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Springer New York
Data Mining for Association Rules and Sequential Patterns: Sequential and Parallel Algorithms
Data Mining for Association Rules and Sequential Patterns: Sequential and Parallel Algorithms
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Recent advances in the data collection and storage technologies have m ade it possible for companies (e.g. bar-code technology), administrati ve agencies (e.g. census data) and scientific laboratories (e.g. molec ule databases in chemistry or biology) to keep vast amounts of data re lating to their activities. At the same time, the availability of chea p computing power has made automatic extraction of structured knowledg e from these data feasible. Such an activity is referred to as data mi ning. More recently, the advent on the marketplace of cheap high perfo rmance (gigabit level) communication switches is even placing cheap pa rallel data mining within the reach of the majority.
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