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This book constitutes refereed proceedings of the 2nd International Semantic Intelligence Conference (ISIC 2022). This book covers a wide range of topics, including semantic web engineering, ontology-based data access, multimodal and multilingual access, machine-to-machine communications and interoperability, knowledge extraction and ontology learning from the web, computational paradigms and computational intelligence, distributed and mobile systems, and many others. This book includes novel contributions and the latest developments from researchers across industry and academia. This book serves as a valuable reference resource for academics and researchers across the globe.
The data that must be processed in healthcare includes text, numbers, statistics, and images, and healthcare systems are continuously acquiring novel data from cutting-edge technologies like wearable devices. Semantic intelligence technologies, such as artificial intelligence, machine learning, and the internet of things, together with the hybrid methodologies which combine these approaches, are central to the development of the intelligent, knowledge-based systems now used in healthcare. This book, Roles and Challenges of Semantic Intelligence in Healthcare Cognitive Computing explores those emerging fields of science and technology in which cognitive computing techniques offer the effective solutions poised to impact healthcare in the foreseeable future, minimizing errors and improving the effectiveness of personalized care models. The book assesses the current landscape, and identifies the roles and challenges of integrating cognitive computing techniques into the widespread adoption of innovative smart healthcare solutions. Each chapter is the result of collaboration by experts from various domains, and provides a detailed overview of the potential offered by new technologies in the field. A wide spectrum of topics and emerging trends are covered, reflecting the multidisciplinary nature of healthcare and cognitive computing and including digital twins, eXplainable AI, AI-based decision-support systems in intensive care, and culinary healthcare, as well as the semantic internet of things (SIoT), natural language processing, and deep learning and graph models. The book presents new ideas which will facilitate collaboration among the different disciplines involved, and will be of interest to all those working in this rapidly evolving field.
Featuring chapters by selected contributors to the second international Ontology for the Intelligence Community (OIC) conference, this book offers a partial technology roadmap for decision makers in the field of information integration, sharing and situational awareness in the use of ontologies and semantic technologies for intelligence.
As modern technologies continue to develop and evolve, the ability of users to adapt with new systems becomes a paramount concern. Research into new ways for humans to make use of advanced computers and other such technologies through artificial intelligence and computer simulation is necessary to fully realize the potential of tools in the 21st century. Advanced Methodologies and Technologies in Artificial Intelligence, Computer Simulation, and Human-Computer Interaction provides emerging research in advanced trends in robotics, AI, simulation, and human-computer interaction. Readers will learn about the positive applications of artificial intelligence and human-computer interaction in various disciples such as business and medicine. This book is a valuable resource for IT professionals, researchers, computer scientists, and researchers invested in assistive technologies, artificial intelligence, robotics, and computer simulation.
Ontologies are now increasingly used to integrate, and organize data and knowledge, particularly in data and knowledge-intensive applications in both research and industry. The book is devoted to semantic data mining – a data mining approach where domain ontologies are used as background knowledge, and where the new challenge is to mine knowledge encoded in domain ontologies and knowledge graphs, rather than only purely empirical data. The introductory chapters of the book provide theoretical foundations of both data mining and ontology representation. Taking a unified perspective, the book then covers several methods for semantic data mining, addressing tasks such as pattern mining, classification and similarity-based approaches. It attempts to provide state-of-the-art answers to specific challenges and peculiarities of data mining with use of ontologies, in particular: How to deal with incompleteness of knowledge and the so-called Open World Assumption? What is a truly “semantic” similarity measure? The book contains several chapters with examples of applications of semantic data mining. The examples start from a scenario with moderate use of lightweight ontologies for knowledge graph enrichment and end with a full-fledged scenario of an intelligent knowledge discovery assistant using complex domain ontologies for meta-mining, i.e., an ontology-based meta-learning approach to full data mining processes. The book is intended for researchers in the fields of semantic technologies, knowledge engineering, data science, and data mining, and developers of knowledge-based systems and applications.
This book is an attempt to establish in the readers the importance of creating interoperable data stores and writing rules for handling this data. It also covers extracts from a few project dissertations and a research funded project that the author had supervised.• Describes the power of ontologies for better data management• Provides an overview of knowledge engineering including ontology engineering, tools and techniques• Provides sample development procedures for creating two domain ontologies.• Depicts the utility of ontological representation in situation awareness• Demonstrates recommendation engine for unconventional emergencies using a hybrid reasoning approach.• The text explains how to make better utilization of resources when emergency strikesGraduates and undergraduates doing courses in artificial intelligence, semantic web and knowledge engineering will find this book beneficial.
