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检索条件"丛书名=Advanced Information and Knowledge Processing"

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Robust representation for data analytics : models and applications /

引用

2017年

作者： Li Sheng

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Understanding information 1st ed. 2017

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丛书名： advanced information and knowledge processing

2017年

作者： Alfons Josef Schuster

ISBN: (数字)9783319590905

ISBN: (纸本)9783319590899

The motivation of this edited book is to generate an understanding about information, related concepts and the roles they play in the modern, technology permeated world. In order to achieve our goal, we observe how information is understood in domains, such as cosmology, physics, biology, neuroscience, computer science, artificial intelligence, the Internet, big data, information society, or philosophy. Together, these observations form an integrated view so that readers can better understand this exciting building-block of modern-day society. On the surface, information is a relatively straightforward and intuitive concept. Underneath, however, information is a relatively versatile and mysterious entity. For instance, the way a physicist looks at information is not necessarily the same way as that of a biologist, a neuroscientist, a computer scientist, or a philosopher. Actually, when it comes to information, it is common that each field has its domain specific views, motivations, interpretations, definitions, methods, technologies, and challenges. With contributions by authors from a wide range of backgrounds, Understanding information: From the Big Bang to Big Data will appeal to readers interested in the impact of information on modern-day life from a variety of perspectives.

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Foundations and Methods in Combinatorial and Statistical Data Analysis and Clustering 1st ed. 2016

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丛书名： advanced information and knowledge processing

2016年

作者： Israël César Lerman

ISBN: (数字)9781447167938

ISBN: (纸本)9781447167914

This book offers an original and broad exploration of the fundamental methods in Clustering and Combinatorial Data Analysis, presenting new formulations and ideas within this very active field. With extensive introductions, formal and mathematical developments and real case studies, this book provides readers with a deeper understanding of the mutual relationships between these methods, which are clearly expressed with respect to three facets: logical, combinatorial and statistical. Using relational mathematical representation, all types of data structures can be handled in precise and unified ways which the author highlights in three stages: Clustering a set of descriptive attributes Clustering a set of objects or a set of object categories Establishing correspondence between these two dual clusterings Tools for interpreting the reasons of a given cluster or clustering are also included. Foundations and Methods in Combinatorial and Statistical Data Analysis and Clustering will be a valuable resource for students and researchers who are interested in the areas of Data Analysis, Clustering, Data Mining and knowledge Discovery.

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Numeric Computation and Statistical Data Analysis on the Java Platform 1st ed. 2016

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丛书名： advanced information and knowledge processing

2016年

作者： Sergei V. Chekanov

ISBN: (数字)9783319285313

ISBN: (纸本)9783319285290

Numerical computation, knowledge discovery and statistical data analysis integrated with powerful 2D and 3D graphics for visualization are the key topics of this book. The Python code examples powered by the Java platform can easily be transformed to other programming languages, such as Java, Groovy, Ruby and BeanShell. This book equips the reader with a computational platform which, unlike other statistical programs, is not limited by a single programming language. The author focuses on practical programming aspects and covers a broad range of topics, from basic introduction to the Python language on the Java platform (Jython), to descriptive statistics, symbolic calculations, neural networks, non-linear regression analysis and many other data-mining topics. He discusses how to find regularities in real-world data, how to classify data, and how to process data for knowledge discoveries. The code snippets are so short that they easily fit into single pages. Numeric Computation and Statistical Data Analysis on the Java Platform is a great choice for those who want to learn how statistical data analysis can be done using popular programming languages, who want to integrate data analysis algorithms in full-scale applications, and deploy such calculations on the web pages or computational servers regardless of their operating system. It is an excellent reference for scientific computations to solve real-world problems using a comprehensive stack of open-source Java libraries included in the DataMelt (DMelt) project and will be appreciated by many data-analysis scientists, engineers and students.

