Open AccessRule Mining for Dynamic Databases
Author(s) -
Aparna Das,
Dhruba K. Bhattacharyya
Publication year - 2005
Publication title -
ajis. australasian journal of information systems/ajis. australian journal of information systems/australian journal of information systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.351
H-Index - 18
eISSN - 1326-2238
pISSN - 1039-7841
DOI - 10.3127/ajis.v13i1.59
Subject(s) - association rule learning , computer science , scalability , database , data mining , distributed database , join (topology) , mathematics , combinatorics
Association rules identify associations among data items and were introduced in 1993 by Agarwal et al.. Most of the algorithms to find association rules deal with the static databases. There are very few algorithms that deal with dynamic databases. The most classical algorithm to find association rules in dynamic database is Borders algorithm. This paper presents two modified version of the Borders algorithm called Modified Borders. Experimental results show that the modified version performs better than the Borders algorithm in terms of execution time. To address the scalability issue, the paper also proposes a distributed version of the Borders algorithm, called Distributed Borders