An XML-Enabled Association Rule Framework

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dc.contributor.author Feng, L
dc.contributor.author Dillon, TS
dc.contributor.author Weigand, H
dc.contributor.author Chang, E
dc.contributor.editor Marik, V
dc.contributor.editor Retschitzegger, W
dc.contributor.editor Stepankova, O
dc.date.accessioned 2009-11-09T02:45:28Z
dc.date.issued 2003-01
dc.identifier.citation Database and Expert Systems Applications, 2003, pp. 88 - 97
dc.identifier.issn 0302-9743
dc.identifier.other E1 en_US
dc.identifier.uri http://hdl.handle.net/10453/1826
dc.description.abstract With the sheer amount of data stored, presented and exchanged using XML nowadays, the ability to extract knowledge from XML data sources becomes increasingly important and desirable. This paper aims to integrate the newly emerging XML technology with data mining technology, using association rule mining as a case in point. Compared with traditional association mining in the well-structured world (e.g., relational databases), mining from XML data is faced with more challenges due to the inherent flexibilities of XML in both structure and semantics. The primary challenges include 1) a more complicated hierarchical data structure; 2) an ordered data context; and 3) a much bigger data size. To tackle these challenges, in this paper, we propose an extended XML-enabled association rule framework, which is flexible and powerful enough to represent both simple and complex structured association relationships inherent in XML data.
dc.publisher Springer-Verlag Berlin Heidelberg
dc.relation.isbasedon 10.1007/978-3-540-45227-0_10
dc.title An XML-Enabled Association Rule Framework
dc.type Conference Proceeding
dc.parent Database and Expert Systems Applications
dc.journal.number en_US
dc.publocation Germany en_US
dc.identifier.startpage 88 en_US
dc.identifier.endpage 97 en_US
dc.cauo.name FEIT.School of Systems, Management and Leadership en_US
dc.conference Verified OK en_US
dc.conference International Conference on Database and Expert Systems Applications
dc.conference.location Prague, Czech Republic en_US
dc.for 0801 Artificial Intelligence and Image Processing
dc.personcode 030567
dc.percentage 100 en_US
dc.classification.name Artificial Intelligence and Image Processing en_US
dc.classification.type FOR-08 en_US
dc.custom International Conference on Database and Expert Systems Applications en_US
dc.date.activity 20030901 en_US
dc.date.activity 2003-09-01
dc.location.activity Prague, Czech Republic en_US
dc.description.keywords association rule, semi-structure, XML 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/Faculty of Engineering and Information Technology/School of Software
utslib.copyright.status Closed Access
utslib.copyright.date 2015-04-15 12:17:09.805752+10
utslib.collection.history Closed (ID: 3)
utslib.collection.history School of Software (ID: 337)


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