Mining dynamic databases by weighting

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dc.contributor.author Zhang, S
dc.contributor.author Liu, L
dc.date.accessioned 2010-06-18T02:06:58Z
dc.date.issued 2003
dc.identifier.citation Acta Cybernetica, 2003, 16 (1), pp. 179 - 205
dc.identifier.issn 0324-721X
dc.identifier.other C1 en_US
dc.identifier.uri http://hdl.handle.net/10453/12382
dc.description.abstract A dynamic database is a set of transactions, in which the content and the size can change over time. There is an essential difference between dynamic database mining and traditional database mining. This is because recently added transactions can be more 'interesting' than those inserted long ago in a dynamic database. This paper presents a method for mining dynamic databases. This approach uses weighting techniques to increase efficiency, enabling us to reuse frequent itemsets mined previously. This model also considers the novelty of itemsets when assigning weights. In particular, this method can find a kind of new patterns from dynamic databases, referred to trend patterns. To evaluate the effectiveness and efficiency of the proposed method, we implemented our approach and compare it with existing methods.
dc.language eng
dc.title Mining dynamic databases by weighting
dc.type Journal Article
dc.parent Acta Cybernetica
dc.journal.volume 1
dc.journal.volume 16
dc.journal.number 1 en_US
dc.publocation Szeged, Hungary en_US
dc.publocation USA
dc.identifier.startpage 179 en_US
dc.identifier.endpage 205 en_US
dc.cauo.name FEIT.School of Software en_US
dc.conference Verified OK en_US
dc.conference International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing
dc.for 0802 Computation Theory and Mathematics
dc.personcode 020030
dc.personcode 021010
dc.percentage 100 en_US
dc.classification.name Computation Theory and Mathematics en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom en_US
dc.date.activity en_US
dc.date.activity 2003-10-16
dc.location.activity en_US
dc.location.activity Lubeck, Germany
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
utslib.copyright.status Open Access
utslib.copyright.date 2015-04-15 12:23:47.074767+10
pubs.consider-herdc true
utslib.collection.history General (ID: 2)


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