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dc.contributor.authorHadzic, Fedja
dc.contributor.editorL. Cao
dc.contributor.editorJ. Huang
dc.contributor.editorJ. Bailey
dc.contributor.editorY. Koh
dc.contributor.editorJ. Luo
dc.date.accessioned2017-01-30T14:06:49Z
dc.date.available2017-01-30T14:06:49Z
dc.date.created2012-03-07T20:01:06Z
dc.date.issued2012
dc.identifier.citationHadzic, Fedja. 2012. A structure preserving flat data format representation for tree-structured data, in Cao, L. and Huang, J. and Bailey, J. and Koh, Y. and Luo, J. (ed), New Frontiers in Applied Data Mining, PAKDD 2011 International Workshops, May 24 2011, pp. 221-233. Shenzhen, China: Springer.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/37719
dc.description.abstract

Mining of semi-structured data such as XML is a popular research topic due to many useful applications. The initial work focused mainly on values associated with tags, while most of recent developments focus on discovering association rules among tree structured data objects to preserve the structural information. Other data mining techniques have had limited use in tree-structured data analysis as they were mainly designed to process flat data format with no need to capture the structural properties of data objects. This paper proposes a novel structure-preserving way for representing tree-structured document instances as records in a standard flat data structure to enable applicability of a wider range of data analysis techniques. The experiments using synthetic and real world data demonstrate the effectiveness of the proposed approach.

dc.publisherSpringer
dc.relation.urihttp://conferences.telecom-bretagne.eu/data/qimie2011/hadzic-informal_QIMIE_2011.pdf
dc.subjectXML mining
dc.subjectdecision tree learning from XML data
dc.subjecttree mining
dc.titleA structure preserving flat data format representation for tree-structured data
dc.typeConference Paper
dcterms.source.startPage221
dcterms.source.endPage233
dcterms.source.titleNew Frontiers in Applied Data Mining
dcterms.source.seriesNew Frontiers in Applied Data Mining
dcterms.source.isbn9783642283192
dcterms.source.conferencePAKDD 2011 International Workshops
dcterms.source.conference-start-dateMay 24 2011
dcterms.source.conferencelocationShenzhen, China
dcterms.source.placeBerlin, Germany
curtin.departmentDepartment of Computing
curtin.accessStatusFulltext not available


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