Skip to main content

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1983))

Abstract

We consider the problem of mining sequential patterns over several large databases placed at different sites. Experiments carried out on synthetic data generated within a simulation environment are reported. We use several agents capable to communicate with a temporal ontology.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. R. Agrawal and R. Srikant: Mining sequential patterns. In International Conference on Database Engineering, pages 3–14, Washington, D.C., 1995. IEEE Computer Society Press.

    Google Scholar 

  2. C. Bettini, X. Sean Wang, and S. Jajodia: Testing complex temporal relationships involving multiple granularities and its application to data mining. In Proceedings of the Fifteenth ACM Symposium on Principles of Database Systems, volume 15, pages 68–78, New York, NY 10036, USA, 1996. ACM Press.

    Google Scholar 

  3. D. W. Cheung, V. T. Ng, A. W. Fu, and Y. Fu: Efficient mining of association rules in distributed databases. IEEE Transactions on Knowledge and Data Engineering, pages 911–922, Dec 1996.

    Google Scholar 

  4. Luc Dehaspe and Hannu Toivonen: Discovery of frequent Datalog patterns. Data Mining and Knowledge Discovery, 3, 1999.

    Google Scholar 

  5. H. Mannila, H. Toivonen, and A. I. Verkamo: Discovering frequent episodes in sequences. In U. M. Fayyad and R. Uthurusamy, editors, Proceedings of the First International Conference on Knowledge Discovery and Data Mining (KDD-95), pages 210–215, Montreal, Canada, August 1995. AAAI Press.

    Google Scholar 

  6. F. Masseglia, F. Cathala, and P. Poncelet: The PSP approach for mining sequential patterns. In J. M. Zytkow and M. Quafafou, editors, Principles of Data Mining and Knowledge Discovery, LNAI 1510, pages 176–184, 1998.

    Google Scholar 

  7. Ryszard S. Michalski and Kenneth A. Kaufman: Data mining and knowledge discovery: A review of issues and a multistrategy approach. In R. S. Michalski, I. Bratko, and M. Kubat, editors, Machine Learning and Data Mining, pages 71–112. John Wiley, 1998.

    Google Scholar 

  8. T. M. Mitchell: Machine learning and data mining. Communications of the ACM, 42(11), Nov 1999.

    Google Scholar 

  9. R. Srikant and R. Agrawal: Mining sequential patterns: Generalizations and performance improvements. In Proceedings of the 5th International Conference on Extending Database Technology, Avignon, France, 1996.

    Google Scholar 

  10. S. Stolfo, A. Prodromidis, S. Tselepsis, W. Lee, D. Fan, and P. Chan: JAM: Java agents for meta-learning over distributed databases. In Proceedings of the 3rd International Conference on Knowledge Discovery and Data Mining, 1997.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2000 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Letia, I.A., Craciun, F., Köpe, Z., Lelutiu, A. (2000). First Experiments for Mining Sequential Patterns on Distributed Sites with Multi-Agents. In: Leung, K.S., Chan, LW., Meng, H. (eds) Intelligent Data Engineering and Automated Learning — IDEAL 2000. Data Mining, Financial Engineering, and Intelligent Agents. IDEAL 2000. Lecture Notes in Computer Science, vol 1983. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44491-2_28

Download citation

  • DOI: https://doi.org/10.1007/3-540-44491-2_28

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-41450-6

  • Online ISBN: 978-3-540-44491-6

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics