Expert systems / knowledge-based systems

A comprehensive look at General automata and how it can be used to establish the fundamentals for communication in human-computer systems Drawing on author Eldo C.

In recent years AI has been experiencing a deep internal debate on the appropriateness of the symbolic-based paradigm and all of its consequences.

This book will show how generative technology works and the drivers.

Automation in the Virtual Testing of Mechanical Systems: Theories and Implementation Techniques provides a practical understanding of Knowledge-Based Engineering (KBE), an approach that is driving automation in engineering.

First published in 1992, this volume identifies the problems facing the designer of multi-environmental knowledge-based systems, and explains the principles that must be followed in order to obtain successful results.

First published in 1992, this volume identifies the problems facing the designer of multi-environmental knowledge-based systems, and explains the principles that must be followed in order to obtain successful results.

This book introduces the field of artificial intelligence in medicine, a new research area that combines sophisticated representational and computing techniques with the insights of expert physicians to produce tools for improving health care.

This book introduces the field of artificial intelligence in medicine, a new research area that combines sophisticated representational and computing techniques with the insights of expert physicians to produce tools for improving health care.

Scientists often collect samples of curves and other functional observations, and develop models where parameters are also functions.

Computational inference has taken its place alongside asymptotic inference and exact techniques in the standard collection of statistical methods.

Comparing Distributions refers to the statistical data analysis that encompasses the traditional goodness-of-fit testing.

This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing in a common conceptual framework.

Many networked computer systems are far too vulnerable to cyber attacks that can inhibit their functioning, corrupt important data, or expose private information.

Data Mining in Agriculture represents a comprehensive effort to provide graduate students and researchers with an analytical text on data mining techniques applied to agriculture and environmental related fields.

The explosive growth of e-commerce and online environments has made the issue of information search and selection increasingly serious; users are overloaded by options to consider and they may not have the time or knowledge to personally evaluate these options.

In recent years there has been an explosion of network data - that is, measu- ments that are either of or from a system conceptualized as a network - from se- ingly all corners of science.

Data Mining for Business Applications presents the state-of-the-art research and development outcomes on methodologies, techniques, approaches and successful applications in the area.

Biometric  System and Data Analysis: Design, Evaluation, and Data Mining brings together aspects of statistics and machine learning to provide a comprehensive guide to evaluate, interpret and understand biometric data.

The papers in this volume comprise the refereed proceedings of the First Int- national Conference on Computer and Computing Technologies in Agriculture (CCTA 2007), in Wuyishan, China, 2007.

The papers in this volume comprise the refereed proceedings of the the First International Conference on Computer and Computing Technologies in Ag- culture (CCTA 2007), in Wuyishan, China, 2007.

Every mathematical discipline goes through three periods of development: the naive, the formal, and the critical.

One of the "e;image"e; problems with wavelets is that because they have been a dominant area of interest (in nonparametric smoothing) people have forgotten that they are general tools with a fascinating role and future in other areas.

Remarkable advances in computation and data storage and the ready availability of huge data sets have been the keys to the growth of the new disciplines of data mining and machine learning, while the enormous success of the Human Genome Project has opened up the field of bioinformatics.

Social computing concerns the study of social behavior and context based on computational systems.

The use of geospatial technologies has become ubiquitous since the leading Internet vendors delivered a number of popular map websites.

This book brings together the latest research achievements from various areas of signal processing and related disciplines.

Probabilistic networks, also known as Bayesian networks and influence diagrams, have become one of the most promising technologies in the area of applied artificial intelligence, offering intuitive, efficient, and reliable methods for diagnosis, prediction, decision making, classification, troubleshooting, and data mining under uncertainty.

Over the past two decades, network technologies have been remarkably renovated and computer networks, particularly the Internet, have permeated into every facet of our daily lives.

There can be no question, my dear Watson, of the value of exercise before breakfast.

This book provides balanced coverage of the existing results on sequence data mining as well as pattern types and associated pattern mining methods.

Data mining is the science and technology of exploring large and complex bodies of data in order to discover useful patterns.

Most commonly-used parametric and permutation statistical tests, such as the matched-pairs t test and analysis of variance, are based on non-metric squared distance functions that have very poor robustness characteristics.

Joseph Dvorak has over 10 years experience in wearable technology and design.

The Akaike information criterion (AIC) derived as an estimator of the Kullback-Leibler information discrepancy provides a useful tool for evaluating statistical models, and numerous successful applications of the AIC have been reported in various fields of natural sciences, social sciences and engineering.

On any advanced integrated circuit or "e;system-on-chip"e; there is a need for security.

This book is about using interactive and dynamic plots on a computer screen as part of data exploration and modeling, both alone and as a partner with static graphics and non-graphical computational methods.

Advances in hardware technology have increased the capability to store and record personal data about consumers and individuals, causing concerns that personal data may be used for a variety of intrusive or malicious purposes.

The breakthrough idea of parallel coordinates has enchanted many people with its cleverness and power.

Data warehousing and data mining provide techniques for collecting information from distributed databases and for performing data analysis.

Data Streams: Models and Algorithms primarily discusses issues related to the mining aspects of data streams.

Methods of dimensionality reduction provide a way to understand and visualize the structure of complex data sets.

Graphics are great for exploring data, but how can they be used for looking at the large datasets that are commonplace to-day?

"e;If you torture the data long enough, Nature will confess,"e; said 1991 Nobel-winning economist Ronald Coase.

Data mining is a mature technology.

This volume forms the edited proceedings of the Sixth International Symposium on Communications Interworking, held in Perth, Western Australia, from 13-16 October, 2002.

Data mining has emerged as a significant technology for gaining knowledge from vast quantities of data.

During the 1980s and early 1990s there was signi?

Access Control Systems: Security, Identity Management and Trust Models provides a thorough introduction to the foundations of programming systems security, delving into identity management, trust models, and the theory behind access control models.

As computing devices proliferate, demand increases for an understanding of emerging computing paradigms and models based on natural phenomena.

Introduction The goal of this book is to introduce XML to a bioinformatics audience.