Innovative Applications in Data Mining

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Nedjah, Nadia (Επιμελητής έκδοσης), Macedo Mourelle, Luiza de (Επιμελητής έκδοσης), Kacprzyk, Janusz (Επιμελητής έκδοσης)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2009.
• Σειρά: Studies in Computational Intelligence, 169
• Θέματα: Engineering.; Artificial intelligence.; Applied mathematics.; Engineering mathematics.; Appl.Mathematics/Computational Methods of Engineering.; Artificial Intelligence (incl. Robotics).

 Data mining consists of attempting to discover novel and useful knowledge from data, trying to find patterns among datasets that can help in intelligent decision making. However, reports of real-world case studies are not generally detailed in the literature, due to the fact that they are usually based on proprietary datasets, making it impossible to publish the results. This kind of situation makes hard to evaluate, in a precise way, the degree of effectiveness of data mining techniques in real-world applications. On the other hand, researchers of this field of expertise usually exploit public-domain datasets. This volume offers a wide spectrum of research work developed for data mining for real-world application. In the following, we give a brief introduction of the chapters that are included in this book. 

 Application of Data Mining Techniques to Storage Management and Online Distribution of Satellite Images -- A GUI Tool for Plausible Reasoning in the Semantic Web Using MEBN -- Multiobjective Optimization and Rule Learning: Subselection Algorithm or Meta-heuristic Algorithm? -- Clustering Dynamic Web Usage Data -- Towards Characterization of the Data Generation Process -- Data Mining Applied to the Electric Power Industry: Classification of Short-Circuit Faults in Transmission Lines.