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    Implications of frequent subtree mining using hybrid support definitions

    Access Status
    Open access via publisher
    Authors
    Hadzic, Fedja
    Tan, H.
    Dillon, Tharam S.
    Chang, Elizabeth
    Date
    2007
    Type
    Book Chapter
    
    Metadata
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    Citation
    Hadzic, Fedja and Tan, H. and Dillon, Tharam S. and Chang, Elizabeth. 2007. Implications of frequent subtree mining using hybrid support definitions, in Zanasi, A. and Brebbia, C.A. and Ebecken, N.F.F. (ed), Data mining VII: data, text, and web mining and their business applications, pp. 13-23. Southampton, UK: WIT Press.
    Source Title
    Data mining VII: data, text, and web mining and their business applications
    DOI
    10.2495/DATA070021
    Faculty
    Curtin Business School
    School of Information Systems
    School
    Centre for Extended Enterprises and Business Intelligence
    URI
    http://hdl.handle.net/20.500.11937/17005
    Collection
    • Curtin Research Publications
    Abstract

    Frequent subtree mining has found many useful applications in areas where the domain knowledge is presented in a tree structured form, such as bioinformatics, web mining, scientific knowledge management etc. It involves the extraction of a set of frequent subtrees from a tree structured database, with respect to the user specified minimum support. Up to date, the commonly used support definitions are occurrence match and transaction based support. There are some application areas where using either of these support definitions would not provide the desired information automatically, but instead further querying on the extracted patterns needs to take place. This has motivated us to develop a hybrid support definition that constrains the kind of patterns to be extracted and provides additional information not provided by previous support definitions. This would simplify some of the reasoning process which commonly takes place in certain applications. In this paper we demonstrate the need for the hybrid support definition by presenting some applications of tree mining where traditional support definitions would fall short in providing the desired information. We have extended our previous tree mining algorithms to mine frequent subtrees using the hybrid support definition. Using real-world and synthetic data sets we demonstrate the effectiveness of the method, and further implications for reasoning with the extracted patterns.

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