| Author: | Mohamed Rahama | ISBN: | 9783656295204 |
| Publisher: | GRIN Verlag | Publication: | October 23, 2012 |
| Imprint: | GRIN Verlag | Language: | English |
| Author: | Mohamed Rahama |
| ISBN: | 9783656295204 |
| Publisher: | GRIN Verlag |
| Publication: | October 23, 2012 |
| Imprint: | GRIN Verlag |
| Language: | English |
Essay from the year 2012 in the subject Computer Science - Theory, grade: B, Atlantic International University (School of Science and Engineering), course: Doctorate in Information Technology, language: English, abstract: Data mining is an independent science that based on advanced ways for information retrieval. Data mining is dealing with knowledge discovery in data warehouses without predefined hypotheses. So it is quite different from other applications such as decision support systems, OLAP and others which are looking for information on the factors and assumptions that we know it in advance. Data Mining supports multiple algorithms which have the ability to adopt automatic classification of historical data and predict future events. Data mining in the databases is designed to extract the hidden information, and it is a modern technology that imposed itself strongly in the information revolution, in the light of the great technological development and widespread use of data warehouses. Data mining techniques focus on building future forecasts and explore the behavior and trends, allowing a good estimation for right decisions that taken in a timely manner. This paper provides a general definition of data mining science and its most important techniques and algorithms used.
Essay from the year 2012 in the subject Computer Science - Theory, grade: B, Atlantic International University (School of Science and Engineering), course: Doctorate in Information Technology, language: English, abstract: Data mining is an independent science that based on advanced ways for information retrieval. Data mining is dealing with knowledge discovery in data warehouses without predefined hypotheses. So it is quite different from other applications such as decision support systems, OLAP and others which are looking for information on the factors and assumptions that we know it in advance. Data Mining supports multiple algorithms which have the ability to adopt automatic classification of historical data and predict future events. Data mining in the databases is designed to extract the hidden information, and it is a modern technology that imposed itself strongly in the information revolution, in the light of the great technological development and widespread use of data warehouses. Data mining techniques focus on building future forecasts and explore the behavior and trends, allowing a good estimation for right decisions that taken in a timely manner. This paper provides a general definition of data mining science and its most important techniques and algorithms used.
