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    Applications of concurrent access patterns in web usage mining

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    Authors
    Lu, Jing
    Keech, Malcolm
    Wang, Cuiqing
    Affiliation
    University of Bedfordshire
    Issue Date
    2013-08
    Subjects
    web access patterns (WAP) post-processing
    concurrent access patterns (CAP)
    CAP mining and modelling
    WAP pruning
    knowledge discovery
    web access patterns
    
    Metadata
    Show full item record
    Other Titles
    Data warehousing and knowledge discovery
    Abstract
    This paper builds on the original data mining and modelling research which has proposed the discovery of novel structural relation patterns, applying the approach in web usage mining. The focus of attention here is on concurrent access patterns (CAP), where an overarching framework illuminates the methodology for web access patterns post-processing. Data pre-processing, pattern discovery and patterns analysis all proceed in association with access patterns mining, CAP mining and CAP modelling. Pruning and selection of access patterns takes place as necessary, allowing further CAP mining and modelling to be pursued in the search for the most interesting concurrent access patterns. It is shown that higher level CAPs can be modelled in a way which brings greater structure to bear on the process of knowledge discovery. Experiments with real-world datasets highlight the applicability of the approach in web navigation.
    Citation
    Lu, J., Keech, M., Wang, C., French, T. (2013) 'Applications of Concurrent Access Patterns in Web Usage Mining' 15th International Conference on Data Warehousing and Knowledge Discovery, 26th-29th August 2013, Prague, Czech Republic.
    Publisher
    Springer
    Journal
    Lecture notes in computer science
    URI
    http://hdl.handle.net/10547/333821
    DOI
    10.1007/978-3-642-40131-2_30
    Additional Links
    http://link.springer.com/chapter/10.1007/978-3-642-40131-2_30
    Type
    Conference papers, meetings and proceedings
    Language
    en
    ISBN
    9783642401312
    ae974a485f413a2113503eed53cd6c53
    10.1007/978-3-642-40131-2_30
    Scopus Count
    Collections
    Centre for Research in Distributed Technologies (CREDIT)

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