Ripple-Down Rules


Book Description

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




Ripple-Down Rules


Book Description

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.




Applications and Innovations in Intelligent Systems XIII


Book Description

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


Book Description

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.







Knowledge Engineering: Practice and Patterns


Book Description

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.




Computational Linguistics and Intelligent Text Processing


Book Description

This two-volume set, consisting of LNCS 6608 and LNCS 6609, constitutes the thoroughly refereed proceedings of the 12th International Conference on Computer Linguistics and Intelligent Processing, held in Tokyo, Japan, in February 2011. The 74 full papers, presented together with 4 invited papers, were carefully reviewed and selected from 298 submissions. The contents have been ordered according to the following topical sections: lexical resources; syntax and parsing; part-of-speech tagging and morphology; word sense disambiguation; semantics and discourse; opinion mining and sentiment detection; text generation; machine translation and multilingualism; information extraction and information retrieval; text categorization and classification; summarization and recognizing textual entailment; authoring aid, error correction, and style analysis; and speech recognition and generation.




Computer Applications for Software Engineering, Disaster Recovery, and Business Continuity


Book Description

This book comprises the refereed proceedings of the International Conferences, ASEA and DRBC 2012, held in conjunction with GST 2012 on Jeju Island, Korea, in November/December 2012. The papers presented were carefully reviewed and selected from numerous submissions and focus on the various aspects of advanced software engineering and its applications, and disaster recovery and business continuity.




Knowledge Management and Acquisition for Smart Systems and Services


Book Description

This book constitutes the proceedings of the 13th International Workshop on Knowledge Management and Acquisition for Intelligent Systems, PKAW 2014, held in Gold Cost, Qld, Australia, in December 2014. The 18 full papers and 4 short papers included in this volume were carefully reviewed and selected from 69 initial submissions. They deal with knowledge acquisition, expert systems, intelligent agents, ontology engineering, foundations of artificial intelligence, machine learning, data mining, Web mining, information systems, Web and other applications.




Methodologies for Knowledge Discovery and Data Mining


Book Description

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.