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What is Association Mining

Chapter 28
Handbook of Research on Fuzzy Information Processing in Databases
It is the discovery of patterns discovered in data that includes the concepts of transaction, basket, and group. A common example of a transaction is the set of items someone buys during a supermarket trip. Not all data sets have a transaction-based structure, for example, a database of names, ages, and addresses includes no obvious transactions and will not yield association rules (http://www.wikipedia.com).
Published in Chapter:
Applying Fuzzy Logic in Dynamic Causal Mining
Yi Wang (Cardiff University, UK)
Copyright: © 2008 |Pages: 21
DOI: 10.4018/978-1-59904-853-6.ch028
Abstract
This chapter applies fuzzy logic to a dynamic causal mining (DCM) algorithm and argues that DCM, a combination of association mining and system dynamics for discovering causality patterns, needs a potentially more substantive approach for the user to understand the nature of extracted rules and information in a variety of contexts. Furthermore, the author hopes that the use of fuzzy logic will not only assist the user to make better decisions, but also assist in a better understanding of future behaviour of the target system.
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Chapter 171
Expert Knowledge in Data Mining
A data mining method that discovers frequent patterns, associations, correlations, or causal structures among sets of attributes in data sets. A frequent pattern is a pattern (set of attributes or a sequence) that occurs with some pre-established frequently in the data set.
Published in Chapter: Expert Knowledge in Data Mining; From: Encyclopedia of Information Science and Technology, Third Edition
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