Chance Discovery


Book Description

Chance discovery means discovering chances - the breaking points in systems, the marketing windows in business, etc. It involves determining the significance of some piece of information about an event and then using this new knowledge in decision making. The techniques developed combine data mining methods for finding rare but important events with knowledge management, groupware, and social psychology. The reader will find many applications, such as finding information on the Internet, recognizing changes in customer behavior, detecting the first signs of an imminent earthquake, etc. This first book dedicated to chance discovery covers the state of the art in the theory and methods and examines typical scenarios, and it thus appeals to researchers working on new techniques and algorithms and also to professionals dealing with real-world applications.




Chance Discoveries in Real World Decision Making


Book Description

For this book, the editors invited contributions from indispensable research areas relevant to "chance discovery", which has been defined as the discovery of events significant for making a decision, and studied since 2000. The chapters contain contributions to identifying rare or hidden events and explaining their significance. The methods presented in this book are based on the interaction of human, machine, and humans’ living environment.




Advances in Chance Discovery


Book Description

Since year 2000, scientists on artificial and natural intelligences started to study chance discovery - methods for discovering events/situations that significantly affect decision making. Partially because the editors Ohsawa and Abe are teaching at schools of Engineering and of Literature with sharing the interest in chance discovery, this book reflects interdisciplinary aspects of progress: First, as an interdisciplinary melting pot of cognitive science, computational intelligence, data mining/visualization, collective intelligence, ... etc, chance discovery came to reach new application domains e.g. health care, aircraft control, energy plant, management of technologies, product designs, innovations, marketing, finance etc. Second, basic technologies and sciences including sensor technologies, medical sciences, communication technologies etc. joined this field and interacted with cognitive/computational scientists in workshops on chance discovery, to obtain breakthroughs by stimulating each other. Third, “time” came to be introduced explicitly as a significant variable ruling causalities - background situations causing chances and chances causing impacts on events and actions of humans in the future. Readers may urge us to list the fourth, fifth, sixth, ... but let us stop here and open this book.




Introduction to Probability


Book Description

This classroom-tested textbook is an introduction to probability theory, with the right balance between mathematical precision, probabilistic intuition, and concrete applications. Introduction to Probability covers the material precisely, while avoiding excessive technical details. After introducing the basic vocabulary of randomness, including events, probabilities, and random variables, the text offers the reader a first glimpse of the major theorems of the subject: the law of large numbers and the central limit theorem. The important probability distributions are introduced organically as they arise from applications. The discrete and continuous sides of probability are treated together to emphasize their similarities. Intended for students with a calculus background, the text teaches not only the nuts and bolts of probability theory and how to solve specific problems, but also why the methods of solution work.




Probability: A Lively Introduction


Book Description

Comprehensive, yet concise, this textbook is the go-to guide to learn why probability is so important and its applications.




Trends in Applied Knowledge-Based Systems and Data Science


Book Description

This book constitutes the refereed conference proceedings of the 29th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2016, held in Morioka, Japan, in August 2-4, 2016. The 80 revised full papers presented were carefully reviewed and selected from 168 submissions. They are organized in topical sections: data science; knowledge base systems; natural language processing and sentiment analysis; semantic Web and social networks; computer vision; medical diagnosis system and bio-informatics; applied neural networks; innovations in intelligent systems and applications; decision support systems; adaptive control; soft computing and multi-agent systems; evolutionary algorithms and heuristic search; system integration for real-life applications.




The Accidental Scientist


Book Description

The Accidental Scientist explores the role of chance and error in scientific, medical and commercial innovation, outlining exactly how some of the most well-known products, gadgets and useful gizmos came to be.




Knowledge-Based Intelligent Information and Engineering Systems


Book Description

The four volume set LNAI 3681, LNAI 3682, LNAI 3683, and LNAI 3684 constitute the refereed proceedings of the 9th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2005, held in Melbourne, Australia in September 2005. The 716 revised papers presented were carefully reviewed and selected from nearly 1400 submissions. The papers present a wealth of original research results from the field of intelligent information processing in the broadest sense; topics covered in the fourth volume are innovations in intelligent systems and their applications, data mining and soft computing applications, skill acquisition and ubiquitous human computer interaction, soft computing and their applications, agent-based workflows, knowledge sharing and reuse, multi-media authentication and watermarking applications, knowledge and engineering techniques for spatio-temporal applications, intelligent data analysis and applications, creativitiy support environment and its social applications, collective intelligence, computational methods for intelligent neuro-fuzzy applications, evolutionary and self-organizing sensors, actuators and processing hardware, knowledge based systems for e-business and e-learning, multi-agent systems and evolutionary computing, ubiquitous pattern recognition, neural networks for data mining, and knowledge-based technology in crime matching, modelling and prediction.




A Modern Introduction to Probability and Statistics


Book Description

Suitable for self study Use real examples and real data sets that will be familiar to the audience Introduction to the bootstrap is included – this is a modern method missing in many other books