Books in the Frontiers in Artificial Intelligence and Applications series

Talks about Logic Programming, Uncertainty Reasoning and Machine Learning. This book includes definitions that circumscribe the area formed by extending Inductive Logic Programming to cases annotated with probability values. It investigates the approach of Learning from proofs and the issue of upgrading Fisher Kernels to Relational Fisher Kernels.

Covers developments from philosophy, artificial intelligence and information systems to formulate a collection of functional requirements for ontology development. This book looks at several ontology representation languages to show how they support the functional requirements, what deficiencies there are, and how they relate to each other.

Bringing artificial intelligence planning and scheduling applications into the real world is a hard task that is receiving more attention every day by researchers and practitioners from many fields. In many cases, it requires the integration of several underlying techniques like planning, scheduling, constraint satisfaction, mixed-initiative planning and scheduling, temporal reasoning, knowledge representation, formal models and languages, and technological issues. Most papers included in this book are clear examples on how to integrate several of these techniques. Furthermore, the book also covers many interesting approaches in application areas ranging from industrial job shop to electronic tourism, environmental problems, virtual teaching or space missions. This book also provides powerful techniques that allow to build fully deployable applications to solve real problems and an updated review of many of the most interesting areas of application of these technologies, showing how powerful these technologies are to overcome the expresiveness and efficiency problems of real world problems.

Introduces a particular methodology to build adaptive Web sites and presents the main concepts behind Web mining and applying them to adaptive Web sites. This book includes a chapter, which explains the Web mining process and the tools to analyze Web data, mainly focused in machine learning.

Investigates spontaneous, unpredictable uses of technology that are driven by social contexts and collaborative processes, based on our ability to communicate our presence, both virtual and physical, in symbolic ways. This book proposes a research model of design for emergence, focusing on emergent phenomena as part of an iterative design process.

This book is intended to provide a treatment of the theory and applications of Stochastic Neural Networks, that is networks able to learn random processes from experience, on the basis of recent developments on this subject.

Ever since the early days of machine learning and data mining, it has been realized that the traditional attribute-value and item-set representations are too limited for many practical applications. This book collects studies on mining and learning within graphs, trees and sequences in studies worldwide.

Modern databases and information systems essentially differ from their predecessors. Ontology-based and knowledge-based approaches to system development, UML based IS development methodologies, XML databases and heterogeneous information models have come to the fore. This book discusses these fundamental aspects.

Development of models with explicit mechanisms for data generation from cluster structures is of major interest in order to provide a theoretical framework for cluster structures found in data. This work proposes a framework for typological classification based on a fuzzy clustering model of data generation.

Modelling of information is necessary in developing information systems. Information is acquired from many sources, by using various methods and tools. This publication focuses on modelling of information, along with modelling of time.

This guide covers main issues in transforming the vast majority of models to be used in the context of the semantic web: XML schemas, relational models, UML diagrams, RDF schemas and ontologies. Different practical approaches are presented as well as discussions on some theoretical issues.

Current approaches to the development of legal knowledge-based systems (LKBS), such as the use of rule-based systems, case-based systems or logics, have obtained limited theoretical and practical results. This overview of the field describes present approaches and analyzes their problems.

Reflects on the discussion on using chaos theory for the study of society. This book explores the interface between chaos theory and the social sciences. A broad variety of fields (including Sociology, Anthropology, Economics, Political Science, Management, Philosophy and Cognitive Sciences) are represented.

Addresses several functional areas such as: planning, scheduling, monitoring, control, fault classification and diagnosis, training, and help desks. This book is of interest to researchers and professionals in telecommunication, AI experts, and graduate students.

If a technique represents a genuine advance in software engineering, then it has commercial advantage. This trend is more evident in the application of genetic algorithms (GAs). This book attempts to emphasise the diversity of the GA approach, by presenting descriptions of GAs used for real-world optimization and for complex modelling problems.

Focusing on data mining, this work is a joint effort from researchers in Japan, and includes a report on the forefront of data collection, user-centred mining and user interaction/reaction. It offers an overview of modern solutions with real-world applications, sharing hard-learned experiences.

A core technology for making the Semantic Web happen, but also to leverage application areas like Knowledge Management and E-Business, is the field of Semantic Annotation, which turns human-understandable content into a machine understandable form. This book reports on the broad range of technologies that are used to achieve this translation.

A collection of 26 papers, selected from the 119 presented at the VIII National Symposium on Pattern Recognition and Image Analysis, 1999. They are organized into categories reflecting: pattern recognition; speech recognition; image processing; computer vision; and applications.

Provides a detailed overview of Inductive Logic Programming, as well as a collection of technical contributions to it. This overview is based on the ESPRIT basic research project no 6020 on Inductive Logic Programming. It is useful for students, researchers and practitioners of artificial intelligence and computer science.

This volume provides an in-depth analysis of knowledge modelling technology, illustrating the main tenets of this paradigm, surveying the state of the art and then presenting in detail the application of this technology to parametric design problems.

This work contains a selection of contributions regarding intelligent systems by experts in diverse fields. Topics discussed are: applications of intelligent systems in modelling and prediction of environmental changes; and neural networks for signal processing.

This work examines the theory and applications of intelligent systems, such as neural networks, (adaptive) fuzzy logic, evolutionary computing and their hybrids and deriviatives.

This volume presents research from the interdisciplanary field of norms, logic and information systems, a cross-pollinations between traditional deontic logic and computer science.