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» Constraint-Based Rule Mining in Large, Dense Databases
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KAIS
2006
164views more  KAIS 2006»
14 years 10 months ago
On efficiently summarizing categorical databases
Frequent itemset mining was initially proposed and has been studied extensively in the context of association rule mining. In recent years, several studies have also extended its a...
Jianyong Wang, George Karypis
DASFAA
2007
IEEE
220views Database» more  DASFAA 2007»
15 years 4 months ago
LAPIN: Effective Sequential Pattern Mining Algorithms by Last Position Induction for Dense Databases
Sequential pattern mining is very important because it is the basis of many applications. Although there has been a great deal of effort on sequential pattern mining in recent year...
Zhenglu Yang, Yitong Wang, Masaru Kitsuregawa
VLDB
1995
ACM
163views Database» more  VLDB 1995»
15 years 1 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...
SIGMOD
1993
ACM
134views Database» more  SIGMOD 1993»
15 years 2 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
APWEB
2005
Springer
15 years 3 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,...