Automatic Assignment of Item Weights for Pattern Mining on Data Streams

Show simple item record Koh, Yun Sing en Pears, R en Dobbie, Gillian en
dc.contributor.editor Huang, JZ en
dc.contributor.editor Cao, L en
dc.contributor.editor Srivastava, J en
dc.coverage.spatial Shenzhen, China en 2012-04-10T22:09:02Z en 2011 en
dc.identifier.citation Lecture Notes in Computer Science Volume 6634. Springer-Verlag. 6634: 387-398. 2011 en
dc.identifier.uri en
dc.description.abstract Research in Weighted Association Rule Mining (WARM) has largely concentrated on mining traditional static transactional datasets. Whilst there have been a few attempts at researching WARM in a data stream environment, none have addressed the problem of assigning and adapting weights in the presence of concept drift, which often occurs in a data stream environment. In this research we experiment with two methods of adapting weights; firstly, a simplistic method that recomputes the entire set of weights at fixed intervals, and secondly a method that relies on a distance function that assesses the extent of change in the stream and only updates those items that have had significant change in their patterns of interaction. We show that the latter method is able to maintain good accuracy whilst being several times faster than the former. en
dc.description.uri en
dc.publisher Springer-Verlag en
dc.relation.ispartof 15th Pacific-Asia Conference Knowledge Discovery and Data Mining, PAKDD 2011 en
dc.relation.ispartofseries Lecture Notes in Computer Science Volume 6634 en
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. en
dc.rights.uri en
dc.title Automatic Assignment of Item Weights for Pattern Mining on Data Streams en
dc.type Conference Item en
dc.identifier.doi 10.1007/978-3-642-20841-6_32 en
pubs.begin-page 387 en
pubs.volume 6634 en
dc.rights.holder Copyright: Springer-Verlag en en
pubs.end-page 398 en
pubs.finish-date 2011-05-27 en
pubs.start-date 2011-05-24 en
dc.rights.accessrights en
pubs.subtype Proceedings en
pubs.elements-id 236729 en Science en School of Computer Science en
pubs.record-created-at-source-date 2011-11-01 en

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