Abstract
In this paper, we analyze some potential problems in the existing mining algorithms on association rules. These problems are caused by only concerning about its support and confidence, while neglecting to what extent the rule will interest people. At the same time, the existing definition and mining algorithms of association rules does not take into account any negative items, therefore many valuable rules are lost. We hereby introduce the concepts of interest measure and negative item into the definition and evaluation system. Then we modify the existing algorithms so as to use interest measure to generate rules with negative items. At the end of this paper we analyze the new algorithm and prove it to be efficient and feasible.
This paper was funded by the National 863 Projects of China No. 863-306-ZT02-05-1.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Agrawal, R., Imielinski, T., Swami, A. N.: Mining Association Rules between Sets of Items in Large Databases. SIGMOD Conference (1993) 207–216
Zhou, X., Zhu, Y., Shi, B.: A Method for Mining Association Rules Using Interest Measure. ICYCS (1999)
Zuo, W., Liu, J.: Mining Association Rules Involving Positive and Negative Attributes. NDBC (1999.8) 288–292
Piatetsky-Shapiro, G.: Discovery, Analysis, and Presentation of Strong Rules. Knowledge Discovery in Database. AAAI/MIT Press (1991) 229–248
Agrawal, R., Mannila, H., Srikant, R., Toivonen, H., Verkamo, A. I.: Fast Discovery of Assoication Rules. In: Advances in Knowledge Discovery and Data Mining. AAAI/MIT Press (1996) 307–328
Megiddo, N., Srikant, R.: Discovering Predictive Association Rules. KDD (1998) 274–278
Savasere, A., Omiecinski, E., Navathe, S. B.: Mining for Strong Negative Associations in a Large Database of Customer Transactions. ICDE (1998) 494–502
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2000 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zhou, H., Gao, P., Zhu, Y. (2000). Mining Association Rules with Negative Items Using Interest Measure. In: Lu, H., Zhou, A. (eds) Web-Age Information Management. WAIM 2000. Lecture Notes in Computer Science, vol 1846. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45151-X_11
Download citation
DOI: https://doi.org/10.1007/3-540-45151-X_11
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-67627-0
Online ISBN: 978-3-540-45151-8
eBook Packages: Springer Book Archive