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Association Rules in Very Large Databases

Chapter
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2307)

Abstract

Dealing with very large databases is one of the defining challenges in data mining research and development. Some databases are simp- ly too large (e.g., with terabytes of data) to be processed at one time. An ideal way of mining very large databases would be by us- ing paralleling techniques. This system employs hardware technology, such as parallel machines, to implement concurrent data mining al- gorithms. However, parallel machines are expensive, and less widely available, than single processor machines. This chapter presents some techniques for mining association rules in very large databases, using instance selection.

Keywords

Association Rule Central Limit Theorem Large Database Parallel Machine Frequent Itemsets 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

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