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This volume constitutes the refereed proceedings of the Confederated International International Workshop on Enterprise Integration, Interoperability and Networking (EI2N ), Fact Based Modeling ( FBM), Industry Case Studies Program ( ICSP ), International Workshop on Methods, Evaluation, Tools and Applications for the Creation and Consumption of Structured Data for the e-Society (Meta4eS) and, 1st International Workshop on Security via Information Analytics and Applications (SIAnA 2019) held as part of OTM 2018 in October 2019 in Rhodes, Greece. As the three main conferences and the associated workshops all share the distributed aspects of modern computing systems, they experience the application pull created by the Internet and by the so-called Semantic Web, in particular developments of Big Data, increased importance of security issues, and the globalization of mobile-based technologies.
This volume LNCS 11877 constitutes the refereed proceedings of the Confederated International Conferences: Cooperative Information Systems, CoopIS 2019, Ontologies, Databases, and Applications of Semantics, ODBASE 2019, and Cloud and Trusted Computing, C&TC, held as part of OTM 2019 in October 2019 in Rhodes, Greece. The 38 full papers presented together with 8 short papers were carefully reviewed and selected from 156 submissions. The OTM program every year covers data and Web semantics, distributed objects, Web services, databases, informationsystems, enterprise workflow and collaboration, ubiquity, interoperability, mobility, grid and high-performance computing.
This volume constitutes the refereed proceedings of the Confederated International International Workshop on Enterprise Integration, Interoperability and Networking (EI2N ), Fact Based Modeling ( FBM), Industry Case Studies Program ( ICSP ), and International Workshop on Methods, Evaluation, Tools and Applications for the Creation and Consumption of Structured Data for the e-Society (Meta4eS), held as part of OTM 2018 in October 2018 in Valletta, Malta. As the three main conferences and the associated workshops all share the distributed aspects of modern computing systems, they experience the application pull created by the Internet and by the so-called Semantic Web, in particular developments of Big Data, increased importance of security issues, and the globalization of mobile-based technologies.
The field of legal knowledge and information systems has traditionally been concerned with the subjects of legal knowledge representation and engineering, computational models of legal reasoning, and the analysis of legal data, but recent years have also seen an increasing interest in the application of machine learning methods to ease and empower the everyday activities of legal experts. This book presents the proceedings of the 33rd International Conference on Legal Knowledge and Information Systems (JURIX 2020), organised this year as a virtual event on 9–11 December 2020 due to restrictions resulting from the Covid-19 pandemic. For more than three decades, the annual JURIX international conference, which now also includes demo papers, has provided a platform for academics and practitioners to exchange knowledge about theoretical research and applications in concrete legal use cases. A total of 85 submissions by 255 authors from 28 countries were received for the conference, and after a rigorous review process, 20 were selected for publication as full papers, 14 as short papers, and 5 as demo papers. This selection process resulted in a total acceptance rate of 40% (full and short papers) and a competitive 23.5% acceptance rate for full papers. Topics span from computational models of legal argumentation, case-based reasoning, legal ontologies, smart contracts, privacy management and evidential reasoning to information extraction from different types of text in legal documents, and ethical dilemmas. Providing a state-of-the-art overview of developments in the field, this book will be of interest to all those working with legal knowledge and information systems.
Artificial Intelligence and Machine Learning for Predictive and Analytical Rendering in Edge Computing focuses on the role of AI and machine learning as it impacts and works alongside Edge Computing. Sections cover the growing number of devices and applications in diversified domains of industry, including gaming, speech recognition, medical diagnostics, robotics and computer vision and how they are being driven by Big Data, Artificial Intelligence, Machine Learning and distributed computing, may it be Cloud Computing or the evolving Fog and Edge Computing paradigms. Challenges covered include remote storage and computing, bandwidth overload due to transportation of data from End nodes to Cloud leading in latency issues, security issues in transporting sensitive medical and financial information across larger gaps in points of data generation and computing, as well as design features of Edge nodes to store and run AI/ML algorithms for effective rendering. - Provides a reference handbook on the evolution of distributed systems, including Cloud, Fog and Edge Computing - Integrates the various Artificial Intelligence and Machine Learning techniques for effective predictions at Edge rather than Cloud or remote Data Centers - Provides insight into the features and constraints in Edge Computing and storage, including hardware constraints and the technological/architectural developments that shall overcome those constraints
This book presents the latest advances in machine intelligence and big data analytics to improve early warning of cyber-attacks, for cybersecurity intrusion detection and monitoring, and malware analysis. Cyber-attacks have posed real and wide-ranging threats for the information society. Detecting cyber-attacks becomes a challenge, not only because of the sophistication of attacks but also because of the large scale and complex nature of today’s IT infrastructures. It discusses novel trends and achievements in machine intelligence and their role in the development of secure systems and identifies open and future research issues related to the application of machine intelligence in the cybersecurity field. Bridging an important gap between machine intelligence, big data, and cybersecurity communities, it aspires to provide a relevant reference for students, researchers, engineers, and professionals working in this area or those interested in grasping its diverse facets and exploring the latest advances on machine intelligence and big data analytics for cybersecurity applications.
