Association Rule Mining of Regional Data

Association Rule Mining of Regional Data

Anne Denton (North Dakota State University, USA) and Christopher Besemann (North Dakota State University, USA)
Copyright: © 2005 |Pages: 4
DOI: 10.4018/978-1-59140-557-3.ch014
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Abstract

Most data of practical relevance are structured in more complex ways than is assumed in traditional data mining algorithms, which are based on a single table. The concept of relations allows for discussing many data structures such as trees and graphs. Relational data have much generality and are of significant importance, as demonstrated by the ubiquity of relational database management systems. It is, therefore, not surprising that popular data mining techniques, such as association rule mining, have been generalized to relational data. An important aspect of the generalization process is the identification of problems that are new to the generalized setting.

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