Knowledge Acquisition from Databases


Book Description

This is a textbook for undergraduate and postgraduate students on machine learning, expert systems, and artificial intelligence courses. The text may also serve as a reference book for researchers in machine learning, knowledge based systems, genetic algorithms, and neural networks.




Knowledge EXplorer


Book Description




Automating Knowledge Acquisition for Expert Systems


Book Description

In June of 1983, our expert systems research group at Carnegie Mellon University began to work actively on automating knowledge acquisition for expert systems. In the last five years, we have developed several tools under the pressure and influence of building expert systems for business and industry. These tools include the five described in chapters 2 through 6 - MORE, MOLE, SALT, KNACK and SIZZLE. One experiment, conducted jointly by developers at Digital Equipment Corporation, the Soar research group at Carnegie Mellon, and members of our group, explored automation of knowledge acquisition and code development for XCON (also known as R1), a production-level expert system for configuring DEC computer systems. This work influenced the development of RIME, a programming methodology developed at Digital which is the subject of chapter 7. This book describes the principles that guided our work, looks in detail at the design and operation of each tool or methodology, and reports some lessons learned from the enterprise. of the work, brought out in the introductory chapter, is A common theme that much power can be gained by understanding the roles that domain knowledge plays in problem solving. Each tool can exploit such an understanding because it focuses on a well defined problem-solving method used by the expert systems it builds. Each tool chapter describes the basic problem-solving method assumed by the tool and the leverage provided by committing to the method.




Automated Knowledge Acquisition


Book Description

This tutorial provides clear explanations of techniques for automated knowledge acquisition. The techniques covered include: decision tree methods, progressive rule generation, explanation-based learning, artificial neural networks, and genetic algorithm approaches. The book is suitable for both advanced undergraduate and graduate students and computer professionals.




Knowledge Acquisition from Databases


Book Description

A comprehensive English-Russian and Russian-English collection of modern statistical terminology, containing some 13,500 terms and some 1,000 names. Topics covered include mathematical statistics and probability theory, computational statistics and statistical software, and applied statistical components in economics, sociology, demography, medicine, natural sciences, and technology. The volume provides an extensive collection of terms in the fields of computer terminology related to problems of data processing and statistical software, theory of random processes, statistical quality control, operations research, and some supplementary areas such as the terminology of Russian official statistics. For translators and other experts who work with English and Russian statistical literature. Annotation copyright by Book News, Inc., Portland, OR