2008 · 39 citations · 16 references
Open access
ComputingComputer EngineeringComputer ScienceBusiness IntelligenceData AnalyticsData MiningData WarehousingDistributed Data ProcessingFrequent Pattern MiningOnline Analytical ProcessingQuery ProcessingScalable Data MiningAssociation Rule MiningData RepositoriesDistributed ArchitectureDistributed Data MiningFrequent Itemset MiningOnline Analytical Processing (Olap) ArchitectureOnline Analytical Processing (Olap) SchemaRule Mining
The new SAP NetWeaver Business Intelligence accelerator is an engine that supports online analytical processing. It performs aggregation in memory and in query runtime over large volumes of structured data. This paper first briefly describes the accelerator and its main architectural features, and cites test results that indicate its power. Then it describes in detail how the accelerator may be used for data mining. The accelerator can perform data mining in the same large repositories of data and using the same compact index structures that it uses for analytical processing. A first such implementation of data mining is described and the results of a performance evaluation are presented. Association rule mining in a distributed architecture was implemented with a variant of the BUC iceberg cubing algorithm. Test results suggest that useful online mining should be possible with wait times of less than 60 seconds on business data that has not been preprocessed. 1.
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Mining association rules between sets of items in large databases
Rakesh Agrawal, Tomasz Imieliński, Arun Swami · 1993 · 14.8K citations · Full text
Fast algorithms for mining association rules
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Mining frequent patterns without candidate generation
Jiawei Han, Jian Pei, Yiwen Yin · ACM SIGMOD Record · 2000 · 6.4K citations
Data mining and knowledge discovery: making sense out of data
U.M. Feyyad · IEEE Expert · 1996 · 4.7K citations