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Data Mining Fundamental Concepts and Critical Issues

Data Mining Fundamental Concepts and Critical Issues

John Wang, Qiyang Chen, James Yao
Copyright: © 2009 |Pages: 6
ISBN13: 9781599048499|ISBN10: 1599048493|EISBN13: 9781599048505
DOI: 10.4018/978-1-59904-849-9.ch064
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MLA

Wang, John, et al. "Data Mining Fundamental Concepts and Critical Issues." Encyclopedia of Artificial Intelligence, edited by Juan Ramón Rabuñal Dopico, et al., IGI Global, 2009, pp. 418-423. https://doi.org/10.4018/978-1-59904-849-9.ch064

APA

Wang, J., Chen, Q., & Yao, J. (2009). Data Mining Fundamental Concepts and Critical Issues. In J. Rabuñal Dopico, J. Dorado, & A. Pazos (Eds.), Encyclopedia of Artificial Intelligence (pp. 418-423). IGI Global. https://doi.org/10.4018/978-1-59904-849-9.ch064

Chicago

Wang, John, Qiyang Chen, and James Yao. "Data Mining Fundamental Concepts and Critical Issues." In Encyclopedia of Artificial Intelligence, edited by Juan Ramón Rabuñal Dopico, Julian Dorado, and Alejandro Pazos, 418-423. Hershey, PA: IGI Global, 2009. https://doi.org/10.4018/978-1-59904-849-9.ch064

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Abstract

Data mining is the process of extracting previously unknown information from large databases or data warehouses and using it to make crucial business decisions. Data mining tools find patterns in the data and infer rules from them. The extracted information can be used to form a prediction or classification model, identify relations between database records, or provide a summary of the databases being mined. Those patterns and rules can be used to guide decision making and forecast the effect of those decisions, and data mining can speed analysis by focusing attention on the most important variables.

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