Hardbound. Semantic Networks are graphic structures used to represent concepts and knowledge in computers. Key uses include natural language understanding, information retrieval, machine vision, object-oriented analysis and dynamic control of combat aircraft. This major collection addresses every level of reader interested in the field of knowledge representation. Easy to read surveys of the main research families, most written by the founders, are followed by 25 widely varied articles on semantic networks and the conceptual structure of the world. Some extend ideas of philosopher Charles S Peirce 100 years ahead of his time. Others show connections to databases, lattice theory, semiotics, real-world ontology, graph-grammers, lexicography, relational algebras, property inheritance and semantic primitives. Hundreds of pictures show semantic networks as a visual language of thought.
This two-volume set (CCIS 1005 and CCIS 1006) constitutes the refereed proceedings of the 4th International Conference on Cognitive Systems and Signal Processing, ICCSIP2018, held in Beijing, China, in November and December 2018. The 96 revised full papers presented were carefully reviewed and selected from 169 submissions. The papers are organized in topical sections on vision and image; algorithms; robotics; human-computer interaction; deep learning; information processing and automatic driving.
In recent years, our world has experienced a profound shift and progression in available computing and knowledge sharing innovations. These emerging advancements have developed at a rapid pace, disseminating into and affecting numerous aspects of contemporary society. This has created a pivotal need for an innovative compendium encompassing the latest trends, concepts, and issues surrounding this relevant discipline area. During the past 15 years, the Encyclopedia of Information Science and Technology has become recognized as one of the landmark sources of the latest knowledge and discoveries in this discipline. The Encyclopedia of Information Science and Technology, Fourth Edition is a 10-volume set which includes 705 original and previously unpublished research articles covering a full range of perspectives, applications, and techniques contributed by thousands of experts and researchers from around the globe. This authoritative encyclopedia is an all-encompassing, well-established reference source that is ideally designed to disseminate the most forward-thinking and diverse research findings. With critical perspectives on the impact of information science management and new technologies in modern settings, including but not limited to computer science, education, healthcare, government, engineering, business, and natural and physical sciences, it is a pivotal and relevant source of knowledge that will benefit every professional within the field of information science and technology and is an invaluable addition to every academic and corporate library.
These are exciting times in the fields of Fuzzy Logic and the Semantic Web, and this book will add to the excitement, as it is the first volume to focus on the growing connections between these two fields. This book is expected to be a valuable aid to anyone considering the application of Fuzzy Logic to the Semantic Web, because it contains a number of detailed accounts of these combined fields, written by leading authors in several countries. The Fuzzy Logic field has been maturing for forty years. These years have witnessed a tremendous growth in the number and variety of applications, with a real-world impact across a wide variety of domains with humanlike behavior and reasoning. And we believe that in the coming years, the Semantic Web will be major field of applications of Fuzzy Logic. This book, the first in the new series Capturing Intelligence, shows the positive role Fuzzy Logic, and more generally Soft Computing, can play in the development of the Semantic Web, filling a gap and facing a new challenge. It covers concepts, tools, techniques and applications exhibiting the usefulness, and the necessity, for using Fuzzy Logic in the Semantic Web. It finally opens the road to new systems with a high Web IQ. Most of today's Web content is suitable for human consumption. The Semantic Web is presented as an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation. For example, within the Semantic Web, computers will understand the meaning of semantic data on a web page by following links to specified ontologies. But while the Semantic Web vision and research attracts attention, as long as it will be used two-valued-based logical methods no progress will be expected in handling ill-structured, uncertain or imprecise information encountered in real world knowledge. Fuzzy Logic and associated concepts and techniques (more generally, Soft Computing), has certainly a positive role to play in the development of the Semantic Web. Fuzzy Logic will not supposed to be the basis for the Semantic Web but its related concepts and techniques will certainly reinforce the systems classically developed within W3C. In fact, Fuzzy Logic cannot be ignored in order to bridge the gap between human-understandable soft logic and machine-readable hard logic. None of the usual logical requirements can be guaranteed: there is no centrally defined format for data, no guarantee of truth for assertions made, no guarantee of consistency. To support these arguments, this book shows how components of the Semantic Web (like XML, RDF, Description Logics, Conceptual Graphs, Ontologies) can be covered, with in each case a Fuzzy Logic focus. - First volume to focus on the growing connections between Fuzzy Logic and the Semantic Web - Keynote chapter by Lotfi Zadeh - The Semantic Web is presently expected to be a major field of applications of Fuzzy Logic - It fills a gap and faces a new challenge in the development of the Semantic Web - It opens the road to new systems with a high Web IQ - Contributed chapters by Fuzzy Logic leading experts