This book constitutes revised selected papers from the International Workshops held at the Second International Conference on Process Mining, ICPM 2020, which took place during October 4-9, 2020. The conference was planned to take place in Padua, Italy, but had to be held online due to the COVID-19 pandemic. The conference focuses on the area of process mining research and practice, including theory, algorithmic challenges, and applications. The co-located workshops provided a forum for novel research ideas. The 29 papers included in this volume were carefully reviewed and selected from 59 submissions. They stem from the following workshops: 1st International Workshop on Event Data and Behavioral Analytics (EDBA) 1st International Workshop on Leveraging Machine Learning in Process Mining (ML4PM) 1st International Workshop on Streaming Analytics for Process Mining (SA4PM'20) 5th International Workshop on Process Querying, Manipulation, and Intelligence (PQMI) 3rd International Workshop on Process-Oriented Data Science for Healthcare (PODS4H) 1st International Workshop on Trust and Privacy in Process Analytics (TPPA)
SEMANTIC WEB FOR EFFECTIVE HEALTHCARE SYSTEMS The book summarizes the trends and current research advances in web semantics, delineating the existing tools, techniques, methodologies, and research solutions Semantic Web technologies have the opportunity to transform the way healthcare providers utilize technology to gain insights and knowledge from their data and make treatment decisions. Both Big Data and Semantic Web technologies can complement each other to address the challenges and add intelligence to healthcare management systems. The aim of this book is to analyze the current status on how the semantic web is used to solve health data integration and interoperability problems, and how it provides advanced data linking capabilities that can improve search and retrieval of medical data. Chapters analyze the tools and approaches to semantic health data analysis and knowledge discovery. The book discusses the role of semantic technologies in extracting and transforming healthcare data before storing it in repositories. It also discusses different approaches for integrating heterogeneous healthcare data. This innovative book offers: The first of its kind and highlights only the ontology driven information retrieval mechanisms and techniques being applied to healthcare as well as clinical information systems; Presents a comprehensive examination of the emerging research in areas of the semantic web; Discusses studies on new research areas including ontological engineering, semantic annotation and semantic sentiment analysis; Helps readers understand key concepts in semantic web applications for the biomedical engineering and healthcare fields; Includes coverage of key application areas of the semantic web. Audience: Researchers and graduate students in computer science, biomedical engineering, electronic and software engineering, as well as industry scientific researchers, clinicians, and systems managers in biomedical fields.
Semantic computing is an integral part of modern technology, an essential component of fields as diverse as artificial intelligence, data science, knowledge discovery and management, big data analytics, e-commerce, enterprise search, technical documentation, document management, business intelligence, and enterprise vocabulary management. This book presents the proceedings of SEMANTICS 2023, the 19th International Conference on Semantic Systems, held in Leipzig, Germany, from 20 to 22 September 2023. The conference is a pivotal event for those professionals and researchers actively engaged in harnessing the power of semantic computing, an opportunity to increase their understanding of the subject’s transformative potential while confronting its practical limitations. Attendees include information managers, IT architects, software engineers, and researchers from a broad spectrum of organizations, including research facilities, non-profit entities, public administrations, and the world's largest corporations. For this year’s conference a total of 54 submissions were received in response to a call for papers. These were subjected to a rigorous, double-blind review process, with at least three independent reviews conducted for each submission. The 16 papers included here were ultimately accepted for presentation, with an acceptance rate of 29.6%. Areas covered include novel research challenges in areas such as data science, machine learning, logic programming, content engineering, social computing, and the Semantic Web. The book provides an up-to-date overview, which will be of interest to all those wishing to stay abreast of emerging trends and themes within the vast field of semantic computing.