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Mining access patterns efficiently from web logs

Publication ,  Conference
Pei, J; Han, J; Mortazavi-Asl, B; Zhu, H
Published in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
January 1, 2000

With the explosive growth of data avaiilable 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.

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Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

ISBN

9783540673828

Publication Date

January 1, 2000

Volume

1805

Start / End Page

396 / 407

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences
 

Citation

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Pei, J., Han, J., Mortazavi-Asl, B., & Zhu, H. (2000). Mining access patterns efficiently from web logs. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1805, pp. 396–407). https://doi.org/10.1007/3-540-45571-x_47
Pei, J., J. Han, B. Mortazavi-Asl, and H. Zhu. “Mining access patterns efficiently from web logs.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 1805:396–407, 2000. https://doi.org/10.1007/3-540-45571-x_47.
Pei J, Han J, Mortazavi-Asl B, Zhu H. Mining access patterns efficiently from web logs. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2000. p. 396–407.
Pei, J., et al. “Mining access patterns efficiently from web logs.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 1805, 2000, pp. 396–407. Scopus, doi:10.1007/3-540-45571-x_47.
Pei J, Han J, Mortazavi-Asl B, Zhu H. Mining access patterns efficiently from web logs. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2000. p. 396–407.
Journal cover image

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

ISBN

9783540673828

Publication Date

January 1, 2000

Volume

1805

Start / End Page

396 / 407

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences