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"This book presents up-to-date techniques for addressing data management problems with logic and memory use"--Provided by publisher.
This book reviews state-of-the-art methodologies and techniques for analyzing enormous quantities of raw data in high-dimensional data spaces, to extract new information for decision making. The goal of this book is to provide a single introductory source, organized in a systematic way, in which we could direct the readers in analysis of large data sets, through the explanation of basic concepts, models and methodologies developed in recent decades. If you are an instructor or professor and would like to obtain instructor’s materials, please visit http://booksupport.wiley.com If you are an instructor or professor and would like to obtain a solutions manual, please send an email to: [email protected]
Modern knowledge discovery methods enable users to discover complex patterns of various types in large information repositories. However, the underlying assumption has always been that the data to which the methods are applied to originates from one domain. The focus of this book, and the BISON project from which the contributions are originating, is a network based integration of various types of data repositories and the development of new ways to analyse and explore the resulting gigantic information networks. Instead of finding well defined global or local patterns they wanted to find domain bridging associations which are, by definition, not well defined since they will be especially interesting if they are sparse and have not been encountered before. The 32 contributions presented in this state-of-the-art volume together with a detailed introduction to the book are organized in topical sections on bisociation; representation and network creation; network analysis; exploration; and applications and evaluation.
Intelligent paradigms are increasingly finding their ways in the design and development of decision support systems. This book presents a sample of recent research results from key researchers. The contributions include: Introduction to intelligent systems in decision making - A new method of ranking intuitionistic fuzzy alternatives - Fuzzy rule base model identification by bacterial memetic algorithms - Discovering associations with uncertainty from large databases - Dempster-Shafer structures, monotonic set measures and decision making - Interpretable decision-making models - A general methodology for managerial decision making - Supporting decision making via verbalization of data analysis results using linguistic data summaries - Computational intelligence in medical decisions making. This book is directed to the researchers, graduate students, professors, decision makers and to those who are interested to investigate intelligent paradigms in decision making.
Multimedia represents information in novel and varied formats. One of the most prevalent examples of continuous media is video. Extracting underlying data from these videos can be an arduous task. From video indexing, surveillance, and mining, complex computational applications are required to process this data. Intelligent Analysis of Multimedia Information is a pivotal reference source for the latest scholarly research on the implementation of innovative techniques to a broad spectrum of multimedia applications by presenting emerging methods in continuous media processing and manipulation. This book offers a fresh perspective for students and researchers of information technology, media professionals, and programmers.
This book presents new developments and advances in the theory, applications, and design methods of computational intelligence, integrated in various areas of project management and BIM environments. The chapters of the book span different soft computing techniques, such as: linguistic data summarization, fuzzy systems, evolutionary algorithms, estimation distribution algorithms, computing with words, augmented reality, and hybrid intelligence systems. In addition, different applications of the neutrosophic theory are presented for the treatment of uncertainty and indeterminacy in decision-making processes. Several chapters of the book constitute systematic reviews, useful for future investigations in the following topics: linguistic summarization of data, augmented reality, and the development of BIM technologies. It is a particularly interesting book for engineers, researchers, specialists, teachers, and students related to project management and the development of BIM technologies.
This book constitutes the refereed proceedings of the IFIP TC 5 International Conference on Digital Product and Process Development Systems, NEW PROLAMAT 2013, held in Dresden, Germany, in October 2013. The conference succeeds the International Conference on Programming Languages for Machine Tools, PROLAMAT 2006, held in Shanghai, China in 2006. In order to demonstrate the new orientation toward IT innovations, the acronym PROLAMAT has been changed into NEW PROLAMAT and is now interpreted as Project Research on Leading-Edge Applications and Methods for Applied Technology. The 42 revised papers were carefully reviewed and selected for inclusion in the volume. They have been organized in the following topical sections: digital product and process development; additive manufacturing; quality management; standardization and knowledge management developments; and simulation of procedures and processes.
This book constitutes the proceedings of the 13th conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, held in Dortmund, Germany, in June 2010.
“Neutrosophic Sets and Systems” has been created for publications on advanced studies in neutrosophy, neutrosophic set, neutrosophic logic, neutrosophic probability, neutrosophic statistics that started in 1995 and their applications in any field, such as the neutrosophic structures developed in algebra, geometry, topology, etc.
The quick development of the markets and companies, especially those that apply information technology, has made it easy to store a large volume of digital information. Nevertheless, the extraction of potentially useful knowledge is difficult; also could not be easily understandable by humans. One of the techniques applied to the solution to this problem is the linguistic data summarizations, whose objective is to discover knowledge to extract patterns from databases, from which are generated explicit and concise summaries.