Mining frequent web access patterns with partial enumeration

ABSTRACT

In this paper, we extend the pattern-growth web access pattern mining algorithms [1, 2, 3] with partial enumeration. The extended algorithm can grow the frequent patterns with more than one symbol at a time and unifies the pattern-growth and apriori algorithms [4]. The experimental results show that for the databases of long sequences, the best performance is neither given by the pattern-growth algorithms nor by the full apriori enumeration algorithms, but rather by the mining with partial enumeration in the middle.

REFERENCES

• 1: Jian Pei , Jiawei Han , Behzad Mortazavi-Asl , Hua Zhu, Mining Access Patterns Efficiently from Web Logs, Proceedings of the 4th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Current Issues and New Applications, p.396-407, April 18-20, 2000
• 2: C. I. Ezeife , Yi Lu, Mining Web Log Sequential Patterns with Position Coded Pre-Order Linked WAP-Tree, Data Mining and Knowledge Discovery, v.10 n.1, p.5-38, January 2005 [doi>10.1007/s10618-005-0248-3]
• 3: Peiyi Tang, Markus P. Turkia, and Kyle A. Gallivan. Mining web access patterns with first-occurrence linked wap-tree. Technical Report titus.compsci.ualr.edu/~ptang/papers/flwap-rpt.pdf, Department of Computer Science, University of Arkansas at Little Rock, 2006.
• 4: Jay Ayres , Jason Flannick , Johannes Gehrke , Tomi Yiu, Sequential PAttern mining using a bitmap representation, Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining, July 23-26, 2002, Edmonton, Alberta, Canada [doi>10.1145/775047.775109]
• 5: Myra Spiliopoulou , Lukas Faulstich, WUM - A Tool for WWW Ulitization Analysis, Selected papers from the International Workshop on The World Wide Web and Databases, p.184-103, March 27-28, 1998
• 6: C. I. Ezeife and Min Chen. Mining web sequential patterns incrementally with revised PLWAP tree. In Proceedings of the 5th International Conference on Web-Age Information Management(WAIM 2004), pages pp. 539--548, 2004.
• 7: Peiyi Tang and Markus P. Turkia. Mining frequent web access patterns with partial enumeration. Technical Report titus.compsci.ualr.edu/~ptang/papers/fwap-perpt.pdf, Department of Computer Science, University of Arkansas at Little Rock, 2006.
• 8: Ramakrishnan Srikant , Rakesh Agrawal, Mining Sequential Patterns: Generalizations and Performance Improvements, Proceedings of the 5th International Conference on Extending Database Technology: Advances in Database Technology, p.3-17, March 25-29, 1996
• 9: Peiyi Tang , Markus P. Turkia, Mining frequent itemsets with partial enumeration, Proceedings of the 44th annual Southeast regional conference, March 10-12, 2006, Melbourne, Florida [doi>10.1145/1185448.1185489]
• 10: Cludia Antunes and Arlindo L. Oliveira. Sequential pattern mining algorithms: Trade-offs between speed and memory. In Proceedings of the Second Workshop on Mining Graphs, Trees and Sequences at the 15th European ECML and the 8th European PKDD, 2004.
• 11: Cludia Antunes and Arlindo L. Oliveira. Generalization of pattern-growth methods for sequential pattern mining with gap constraints. In Proceedings of the 2003 International Conference on Machine Learning and Data Mining, pages 239--251, 2003.

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.2 DATABASE MANAGEMENT
      H.2.8 Database applications
          Subjects: Data mining

Additional Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.4 Systems and Software
          Subjects: User profiles and alert services
  H.5 INFORMATION INTERFACES AND PRESENTATION (I.7)
      H.5.4 Hypertext/Hypermedia
          Subjects: Navigation

  I. Computing Methodologies
  I.5 PATTERN RECOGNITION
      I.5.2 Design Methodology
          Subjects: Pattern analysis

General Terms:
Algorithms, Design