This is the first book to explain Ripple-Down Rules, an approach to building knowledge-based systems which is more similar to machine learning methods than other rule-based systems but which depends on using an expert rather than applying statistics to data The book provides detailed worked examples and uses publicly available software to demonstrate Ripple-Down Rules The examples enable users to build their own RDR tools

Machine learning algorithms hold extraordinary promise, but the reality is that their success depends entirely on the suitability of the data available. This book is about Ripple-Down Rules (RDR), an alternative manual technique for rapidly building AI systems. With a human in the loop, RDR is much better able to deal with the limitations of data. Ripple-Down Rules: The Alternative to Machine Learning starts by reviewing the problems with data quality and the problems with conventional approaches to incorporating expert human knowledge into AI systems. It suggests that problems with knowledge acquisition arise because of mistaken philosophical assumptions about knowledge. It argues people never really explain how they reach a conclusion, rather they justify their conclusion by differentiating between cases in a context. RDR is based on this more situated understanding of knowledge. The central features of a RDR approach are explained, and detailed worked examples are presented for different types of RDR, based on freely available software developed for this book. The examples ensure developers have a clear idea of the simple yet counter-intuitive RDR algorithms to easily build their own RDR systems. It has been proven in industrial applications that it takes only a minute or two per rule to build RDR systems with perhaps thousands of rules. The industrial uses of RDR have ranged from medical diagnosis through data cleansing to chatbots in cars. RDR can be used on its own or to improve the performance of machine learning or other methods.

The papers in this volume are the refereed application papers presented at AI-2005, the Twenty-fifth SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, held in Cambridge in December 2005. The papers present new and innovative developments in the field, divided into sections on Synthesis and Prediction, Scheduling and Search, Diagnosis and Monitoring, Classification and Design, and Analysis and Evaluation. This is the thirteenth volume in the Applications and Innovations series. The series serves as a key reference on the use of AI Technology to enable organisations to solve complex problems and gain significant business benefits. The Technical Stream papers are published as a companion volume under the title Research and Development in Intelligent Systems XXII.

Contrarian Ripple Trading "Contrarian Ripple Trading is a well-written and well-documented observation for stock traders. I especially enjoyed hearing the commonsense behind McNamara and Bro?zyna's method. For those individuals looking to cut through the huge amount of poor information out there, I think you will thoroughly appreciate this book. I found the high percentage of winning trades hard to argue with." --Jason Alan Jankovsky, FOREX trader and author of Trading Rules That Work Making money in today's stock market can be a difficult endeavor, especially if you're not an expert in the worlds of finance or business. Authors Aidan McNamara and Martha Broz?yna--a married couple who work outside the investment world, but who happen to be active traders--can relate to this situation. That's why they've created Contrarian Ripple Trading. Written in a straightforward and accessible style, this reliable resource outlines the approach they've successfully used to capture profits from the stock market for many years. With this book as your guide, you'll quickly discover how you too can effectively implement a low-risk trading technique that consistently generates short-term profits on trades in large capitalization stocks--regardless of whether the market is moving up, down, or sideways. Throughout the book, and in accompanying Appendixes, McNamara and Broz?yna refer to examples of their flawless trading record--1,225 profitable, round-trip trades over a twenty-six month period--to illustrate how contrarian ripple trading can produce a regular stream of profits in many different market conditions. By combining aspects of investing--notably the need for safety and decent returns--with characteristics of short-term speculation, Contrarian Ripple Trading arms you with a technique that can be used to generate a reliable extra income stream through low-risk, short-term stock trading.

This book constitutes the proceedings of the 16th International Conference on Smart Homes and Health Telematics, ICOST 2018, held in Singapore, Singapore, in July 2018. The theme of this year volume is "Designing a better Future: Urban Assisted Living", focusing on quality of life of dependent people not only in their homes, but also in outdoor living environment to improve mobility and social interaction in the city. The 21 regular papers and 11 short papers included in this volume focus on research in the design, development, deployment and evaluation of smart urban environments, assistive technologies, chronic disease management, coaching and health telematics systems.

This book constitutes the refereed proceedings of the 16th International Conference on Knowledge Engineering and Knowledge Management, EKAW 2008, held in Acitrezza, Sicily, Italy, in September/October 2008. The 17 revised full papers and 15 revised short papers presented together with 3 invited talks were carefully reviewed and selected from 102 submissions. The papers are organized in topical sections on knowledge patterns and knowledge representation, matching ontologies and data integration, natural language, knowledge acquisition and annotations, search, query and interaction, as well as ontologies.

This book constitutes the refereed proceedings of the Third Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD '99, held in Beijing, China, in April 1999. The 29 revised full papers presented together with 37 short papers were carefully selected from a total of 158 submissions. The book is divided into sections on emerging KDD technology; association rules; feature selection and generation; mining in semi-unstructured data; interestingness, surprisingness, and exceptions; rough sets, fuzzy logic, and neural networks; induction, classification, and clustering; visualization; causal models and graph-based methods; agent-based and distributed data mining; and advanced topics and new methodologies.

The papers in this volume deal with academic research topics as well as practical applications in AI. Special emphasis is given to computer vision, machine learning, neural networks mixed with theory of logic and reasoning, and practical applications of expert systems in industry and decision support.