Metarule-Guided Mining of Multi-Dimensional Association RulesUsing Data Cubes

Micheline Kamber; Jiawei Han; Jenny Y. Chiang

Abstract

In this paper, we employ a novel approach to metarule-guided, multi-dimensional association rule mining which explores a data cube structure. We propose algorithms for metarule-guided mining: given a metarule containing p predicates, we compare mining on an n-dimensional (n-D) cube structure (where p &lt; n) with mining on smaller multiple pdimensional cubes. In addition, we propose an efficient method for precomputing the cube, which takes into account the constraints imposed by the given metarule.

Keywords

Association rule learningCube (algebra)Data cubeData miningComputer scienceEfficient algorithmAlgorithmMathematicsCombinatorics

Affiliated Institutions

Simon Fraser University CA

Related Publications

Finding interesting rules from large sets of discovered association rules

Mika Klemettinen , Heikki Mannila , P. Ronkainen +2 more

Association rules, introduced by Agrawal, Imielinski, and Swami, are rules of the form “for 90% of the rows of the relation, if the row has value 1 in the columns in set W, then...

1994 717 citations

Implementing data cubes efficiently

Venky Harinarayan , Anand Rajaraman , Jeffrey D. Ullman

Decision support applications involve complex queries on very large databases. Since response times should be small, query optimization is critical. Users typically view the dat...

1996 1161 citations

Mining association rules between sets of items in large databases

Rakesh Agrawal , Tomasz Imieliński , Arun Swami

We are given a large database of customer transactions. Each transaction consists of items purchased by a customer in a visit. We present an efficient algorithm that generates a...

1993 14674 citations

Mining frequent patterns without candidate generation

Jiawei Han , Jian Pei , Yiwen Yin

Mining frequent patterns in transaction databases, time-series databases, and many other kinds of databases has been studied popularly in data mining research. Most of the previ...

2000 ACM SIGMOD Record 6285 citations

An Efficient Algorithm for Mining Association Rules in Large Databases

Ashoka Savasere , Edward Omiecinski , Shamkant B. Navathe

Mining for association rules between items in a large database of sales transactions has been described as an important database mining problem. In this paper we present an effi...

1995 1598 citations

Publication Info

Year: 1999
Type: article
Pages: 207-210
Citations: 209
Access: Closed

External Links

Citation Metrics

209

OpenAlex

Cite This

APA Style

                            
                                    Micheline Kamber, 
                                
                                    Jiawei Han, 
                                
                                    Jenny Y. Chiang
                                
                            (1999). 
                            Metarule-Guided Mining of Multi-Dimensional Association RulesUsing Data Cubes. 
                            
                            , 207-210.