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SIGMOD
1993
ACM
134views Database» more  SIGMOD 1993»
13 years 8 months ago
Mining Association Rules between Sets of Items in Large Databases
We are given a large database of customer transactions. Each transaction consists of items purchased by a customer in a visit. We present an e cient algorithm that generates all s...
Rakesh Agrawal, Tomasz Imielinski, Arun N. Swami
ICDM
2008
IEEE
156views Data Mining» more  ICDM 2008»
13 years 11 months ago
Mining Allocating Patterns in One-Sum Weighted Items
An Association Rule (AR) is a common knowledge model in data mining that describes an implicative cooccurring relationship between two disjoint sets of binary-valued transaction d...
Yanbo J. Wang, Xinwei Zheng, Frans Coenen, Cindy Y...
APWEB
2005
Springer
13 years 10 months ago
Mining Quantitative Associations in Large Database
Association Rule Mining algorithms operate on a data matrix to derive association rule, discarding the quantities of the items, which contains valuable information. In order to mak...
Chenyong Hu, Yongji Wang, Benyu Zhang, Qiang Yang,...
VLDB
1995
ACM
163views Database» more  VLDB 1995»
13 years 8 months ago
An Efficient Algorithm for Mining Association Rules in Large Databases
Mining for a.ssociation 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 effic...
Ashok Savasere, Edward Omiecinski, Shamkant B. Nav...
KDD
2002
ACM
140views Data Mining» more  KDD 2002»
14 years 5 months ago
Mining frequent item sets by opportunistic projection
In this paper, we present a novel algorithm OpportuneProject for mining complete set of frequent item sets by projecting databases to grow a frequent item set tree. Our algorithm ...
Junqiang Liu, Yunhe Pan, Ke Wang, Jiawei Han