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    Mining unordered distance-constrained embedded subtrees

    116113_7648_PUB-CBS-EEB-MC-44991.pdf (5.328Mb)
    Access Status
    Open access
    Authors
    Hadzic, Fedja
    Tan, Henry
    Dillon, Tharam S.
    Date
    2008
    Type
    Conference Paper
    
    Metadata
    Show full item record
    Citation
    Hadzic, 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
    Source Title
    Lecture notes in computer science
    Source Conference
    11th International Conference on Discovery Science (DS 2008)
    DOI
    10.1007/978-3-540-88411-8_26
    ISBN
    9783540884101
    Faculty
    Curtin Business School
    School of Information Systems
    School
    Centre for Extended Enterprises and Business Intelligence
    Remarks

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

    URI
    http://hdl.handle.net/20.500.11937/28805
    Collection
    • Curtin Research Publications
    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.

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    • Razor: Mining distance-constrained embedded subtrees
      Tan, H.; Dillon, Tharam S.; Hadzic, Fedja; Chang, Elizabeth (2006)
      Our work is focused on the task of mining frequent subtrees from a database of rooted ordered labelled subtrees. Previously we have developed an efficient algorithm, MB3 [12], for mining frequent embedded subtrees from a ...
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      Large amount of online information is or can be represented using semi-structured documents, such as XML. The information contained in an XML document can be effectively represented using a rooted ordered labeled tree. ...
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