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dc.contributor.authorHadzic, Fedja
dc.contributor.authorTan, Henry
dc.contributor.authorDillon, Tharam S.
dc.contributor.editorJ-F. Boulicaut
dc.contributor.editorM. R. Berthold
dc.contributor.editorT. Horv�th
dc.date.accessioned2017-01-30T13:07:30Z
dc.date.available2017-01-30T13:07:30Z
dc.date.created2009-02-09T18:01:47Z
dc.date.issued2008
dc.identifier.citationHadzic, Fedja and Tan, Henry and Dillon, Tharam. 2008. Mining unordered distance-constrained embedded subtrees, in Boulicaut, J-F. and Berthold, M.R. and Horváth, T. (ed), 11th International Conference on Discovery Science, Oct 13 2008, pp. 272-283. Budapest, Hungary: Springer
dc.identifier.urihttp://hdl.handle.net/20.500.11937/28805
dc.identifier.doi10.1007/978-3-540-88411-8_26
dc.description.abstract

Frequent subtree mining is an important problem in the area of association rule mining from semi-structured or tree structured documents, often found in many commercial, web and scientific domains. This paper presents the u3Razor algorithm, for mining unordered embedded subtrees where the distance of nodes relative to the root of the subtree needs to be considered. Mining distance-constrained unordered embedded subtrees will have important applications in web information systems, conceptual model analysis and more sophisticated knowledge matching. An encoding strategy is presented to efficiently enumerate candidate unordered embedded subtrees taking the distance of nodes relative to the root of the subtree into account. Both synthetic and real-world datasets were used for experimental evaluation and discussion.

dc.publisherSpringer
dc.titleMining unordered distance-constrained embedded subtrees
dc.typeConference Paper
dcterms.source.startPage272
dcterms.source.endPage283
dcterms.source.titleLecture notes in computer science
dcterms.source.seriesLecture notes in computer science
dcterms.source.isbn9783540884101
dcterms.source.conference11th International Conference on Discovery Science (DS 2008)
dcterms.source.conference-start-date13 Oct 2008
dcterms.source.conferencelocationBudapest, Hungary
dcterms.source.placeBerlin / Heidelberg
curtin.note

The original publication is available at http://www.springerlink.com

curtin.departmentCentre for Extended Enterprises and Business Intelligence
curtin.accessStatusOpen access
curtin.facultyCurtin Business School
curtin.facultySchool of Information Systems


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