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2000 | OriginalPaper | Buchkapitel

Mining Access Patterns Efficiently from Web Logs

verfasst von : Jian Pei, Jiawei Han, Behzad Mortazavi-asl, Hua Zhu

Erschienen in: Knowledge Discovery and Data Mining. Current Issues and New Applications

Verlag: Springer Berlin Heidelberg

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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.

Metadaten
Titel
Mining Access Patterns Efficiently from Web Logs
verfasst von
Jian Pei
Jiawei Han
Behzad Mortazavi-asl
Hua Zhu
Copyright-Jahr
2000
Verlag
Springer Berlin Heidelberg
DOI
https://doi.org/10.1007/3-540-45571-X_47

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