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Mining balanced patterns in web access data. (English) Zbl 1157.68449
Gammerman, A. (ed.), Artificial intelligence and applications. Machine learning. As part of the 26th IASTED international multi-conference on applied informatics. Calgary: International Association of Science and Technology for Development (IASTED); Anaheim, CA: Acta Press (ISBN 978-0-88986-710-9/CD-ROM). 104-109 (2008).
Summary: In web access analysis of a large-scale website the behaviour of visitors accessing the website is examined. An example instance of a pattern is if a visitor accesses the same parts of the website every seven days; we will call such types of patterns balanced patterns.
We define balanced patterns using standard deviation and average. We propose a new approach for pruning such patterns. In comparison with related work the required algorithm and definitions will be relatively simple. Furthermore, the new pruning threshold is intuitive from an analysts perspective.
For the entire collection see [Zbl 1154.68012].
MSC:
68T10 Pattern recognition, speech recognition
68T05 Learning and adaptive systems in artificial intelligence
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