"This book presents up-to-date techniques for addressing data management problems with logic and memory use"--Provided by publisher.

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.

“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.

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]

This volume showcases contributions from internationally-known researchers in the field of information management. Most of the approaches presented here make use of fuzzy logic, introduced by L.A. Zadeh almost 50 years ago, which constitute a powerful tool to model and handle gradual concepts. What all of these contributions have in common is placing the user at the center of the information system, be it for helping him/her to query a data set, to handle imperfect information, or to discover useful knowledge from a massive collection of data. Researchers working in data and knowledge management will greatly benefit from this collection of up-to-date studies. This may be also an invaluable source of information for postgraduate students interested in advanced information management techniques.

An ever-increasing thirst for information in recent years among consumers, researchers, and the general population has necessitated continuous growth of internet architecture and accessibility, an issue which, if not addressed properly, may inhibit the growth of the internet as a whole. Solutions for Sustaining Scalability in Internet Growth investigates current issues impeding the growth of information architecture and explores methods for developing a wider-reaching and ever-evolving internet. The book presents viable solutions to some of the current threats to robust and pervasive information systems, enabling internet actors such as network providers, service providers, vendors, and regulatory bodies to ensure the creation of a more accessible and balanced internet.

In the age of transformative artificial intelligence (AI), which has the potential to revolutionize our lives, this book provides a comprehensive exploration of successful research and applications in AI and data analytics. Covering innovative approaches, advanced algorithms, and data analysis methodologies, this book addresses complex problems across topics such as machine learning, pattern recognition, data mining, optimization, and predictive modeling. With clear explanations, practical examples, and cutting-edge research, this book seeks to expand the understanding of a wide readership, including students, researchers, practitioners, and technology enthusiasts eager to explore these exciting fields. Featuring real-world applications in education, health care, climate modeling, cybersecurity, smart transportation, conversational systems, and material analysis, among others, this book highlights how these technologies can drive innovation and generate competitive advantages.

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.