” framework for mining very large databases which are shared by multi-users. Anytime mining has been designed to generate approximate results such that these results can be accessed at any time while the system is autonomously mining a database.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/5766