Knowledge Representation plays an essential role in Semantic Web, in particular in automated information processing and communications among software agents. This book, entitled "Fuzzy Computational Ontologies in Contexts: Formal Models of Knowledge Representation with Membership Degree and Typicality, and Their Applications", discusses knowledge representation in Semantic Web. It introduces the relevant background knowledge, models of fuzzy ontologies, importance and priority of properties in concepts, and object typicality in fuzzy ontologies and context-aware ontologies. The book is intended for graduate students, engineers, and researchers in the field of artificial intelligence and computer science. Yi Cai is an Assistant Professor in School of Software Engineering, South China University of Technology, Guangzhou, China. Ching-man Au Yeung is a Senior Engineer in Hong Kong Applied Science and Technology Research Institute, Hong Kong, China. Ho-fung Leung is a Professor and the Chairman of Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong, China.

This book covers in a great depth the fast growing topic of tools, techniques and applications of soft computing (e.g., fuzzy logic, genetic algorithms, neural networks, rough sets, Bayesian networks, and other probabilistic techniques) in the ontologies and the Semantic Web. The author shows how components of the Semantic Web (like the RDF, Description Logics, ontologies) can be covered with a soft computing methodology.

Fuzzy set and logic theory suggest that all natural language linguistic expressions are imprecise and must be assessed as a matter of degree. But in general membership degree is an imprecise notion which requires that Type 2 membership degrees be considered in most applications related to human decision making schemas. Even if the membership functions are restricted to be Type1, their combinations generate an interval – valued Type 2 membership. This is part of the general result that Classical equivalences breakdown in Fuzzy theory. Thus all classical formulas must be reassessed with an upper and lower expression that are generated by the breakdown of classical formulas.Key features:- Ontological grounding- Epistemological justification- Measurement of Membership- Breakdown of equivalences- FDCF is not equivalent to FCCF- Fuzzy Beliefs- Meta-Linguistic axioms- Ontological grounding- Epistemological justification- Measurement of Membership- Breakdown of equivalences- FDCF is not equivalent to FCCF- Fuzzy Beliefs- Meta-Linguistic axioms

One of the major limitations of the Ambient Intelligent Systems today is the lack of semantic models of those activities on the environment, so that the system can recognize the specific activity being performed by the user(s) and act accordingly. In this context, this thesis addresses the general problem of knowledge representation in Smart Spaces. The main objective is to develop knowledge-based models, equipped with semantics to learn, infer and monitor human behaviours in Smart Spaces. Moreover, it is easy to recognize that some aspects of this problem have a high degree of uncertainty, and therefore, the developed models must be equipped with mechanisms to manage this type of information. As an added value, this system should be sufficiently simple and flexible to be managed by non-expert users, and thus, facilitate the transfer of research to industry. To do this, we develop graphical models to represent human behaviour in Smart Spaces, in order to provide them with more usability in the final application. As a result, human behaviour recognition can help assisting people with special needs such as independent elders, in remote rehabilitation monitoring, industrial process guidelines, and many other cases.

Welcome to the proceedings of the 2004 International Conference on Embedded and Ubiquitous Computing (EUC 2004) which was held in Aizu-Wakamatsu City, Japan, 25–27 August 2004. Embedded and ubiquitous computing are emerging rapidly as exciting new paradigms and disciplines to provide computing and communication services all the time, everywhere. Its systems are now invading every aspect of life to the point that they are disappearing inside all sorts of appliances or can be worn unobtrusively as part of clothing and jewelry, etc. This emergence is a natural outcome of research and technological advances in embedded systems, pervasive computing and communications, wireless networks, mobile computing, distri- ted computing and agent technologies, etc. Its explosive impact on academia, industry, government and daily life can be compared to that of electric motors over the past century but promises to revolutionize life much more profoundly than elevators, electric motors or even personal computer evolution ever did. The EUC 2004 conference provided a forum for engineers and scientists in academia, industry, and government to address all the resulting profound ch- lenges including technical, safety, social, legal, political, and economic issues, and to present and discuss their ideas, results, work in progress and experience on all aspects of embedded and ubiquitous computing. There was a very large number of paper submissions (260) from more than 20countriesandregions,includingnotonlyAsiaandthePaci?c,butalsoEurope and North America. All submissions were reviewed by at least three program or technical committee members or external reviewers.

This book constitutes the proceedings of the 10th International and Interdisciplinary Conference on Modeling and Using Context, CONTEXT 2017, held in Paris, France, in June 2017. The 26 full papers and 15 short papers presented were carefully reviewed and selected from 88 submissions. The papers feature research in a wide range of disciplines related to issues of context and contextual knowledge and discuss commonalities across and differences between the disciplines' approaches to the study of context. They are organized in the following topical sections: context in representation; context modeling of human activities; context in communication; context awareness; and various specific topics.

Provides research developments on mobile technologies and services. Explains how users of such applications access intelligent and adaptable information services, maximizing convenience and minimizing intrusion.

Bringing together an extensively researched area with an emerging research issue, Context-Aware Computing and Self-Managing Systems presents the core contributions of context-aware computing in the development of self-managing systems, including devices, applications, middleware, and networks. The expert contributors reveal the usefulness of contex

This book gathers authoritative contributions in the field of Soft Computing. Based on selected papers presented at the 7th World Conference on Soft Computing, which was held on May 29–31, 2018, in Baku, Azerbaijan, it describes new theoretical advances, as well as cutting-edge methods and applications. New theories and algorithms in fuzzy logic, cognitive modeling, graph theory and metaheuristics are discussed, and applications in data mining, social networks, control and robotics, geoscience, biomedicine and industrial management are described. This book offers a timely, broad snapshot of recent developments, including thought-provoking trends and challenges that are yielding new research directions in the diverse areas of Soft Computing.

This book constitutes the refereed proceedings of the 9th International Conference on Rough Sets and Current Trends in Computing, RSCTC 2014, held in Granada and Madrid, Spain, in July 2014. RSCTC 2014 together with the Conference on Rough Sets and Emerging Intelligent Systems Paradigms (RSEISP 2014) was held as a major part of the 2014 Joint Rough Set Symposium (JRS 2014) The 23 regular and 17 short papers presented were carefully reviewed and selected from 120 submissions. They are organized in topical sections such as fuzzy logic and rough set: tools for imperfect information; fuzzy-rough hybridization; three way decisions and probabilistic rough sets; new trends in formal concept analysis and related methods; fuzzy decision making and consensus; soft computing for learning from data; web information systems and decision making; image processing and intelligent systems.