Data mining in the industry
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The monograph proposes a suitable process application for a knowledge discovery process in industry databases. The entire process was divided into distinct stages. First, the subject matter to be resolved by employing the knowledge discovery process was identified. Next, the data of the production system was analysed. Several mining models, in which various methods and techniques of data mining in dependence on analyzed data and subject matter investigated, were developed. In order to examine how interesting and useful the knowledge discovered was, it was applied to a production system, whose data operated as input data to the process of KDD. The results achieved proved that the knowledge discovered was useful and a modified simulation model achieved the predicted behaviour. Finally, the proposal of the process application methodology of knowledge discovery in industry databases is discussed. This methodology describes the particular steps of implementing the process of KDD. The proposed methodology can help identify specific requirements and potential problems in the process stages that might be encountered in the course of its application in the industry.
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Data mining in the industry, Michal Kebísek
- Language
- Released
- 2012
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- Title
- Data mining in the industry
- Language
- English
- Authors
- Michal Kebísek
- Publisher
- Univ.-Verl.
- Released
- 2012
- ISBN10
- 3863600487
- ISBN13
- 9783863600488
- Series
- Scientific monographs in automation and computer science
- Category
- University and college textbooks
- Description
- The monograph proposes a suitable process application for a knowledge discovery process in industry databases. The entire process was divided into distinct stages. First, the subject matter to be resolved by employing the knowledge discovery process was identified. Next, the data of the production system was analysed. Several mining models, in which various methods and techniques of data mining in dependence on analyzed data and subject matter investigated, were developed. In order to examine how interesting and useful the knowledge discovered was, it was applied to a production system, whose data operated as input data to the process of KDD. The results achieved proved that the knowledge discovered was useful and a modified simulation model achieved the predicted behaviour. Finally, the proposal of the process application methodology of knowledge discovery in industry databases is discussed. This methodology describes the particular steps of implementing the process of KDD. The proposed methodology can help identify specific requirements and potential problems in the process stages that might be encountered in the course of its application in the industry.