The Internet of Services and the Internet of Things are major building blocks of the Future Internet. The digital enterprise of the future is based not only on mobile, social, and cloud technologies, but also on se­mantic technologies and the future Internet of Everything. Semantic technologies now enable mass cus­tomization for the delivery of goods and services that meet individual customer needs and tastes with near mass production efficiency and reliability. This is creating a competitive advantage in the industrial econ­omy, the service economy, and the emerging data economy, leading to smart products, smart services, and smart data, all adaptable to specific tasks, locations, situations, and contexts of smart spaces. Such tech­nologies allow us to describe, revise, and adapt the characteristics, functions, processes, and usage patterns of customization targets on the basis of machine-understandable content representation that enables auto­mated processing and information sharing between human and software agents.   This book explains the principal achievements of the Theseus research program, one of the central pro­grams in the German government's Digital 2015 initiative and its High-Tech Strategy 2020. The methods, toolsets, and standards for semantic technologies developed during this program form a solid basis for the fourth industrial revolution (Industrie 4.0), the hybrid service economy, and the transformation of big data into useful smart data for the emerging data economy.   The contributing authors are leading scientists and engineers, representing world-class academic and in­dustrial research teams, and the ideas, technologies, and representative use cases they describe in the book derive from results in multidisciplinary fields, such as the Internet of Services; the Semantic Web, and semantic technologies, knowledge management, and search; user interfaces, multimodal interaction, and visualization; machine learning and data mining; and business process support, manufacturing, automa­tion, medical systems, and integrated service engineering.   The book will be of value to both researchers and practitioners in these domains.

The Internet of Services and the Internet of Things are major building blocks of the Future Internet. The digital enterprise of the future is based not only on mobile, social, and cloud technologies, but also on semantic technologies and the future Internet of Everything. Semantic technologies now enable mass customization for the delivery of goods and services that meet individual customer needs and tastes with near mass production efficiency and reliability. This is creating a competitive advantage in the industrial economy, the service economy, and the emerging data economy, leading to smart products, smart services, and smart data, all adaptable to specific tasks, locations, situations, and contexts of smart spaces. Such technologies allow us to describe, revise, and adapt the characteristics, functions, processes, and usage patterns of customization targets on the basis of machine-understandable content representation that enables automated processing and information sharing between human and software agents.

This book explains the principal achievements of the Theseus research program, one of the central programs in the German government's Digital 2015 initiative and its High-Tech Strategy 2020. The methods, toolsets, and standards for semantic technologies developed during this program form a solid basis for the fourth industrial revolution (Industrie 4.0), the hybrid service economy, and the transformation of big data into useful smart data for the emerging data economy.

The contributing authors are leading scientists and engineers, representing world-class academic and industrial research teams, and the ideas, technologies, and representative use cases they describe in the book derive from results in multidisciplinary fields, such as the Internet of Services; the Semantic Web, and semantic technologies, knowledge management, and search; user interfaces, multimodal interaction, and visualization; machine learning and data mining; and business process support, manufacturing, automation, medical systems, and integrated service engineering.

The book will be of value to both researchers and practitioners in these domains."

In just few years, case-based reasoning has evolved from a research topic studied at a small number of specialized academic labs into an industrial-strength technology applied in various fields. The INRECA methodology presented in detail in this monograph provides a data analysis framework for developing case-based reasoning solutions for successful applications in real-world industrial contexts.

The book is divided into parts on:

- smarter business with case-based decision support;
- developing case-based applications using the INRECA methodology; and
- using the methodology in various application domains.

The book provides a self-contained introduction to case-based reasoning applications that address both R&D professionals and general IT managers interested in this powerful new technology.

In this second edition, improvements and updates have been incorporated throughout the text. Particularly useful is the systematic coverage of experience factory applications at various steps; and, of course, the references have been extended substantially.

This volume presents the 36 full refereed papers selected from the presentations at the First European Workshop on Case-Based Reasoning, held at Kaiserslautern, Germany in November 1993.
Case-based reasoning (CBR) has recently attracted much interest among AI researchers: it supports knowledge acquisition and problem solving, and it is related to machine learning, analogical reasoning, cognitive modeling, similarity, and information retrieval. EWCBR is now established as the prime European forum for CBR research. This volume reflects the importance of this dynamic area of research through essential contributions to all aspects of CBR research and advanced applications.

Humanexpertsarenotsystemsofrules,theyarelibrariesofexperiences. Riesbeck and Schank (1989, p.15) Broadlyspeaking,case-basedreasoning(CBR)is concernedwith solvingnew problems by adapting solutions that worked for similar problems in the past. As with Arti cial Intelligence in general, case-based reasoning deals with two di erent aspects of intelligence: A r st motivation is to establish cog- tive models in order to understand human thinking and behavior. A second motivationis to buildsystemswhichhelpto solvereal-worldproblems.These twofacetscanbeconsideredastwosidesofthesamecoin.Traditionally,CBR researchinEuropehasconcentratedverymuchonthesecondaspect,though, of course, successful projects are not possible without a sound theory. The objective of this book is to summarize the results of recent years of research in CBR. A strong emphasis is put on projects performed and - plications developed in Germany. However, research has not been performed in isolation. Rather, a large number of cooperations between research sites throughout the world have been established which provided a fertile ground for the community. Hence, it is only natural that work from colleagues from France, Ireland, the Netherlands, and the United States has been included in this volume. This book is not intended to be a textbook giving a comprehensive overview of the eld. Rather, the objective is to consider in detail di - ent potential application areas, to work out the pros and cons of using CBR and to summarize the lessons learned from projects. For this, we assume that the reader already has at least a basic understanding of what case-based reasoning is all about.