Abstract
With the explosive growth of data available on the World Wide Web, discovery and analysis of useful information from the World Wide Web becomes a practical necessity. Web access pattern, which is the sequence of accesses pursued by users frequently, is a kind of interesting and useful knowledge in practice.
In this paper, we study the problem of mining access patterns from Web logs efficiently. A novel data structure, called Web access pattern tree, or WAP-tree in short, is developed for efficient mining of access patterns from pieces of logs. The Web access pattern tree stores highly compressed, critical information for access pattern mining and facilitates the development of novel algorithms for mining access patterns in large set of log pieces. Our algorithm can find access patterns from Web logs quite efficiently. The experimental and performance studies show that our method is in general an order of magnitude faster than conventional methods.
The work was supported in part by the Natural Sciences and Engineering Research Council of Canada (grant NSERC-A3723), the Networks of Centres of Excellence of Canada (grant NCE/IRIS-3), and the Hewlett-Packard Lab.
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Pei, J., Han, J., Mortazavi-asl, B., Zhu, H. (2000). Mining Access Patterns Efficiently from Web Logs. In: Terano, T., Liu, H., Chen, A.L.P. (eds) Knowledge Discovery and Data Mining. Current Issues and New Applications. PAKDD 2000. Lecture Notes in Computer Science(), vol 1805. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45571-X_47
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DOI: https://doi.org/10.1007/3-540-45571-X_47
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