Publication Type
Conference Paper
Version
submittedVersion
Publication Date
10-2001
Abstract
Association rule mining has received broad research in the academic and wide application in the real world. As a result, many variations exist and one such variant is the mining of multi-level rules. The mining of multi-level rules has proved to be useful in discovering important knowledge that conventional algorithms such as Apriori, SETM, DIC etc., miss. However, existing techniques for mining multi-level rules have failed to take into account the recurrence relationship that can occur in a transaction during the translation of an atomic item to a higher level representation. As a result, rules containing recurrent items go unnoticed. In this paper, we consider the notion of `quantity' to an item, and present an algorithm based on an extension of the FP-Tree to find association rules with recurrent items at multiple concept levels.
Discipline
Databases and Information Systems | Numerical Analysis and Scientific Computing
Publication
Third International Conference on Information Communications and Signal Processing (ICICS 2001)
ISBN
9781450309189
Publisher
ACM
City or Country
Singapore, Oct 15-18
Citation
ONG, Kok-Leong; NG, Wee-Keong; and LIM, Ee Peng.
Mining multi-level rules with recurrent items using FP'-Tree. (2001). Third International Conference on Information Communications and Signal Processing (ICICS 2001).
Available at: https://ink.library.smu.edu.sg/sis_research/904
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.16.4540
Included in
Databases and Information Systems Commons, Numerical Analysis and Scientific Computing Commons