Results 251 to 260 of about 9,278,183 (294)

Visual Comparison of Association Rules

Computational Statistics, 2001
An association rule \(A\to B(\text{supp, conf})\), where ``supp'' is the support and ``conf'' is the confidence of the rule, can be considered as a description of a link between two random events: \(\text{supp}=\Pr(A\cap B)\) and \(\text{conf}=\Pr(B |A)\). The analysis of such rules is aimed at the selection of interesting ones.
Heike Hofmann, Adalbert F. X. Wilhelm
openaire   +2 more sources

Mining generalized association rules

Future Generation Computer Systems, 1997
Abstract We introduce the problem of mining generalized association rules. Given a large database of transactions, where each transaction consists of a set of items, and a taxonomy (is-a hierarchy) on the items, we find associations between items at any level of the taxonomy.
Ramakrishnan Srikant, Rakesh Agrawal 0001   +1 more
openaire   +3 more sources

Association Rules Using Rough Set and Association Rule Methods

2002
With the wide applications of computers, database technologies and automated data collection techniques, large amount of data have been continuously collected into databases. It creates great demands for analyzing such data and turning them into useful knowledge. Therefore, it is necessary and interesting to examine how to extract hidden information or
Defit Sarjon, Mohd. Noor Md. Sap
openaire   +2 more sources

An Associative Memory for Association Rule Mining

2007 International Joint Conference on Neural Networks, 2007
Association rule mining is a thoroughly studied problem in data mining. Its solution has been aimed for by approaches based on different strategies involving, for instance, the use of novel data structures to represent the knowledge discovered, the transformation of the input data to speed up the process, the exploitation of the itemset properties ...
Vicente Oswaldo Baez Monroy, Simon O'Keefe   +1 more
openaire   +1 more source

Ordinal Association Rules towards Association Rules

2003
Intensity of inclination, an objective rule-interest measure, allows us to extract implications on databases without having to go through the step of transforming the initial set of attributes into binary attributes, thereby avoiding obtaining a prohibitive number of rules of little significance with many redundancies.
openaire   +1 more source

Representative association rules

1998
Discovering association rules between items in a large database is an important database mining problem. The number of association rules may be huge. In this paper, we define a cover operator that logically derives a set of association rules from a given association rule.
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Association Rule Hiding Methods

WIREs Data Mining and Knowledge Discovery, 2009
The enormous expansion of data collection and storage facilities has created an unprecedented increase in the need for data analysis and processing power. Data mining has long been the catalyst for automated and sophisticated data analysis and interrogation.
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Association Rules

2009
Association rules present one of the most versatile techniques for the analysis of binary data, with applications in areas as diverse as retail, bioinformatics, and sociology. In this chapter, the origin of association rules is discussed along with the functions by which association rules are traditionally characterised. Following the formal definition
Paul D. McNicholas, Yanchang Zhao
openaire   +2 more sources

Learning Business Rules with Association Rule Classifiers

2014
The main obstacles for a straightforward use of association rules as candidate business rules are the excessive number of rules discovered even on small datasets, and the fact that contradicting rules are generated. This paper shows that Association Rule Classification algorithms, such as CBA, solve both these problems, and provides a practical guide ...
Tomás Kliegr, Jaroslav Kuchar, Davide Sottara, Stanislav Vojír   +3 more
openaire   +1 more source

Highly explainable cumulative belief rule-based system with effective rule-base modeling and inference scheme

Knowledge-Based Systems, 2022
Fei-Fei Ye, Chris Nugent
exaly