Subscribe Now Subscribe Today
Science Alert
 
Blue
   
Curve Top
Asian Journal of Information Management
  Year: 2007 | Volume: 1 | Issue: 1 | Page No.: 19-26
DOI: 10.3923/ajim.2007.19.26
 
Facebook Twitter Digg Reddit Linkedin StumbleUpon E-mail

Fast Algorithm for Mining Multi-Level Association Rules in Large Databases

R.S. Thakur, R.C. Jain and K.R. Pardasani

Abstract:
Data Mining refers to extracting knowledge from large amount of data. The Discovery of interesting association relationships among huge amount of data will help marketing, decision making and business management. Previous studies on mining association rules find rules at single level. However mining association rules at multiple-level may lead to the discovery of more specific and concrete knowledge from data. In this research we propose a new algorithms for mining multi-level association rules in large databases. It uses concept of counting inference approach that allows performing as few support counts as possible. This new method reduces database scan at each concept level than the other existing algorithm for multi-level association rule mining from large databases.
PDF Fulltext XML References Citation Report Citation
 RELATED ARTICLES:
  •    CFD-Mine: An Efficient Algorithm For Discovering Functional and Conditional Functional Dependencies
  •    Connection Subgraphs: A Survey
  •    Extracting Association Rules from Hiv Infected Patients’ Treatment Dataset
How to cite this article:

R.S. Thakur, R.C. Jain and K.R. Pardasani, 2007. Fast Algorithm for Mining Multi-Level Association Rules in Large Databases . Asian Journal of Information Management, 1: 19-26.

DOI: 10.3923/ajim.2007.19.26

URL: https://scialert.net/abstract/?doi=ajim.2007.19.26

COMMENTS
26 August, 2009
karamsi bhaskar naik:
dear sir ,we saw aprior algorithm for finding the transaction in d/b.
i would to know what is the algorithm is implemented new one can u mail me ,as i am requesting u please...
COMMENT ON THIS PAPER
 
 
 

 

 
 
 
 
 
 
 
 
 

 
 
 
 
 

Curve Bottom