Skip to main content
SpringerLink
Log in

Mining Dynamic Association Rules in Databases

  • Conference paper
Computational Intelligence and Security (CIS 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3801))

Included in the following conference series:

Abstract

We put forward a new conception, dynamic association rule, which can describe the regularities of changes over time in association rules. The dynamic association rule is different in that it contains not only a support and a confidence but also a support vector and a confidence vector. During the mining process, the data used for mining is divided into several parts according to certain time indicators, such as years, seasons and months, and a support vector and a confidence vector for each rule are generated which show the support and the confidence of the rule in each subsets of the data. By using the two vectors, we can not only find the information about the rules’ changes with time but also predict the tendencies of the rules, which ordinary association rules can not offer.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
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. Agrawal, R., Srikant, R.: Mining sequential patterns. In: Proc. of the 11th Int’l. Conference on Data Engineering, March 3–14 (1995)

    Google Scholar 

  2. Dong, G., Li, J.: Efficient mining of emerging patterns: Discovering trends and differences. In: Proc. of the Fifth Int’l. Conference on Knowledge Discovery and Data Mining, pp. 43–52 (1999)

    Google Scholar 

  3. Au, W.H., Chan, K.C.C.: Fuzzy data mining for discovering changes in association rules over time. In: Proc. of 2002 IEEE Int’l. Conference on Fuzzy Systems, May 2002, pp. 890–895 (2002)

    Google Scholar 

  4. Agrawal, R., Srikant, R.: Fast algorithms for mining association rules in large databases. In: Proc of 20th Int’l. Conference on Very Large Data Bases, September 1994, pp. 487–499 (1994)

    Google Scholar 

  5. Han, J., Kamber, M.: Data Mining Concepts and Techniques. Morgan Kaufmann Publishers, San Fransisco (2000)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. National Key Laboratory of Industrial Control Technology, Zhejiang University, China

    Jinfeng Liu & Gang Rong

Authors
  1. Jinfeng Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Gang Rong
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Microelectronic Instiute, Xidian University, 710071, Xi’an, China

    Yue Hao

  2. Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong

    Jiming Liu

  3. School of Computer Science and Technology, Xidian University, Xi’an, China

    Yuping Wang

  4. Department of Computer Science, Hong Kong Baptist University, Hong Kong,  

    Yiu-ming Cheung

  5. School of Electrical and Electronic Engineering, University of Manchester, UK

    Hujun Yin

  6. Life Science Research Center, School of Electronic Engineering, Xidian University, 710071, Xi’an, Shaanxi, China

    Licheng Jiao

  7. Key Laboratory of Computer Networks and Information Security (Ministry of Education), Xidian University, 710071, Xi’an, China

    Jianfeng Ma

  8. National Laboratory of Antennas and Microwave Technology, Xidian University, 710071, Xi’an, Shanxi, P.R. China

    Yong-Chang Jiao

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Liu, J., Rong, G. (2005). Mining Dynamic Association Rules in Databases. In: Hao, Y., et al. Computational Intelligence and Security. CIS 2005. Lecture Notes in Computer Science(), vol 3801. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11596448_102

Download citation

  • DOI: https://doi.org/10.1007/11596448_102

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30818-8

  • Online ISBN: 978-3-540-31599-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation