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Journal of Intelligent Information Systems 12, 6173 (1999) c 1999 Kluwer Academic Publishers. Manufactured in The Netherlands.
 

Summary: Journal of Intelligent Information Systems 12, 6173 (1999)
c 1999 Kluwer Academic Publishers. Manufactured in The Netherlands.
Borders: An Efficient Algorithm for Association
Generation in Dynamic Databases
YONATAN AUMANN aumann@cs.biu.ac.il
RONEN FELDMAN feldman@cs.biu.ac.il
ORLY LIPSHTAT okatz@cs.biu.ac.il
Department of Mathematics and Computer Science, Bar-Ilan University, Ramat-Gan 52900, Israel
HEIKKI MANILLA Mannila@cs.helsinki.fi
Department of Computer Science, University of Helsinki, Helsinki, Finland
Abstract. We consider the problem of finding association rules in a database with binary attributes. Most
algorithms for finding such rules assume that all the data is available at the start of the data mining session. In
practice, the data in the database may change over time, with records being added and deleted. At any given time,
the rules for the current set of data are of interest. The naive, and highly inefficient, solution would be to rerun
the association generation algorithm from scratch following the arrival of each new batch of data. This paper
describes the Borders algorithm, which provides an efficient method for generating associations incrementally,
from dynamically changing databases. Experimental results show an improved performance of the new algorithm
when compared with previous solutions to the problem.
Keywords: association rules, knowledge discovery, data mining
1. Introduction

  

Source: Aumann, Yonatan - Computer Science Department, Bar Ilan University

 

Collections: Computer Technologies and Information Sciences