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...

Knowledge acquisition has become a major area of artificial intelligence and cognitive science research. The papers in this book show that the area of knowledge acquisition for knowledge-based systems is still a diverse field in which a large number of research topics are being addressed. However, several main themes run through the papers. First, the issue of integrating knowledge from different sources and tools is a sallent topic in many papers. A second major topic in the papers is that of knowledge modelling. Research in knowledge-based systems emphasizes the use of generic models of...

This volume brings together ontology learning, knowledge acquisition and other related topics. It presents current research in ontology learning, addressing three perspectives. The first perspective looks at methodologies that have been proposed to automatically extract information from texts and to give a structured organization to such knowledge, including approaches based on machine learning techniques. Then there are evaluation methods for ontology learning, aiming at defining procedures and metrics for a quantitative evaluation of the ontology learning task; and finally application...

In order for information systems supporting two different organizations to interoperate, there must be an agreement as to what the words mean. There are many such agreements in place, supporting information systems interoperation in many different application areas. Most of these agreements have been created as part of diverse systems development processes, but since the advent of the Semantic Web in the late 1990s, they have been studied as a kind of software artifact in their own right, called an ontology, or description of a shared world. This book brings together developments from...

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

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 can be presented in two different ways. Firstly, it introduces a particular methodology to build adaptive Web sites and secondly, it presents the main concepts behind Web mining and then applying them to adaptive Web sites. In this case, Adaptive Web Sites is the case study to exemplify the tools introduced in the text. The authors start by introducing the Web and motivating the need for adaptive Web sites. The second chapter introduces the main concepts behind a Web site: its operation, its associated data and structure, user sessions, etc. Chapter three explains the Web mining...

The application of Data Mining (DM) technologies has shown an explosive growth in an increasing number of different areas of business, government and science. Two of the most important business areas are finance, in particular in banks and insurance companies, and e-business, such as web portals, e-commerce and ad management services. In spite of the close relationship between research and practice in Data Mining, it is not easy to find information on some of the most important issues involved in real world application of DM technology, from business and data understanding to evaluation and...

This publication presents the latest innovations and achievements of academic communities on Decision Support Systems (DSS). These advances include theory systems, computer-aided methods, algorithms, techniques and applications related to supporting decision making. The aim is to develop approaches for applying information systems technology to increase the effectiveness of decision making in situations where the computer system can support and enhance human judgements in the performance of tasks that have elements which cannot be specified in advance. Also it is intended to improve ways of...