OCLC Systems & Services · 1999 · 84 citations · 4 references
ComputingComputer ScienceInformation TechnologyData AnalyticsData MiningMachine LearningData WarehousingData-driven Decision MakingDecision TreesKnowledge DiscoveryReal-time AnalyticsData Warehouse ArchitectureExplainable Data MiningKnowledge Discovery ProcessesReal-time Data Analysis
Data mining can discover information hidden within valuable data assets. Knowledge discovery, using advanced information technologies, can uncover veins of surprising, golden insights in a mountain of factual data. Data mining consists of a panoply of powerful tools which are intuitive, easy to explain, understandable, and simple to use. These advanced information technologies include artificial intelligence methods (e.g. expert systems, fuzzy logic, etc.), decision trees, rule induction methods, genetic algorithms and genetic programming, neural networks (e.g. backpropagation, associate memories, etc.), and clustering techniques. The synergy created between data warehousing and data mining allows knowledge seekers to leverage their massive data assets, thus improving the quality and effectiveness of their decisions. The growing requirements for data mining and real time analysis of information will be a driving force in the development of new data warehouse architectures and methods and, conversely, the development of new data mining methods and applications.
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Genetic algorithms in search, optimization, and machine learning
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