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Machine Learning for Audio, Image and Video Analysis: Theory and Applications 2

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丛书名： advanced information and knowledge processing

2015年

作者： Francesco Camastra, Alessandro Vinciarelli (auth.)

ISBN: (数字)9781447167358

ISBN: (纸本)9781447167341;9781447167358

This second edition focuses on audio, image and video data, the three main types of input that machines deal with when interacting with the real world. A set of appendices provides the reader with self-contained introductions to the mathematical background necessary to read the book. Divided into three main parts, From Perception to Computation introduces methodologies aimed at representing the data in forms suitable for computer processing, especially when it comes to audio and images. Whilst the second part, Machine Learning includes an extensive overview of statistical techniques aimed at addressing three main problems, namely classification (automatically assigning a data sample to one of the classes belonging to a predefined set), clustering (automatically grouping data samples according to the similarity of their properties) and sequence analysis (automatically mapping a sequence of observations into a sequence of human-understandable symbols). The third part Applications shows how the abstract problems defined in the second part underlie technologies capable to perform complex tasks such as the recognition of hand gestures or the transcription of handwritten data. Machine Learning for Audio, Image and Video Analysis is suitable for students to acquire a solid background in machine learning as well as for practitioners to deepen their knowledge of the state-of-the-art. All application chapters are based on publicly available data and free software packages, thus allowing readers to replicate the experiments.

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Metasynthetic Computing and Engineering of Complex Systems 1

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丛书名： advanced information and knowledge processing

2015年

作者： Longbing Cao (auth.)

ISBN: (数字)9781447165507;9781447165514

ISBN: (纸本)9781447165507;9781447165514

Provides a comprehensive overview and introduction to the concepts, methodologies, analysis, design and applications of metasynthetic computing and engineering. The author: Presents an overview of complex systems, especially open complex giant systems such as the Internet, complex behavioural and social problems, and actionable knowledge discovery and delivery in the big data era. Discusses ubiquitous intelligence in complex systems, including human intelligence, domain intelligence, social intelligence, network intelligence, data intelligence and machine intelligence, and their synergy through metasynthetic engineering. Explains the concept and methodology of human-centred, human-machine-cooperated qualitative-to-quantitative metasynthesis for understanding and managing open complex giant systems, and its computing approach: metasynthetic computing. Introduces techniques and tools for analysing and designing problem-solving systems for open complex problems and systems. Metasynthetic Computing and Engineering uses the systematology methodology in addressing system complexities in open complex giant systems, for which it may not only be effective to apply reductionism or holism. The book aims to encourage and inspire discussions, design, implementation and reflection of effective methodologies and tools for computing and engineering open complex systems and problems. Researchers, research students and practitioners in complex systems, artificial intelligence, data science, computer science, and even system science, cognitive science, behaviour science, and social science, will find this book invaluable.

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Mathematical Tools for Data Mining 2nd ed. 2014

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丛书名： advanced information and knowledge processing

2014年

作者： Dan A. Simovici Chabane Djeraba

ISBN: (数字)9781447164074

ISBN: (纸本)9781447164067

Data mining essentially relies on several mathematical disciplines, many of which are presented in this second edition of this book. Topics include partially ordered sets, combinatorics, general topology, metric spaces, linear spaces, graph theory. To motivate the reader a significant number of applications of these mathematical tools are included ranging from association rules, clustering algorithms, classification, data constraints, logical data analysis, etc. The book is intended as a reference for researchers and graduate students. The current edition is a significant expansion of the first edition. We strived to make the book self-contained and only a general knowledge of mathematics is required. More than 700 exercises are included and they form an integral part of the material. Many exercises are in reality supplemental material and their solutions are included.

