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Complex analysis --- Mathematical statistics --- Information systems --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- patroonherkenning --- DIP (documentimage processing) --- beeldverwerking --- IR (information retrieval) --- factoranalyse --- complexe analyse (wiskunde) --- database management --- KI (kunstmatige intelligentie) --- robots --- AI (artificiële intelligentie)
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Bioinformatics, a field devoted to the interpretation and analysis of biological data using computational techniques, has evolved tremendously in recent years due to the explosive growth of biological information generated by the scientific community. Soft computing is a consortium of methodologies that work synergistically and provides, in one form or another, flexible information processing capabilities for handling real-life ambiguous situations. Several research articles dealing with the application of soft computing tools to bioinformatics have been published in the recent past; however,
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Advanced Methods for Knowledge Discovery from Complex Data brings together research articles by active practitioners and leading researchers reporting recent advances in the field of knowledge discovery, where the information is mined from complex data, such as unstructured text from the world-wide web, databases naturally represented as graphs and trees, geoscientific data from satellites and visual images, multimedia data and bioinformatics data. An overview of the field, looking at the issues and challenges involved is followed by coverage of recent trends in data mining, including descriptions of some currently popular tools like genetic algorithms, neural networks and case-based reasoning. This provides the context for the subsequent chapters on methods and applications. Part I is devoted to the foundations of mining different types of complex data like trees, graphs, links and sequences. A knowledge discovery approach based on problem decomposition is also described. Part II presents important applications of advanced mining techniques to data in unconventional and complex domains, such as life sciences, world-wide web, image databases, cyber security and sensor networks. With a good balance of introductory material on the knowledge discovery process, advanced issues and state-of-the-art tools and techniques, as well as recent working applications this book provides a representative selection of the available methods and their evaluation in real domains. It will be useful to students at Masters and PhD level in Computer Science, as well as practitioners in the field. A website supports the book: http://www.cse.uta.edu/amkdcd.
Complex analysis --- Mathematical statistics --- Information systems --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- patroonherkenning --- DIP (documentimage processing) --- beeldverwerking --- IR (information retrieval) --- factoranalyse --- complexe analyse (wiskunde) --- database management --- KI (kunstmatige intelligentie) --- robots
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Numerical methods of optimisation --- Operational research. Game theory --- Mathematics --- Biomathematics. Biometry. Biostatistics --- Genetics --- Molecular biology --- Biology --- Biotechnology --- Computer science --- Information systems --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- biomathematica --- datamining --- bio-informatica --- biologie --- automatisering --- informatica --- biotechnologie --- wiskunde --- AI (artificiële intelligentie) --- data acquisition --- genexpressie
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