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    Knowledge analyisis with tree patterns

    20764_downloaded_stream_220.pdf (335.1Kb)
    Access Status
    Open access
    Authors
    Hadzic, Fedja
    Dillon, Tharam S.
    Chang, Elizabeth
    Date
    2008
    Type
    Conference Paper
    
    Metadata
    Show full item record
    Citation
    Hadzic, Fedja and Dillon, Tharam and Chang, Elizabeth. 2008. : Knowledge analyisis with tree patterns, in Sprague, Ralph H. (ed), 41st Hawaii International Conference on Systems and Sciences, 07 Jan 2008, pp. 369-369. Hawaii, USA: IEEE Xplore.
    Source Title
    Hawaii International Conference on System Sciences, Proceedings of the 41st Annual
    Source Conference
    41st Hawaii International Conference on Systems and Sciences
    DOI
    10.1109/HICSS.2008.226
    Faculty
    Curtin Business School
    School
    Centre for Extended Enterprises and Business Intelligence
    Remarks

    Copyright 2008 IEEE

    This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

    URI
    http://hdl.handle.net/20.500.11937/16420
    Collection
    • Curtin Research Publications
    Abstract

    Tree-structured knowledge representations are increasingly being used since the relationships between data objects can be represented in a more meaningful way. A number of tree mining algorithms were developed for mining different subtree types using different parameters. At this point in research it would be useful to discuss what kind of sub-problems can be solved within the current tree mining framework. In this paper we provide a general overview of the development in the area of tree mining and discuss motivations and useful application areas for each development. Implications of using different tree mining parameters and constraints are discussed. Such an overview will be particularly useful for those not so familiar with the area of tree mining as it can reveal useful applications within their domain of interest. It gives guidance as to which type of tree mining will be most useful for their particular application.

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