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Advances in Applied Self-Organizing Systems 2nd ed. 2013

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丛书名： advanced information and knowledge processing

2013年

作者： Mikhail Prokopenko

ISBN: (数字)9781447151135

ISBN: (纸本)9781447151128

How do we design a self-organizing system? Is it possible to validate and control non-deterministic dynamics? What is the right balance between the emergent patterns that bring robustness, adaptability and scalability, and the traditional need for verification and validation of the outcomes? The last several decades have seen much progress from original ideas of emergent functionality and design for emergence, to sophisticated mathematical formalisms of guided self-organization. And yet the main challenge remains, attracting the best scientific and engineering expertise to this elusive problem. This book presents state-of-the-practice of successfully engineered self-organizing systems, and examines ways to balance design and self-organization in the context of applications. As demonstrated in this second edition of Advances in Applied Self-Organizing Systems, finding this balance helps to deal with practical challenges as diverse as navigation of microscopic robots within blood vessels, self-monitoring aerospace vehicles, collective and modular robotics adapted for autonomous reconnaissance and surveillance, self-managing grids and multiprocessor scheduling, data visualization and self-modifying digital and analog circuitry, intrusion detection in computer networks, reconstruction of hydro-physical fields, traffic management, immunocomputing and nature-inspired computation. Many algorithms proposed and discussed in this volume are biologically inspired, and the reader will also gain an insight into cellular automata, genetic algorithms, artificial immune systems, snake-like locomotion, ant foraging, birds flocking, neuromorphic circuits, amongst others. Demonstrating the practical relevance and applicability of self-organization, Advances in Applied Self-Organizing Systems will be an invaluable tool for advanced students and researchers in a wide range of fields.

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Artificial Intelligence Techniques for Rational Decision Making 1

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丛书名： advanced information and knowledge processing

2014年

作者： Tshilidzi Marwala (auth.)

ISBN: (数字)9783319114231

ISBN: (纸本)9783319114231;9783319114248

Develops insights into solving complex problems in engineering, biomedical sciences, social science and economics based on artificial intelligence. Some of the problems studied are in interstate conflict, credit scoring, breast cancer diagnosis, condition monitoring, wine testing, image processing and optical character recognition. The author discusses and applies the concept of flexibly-bounded rationality which prescribes that the bounds in Nobel Laureate Herbert Simons bounded rationality theory are flexible due to advanced signal processing techniques, Moores Law and artificial intelligence. Artificial Intelligence Techniques for Rational Decision Making examines and defines the concepts of causal and correlation machines and applies the transmission theory of causality as a defining factor that distinguishes causality from correlation. It develops the theory of rational counterfactuals which are defined as counterfactuals that are intended to maximize the attainment of a particular goal within the context of a bounded rational decision making process. Furthermore, it studies four methods for dealing with irrelevant information in decision making: Theory of the marginalization of irrelevant information Principal component analysis Independent component analysis Automatic relevance determination method In addition it studies the concept of group decision making and various ways of effecting group decision making within the context of artificial intelligence. Rich in methods of artificial intelligence including rough sets, neural networks, support vector machines, genetic algorithms, particle swarm optimization, simulated annealing, incremental learning and fuzzy networks, this book will be welcomed by researchers and students working in these areas.

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Natural and Artificial Reasoning: An Exploration of Modelling Human Thinking 1

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丛书名： advanced information and knowledge processing

2014年

作者： Tom Addis (auth.)

ISBN: (数字)9783319112855

ISBN: (纸本)9783319112855;9783319112862

What are the limitations of computer models and why do we still not have working models of people that are recognizably human? This is the principle puzzle explored in this book where ideas behind systems that behave intelligently are described and different philosophical issues are touched upon. The key to human behavior is taken to be intelligence and the ability to reason about the world. A strong scientific approach is taken, but first it was required to understand what a scientific approach could mean in the context of both natural and artificial systems. A theory of intelligence is proposed that can be tested and developed in the light of experimental results. The book illustrates that intelligence is much more than just behavior confined to a unique person or a single computer program within a fixed time frame. Some answers are unraveled and some puzzles emerge from these investigations and experiments. Natural and Artificial Reasoning provides a few steps of an exciting journey that began many centuries ago with the word why?

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