Software methodologies, tools and techniques have become an ever more important part of our lives, and are crucial to the decision-making processes that affect us every day. This book presents papers from the 19th International Conference on New Trends in Intelligent Software Methodology Tools, and Techniques (SoMeT20), held in Kitakyushu, Japan from 22–24 September 2020. The SoMeT conferences bring together researchers and practitioners to share their original research results and experience of practical developments in software science and related new technologies, and this book explores new trends and theories that highlight the direction and development of intelligent software methodologies, tools and techniques. It covers newly developed techniques, enhanced methodologies, software related solutions and recently developed tools, as well as indicating the direction of future research, and the 40 revised papers included here have been selected by the SoMeT20 international reviewing committee on the basis of technical soundness, relevance, originality, significance, and clarity. The book is divided into 5 chapters: artificial intelligence techniques on software engineering, and requirement engineering; software methods for informatics, medical informatics and bio-medicine applications; applied software tools, techniques and related software engineering models; intelligent-software systems design, software quality, software evolution and validation techniques; and knowledge science and intelligent computing. Providing an overview of the state-of-the-art in software science and its supporting technology, this book will be of interest to all those working in the field.

The integration of AI with software is an essential enabler for science and the new economy, creating new markets and opportunities for a more reliable, flexible and robust society. Current software methodologies, tools and techniques often fall short of expectations, however, and much software remains insufficiently robust and reliable for a constantly changing and evolving market. This book presents 54 papers delivered at the 20th edition of the International Conference on New Trends in Intelligent Software Methodology Tools, and Techniques (SoMeT_21), held in Cancun, Mexico, from 21–23 September 2021. The aim of the conference was to capture the essence of a new state-of-the-art in software science and its supporting technology and to identify the challenges that such a technology will need to master, and this book explores the new trends and theories illuminating the direction of development in this field as it heads towards a transformation in the role of software and science integration in tomorrow’s global information society. The 54 revised papers were selected for publication by means of a rigorous review process involving 3 or 4 reviewers for each paper, followed by selection by the SoMeT_21 international reviewing committee. The book is divided into 9 chapters, classified by paper topic and relevance to the chapter theme. Covering topics ranging from research practices, techniques and methodologies to proposing and reporting on the solutions required by global business, the book offers an opportunity for the software science community to consider where they are today and where they are headed in the future.

The interdisciplinary field of fuzzy logic encompass applications in the electrical, industrial, chemical and engineering realms as well as in areas of management and environmental issues, while data mining covers new approaches to big data, massive data, and scalable, parallel and distributed algorithms. This book presents papers from the 6th International Conference on Fuzzy Systems and Data Mining (FSDM 2020). The conference was originally due to be held from 13-16 November 2020 in Xiamen, China, but was changed to an online conference held on the same dates due to ongoing restrictions connected with the COVID-19 pandemic. The annual FSDM conference provides a platform for knowledge exchange between international experts, researchers academics and delegates from industry. This year, the committee received 316 submissions, of which 76 papers were selected for inclusion in the conference; an acceptance rate of 24%. The conference covers four main areas: fuzzy theory; algorithms and systems, which includes topics like stability; foundations and control; and fuzzy applications, which are widely used and cover various types of processing as well as hardware and architecture for big data and time series. Providing a current overview of research and developments in fuzzy logic and data mining, the book will be of interest to all those working in the field of data science.

Human language technology is the study of the methods by which computer programs or electronic devices can analyze, produce, modify or respond to human texts and speech. It consists of natural language processing and computational linguistics on the one hand, and speech technology on the other. This book presents the proceedings of the 9th International Conference, Human Language Technologies – The Baltic Perspective (Baltic HLT 2020), organised in Kaunas, Lithuania on 22 and 23 September 2020. This biennial conference offers researchers a platform to share knowledge on recent advances in human language processing for the Baltic languages, as well as promoting interdisciplinary and international cooperation in human language-technology research within and beyond the Baltic States. In addition to the traditional topics of natural language processing and language technologies, this year’s conference featured a special session on resource and tool development for teaching and learning the less resourced Baltic languages. This year, 42 submissions were received, each of which was evaluated by two reviewers, resulting in a total of 34 papers being accepted for presentation and publication. The book is divided into four sections: speech and text analysis (9 papers); machine translation and natural understanding (6 papers); tools and resources (14 papers); and language learning resources (5 papers). Providing a fascinating overview of current research in the field from a primarily Baltic perspective, the book will be of interest to all those whose work involves human language technology.

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.

Information modeling and knowledge bases are important technologies for academic and industrial research that goes beyond the traditional borders of information systems and computer science. The amount and complexity of information to be dealt with grows continually, as do the levels of abstraction and the size of databases. This book presents the proceedings of the 30th International Conference on Information Modelling and Knowledge Bases (EJC2020), due to be held in Hamburg, Germany on 8 and 9 June 2020, but instead held as a virtual conference on the same dates due to the Corona-virus pandemic restrictions. The conference provides a research forum for the exchange of scientific results and experiences, and brings together experts from different areas of computer science and other disciplines with a common interest in information modeling and knowledge bases. The subject touches on many disciplines, with philosophy and logic, cognitive science, knowledge management, linguistics and management science, as well as the emerging fields of data science and machine learning, all being relevant areas. The 23 reviewed, selected, and upgraded contributions included here are the result of presentations, comments, and discussions from the conference, and reflect the themes of the conference sessions: learning and linguistics; systems and processes; data and knowledge representation; models and interfaces; formalizations and reasoning; models and modeling; machine learning; models and programming; environment and predictions; modeling emotion; and social networks. The book provides an overview of current research and applications, and will be of interest to all those working in the field.

FOIS is the flagship conference of the International Association for Ontology and its Applications, a non-profit organization which promotes interdisciplinary research and international collaboration at the intersection of philosophical ontology, linguistics, logic, cognitive science, and computer science, as well as in the applications of ontological analysis to conceptual modeling, knowledge engineering, knowledge management, information-systems development, library and information science, scientific research, and semantic technologies in general. This volume presents the 17 papers accepted for the 11th Formal Ontology in Information Systems conference (FOIS 2020). These papers cover a broad range of topics and are organized into 5 groups. Foundations is dedicated to the general ontological decisions providing a foundation for any ontology, both from a philosophical perspective and with an emphasis on applications. Social Entities is dedicated to the ontological analysis and formalization of various social entities, including secrets, legal theories, decisions, kinship, and cultural heritage. The papers in Intentionality and Embodiment analyze aspects of an agent's intentions, beliefs and desires, as well as the embodiment of functional relations. The section on Parts and Wholes is dedicated to mereology as well as the mereological analysis of certain types of entities (e.g., pluralities, information entities, and computer programs). Lastly, the papers in Methods are about ontology evaluation and use. Altogether, the papers reflect traditional FOIS themes with perhaps a greater emphasis on social and agent aspects, and will be of interest to all those whose work involves ontology and its applications.

Software has become ever more crucial as an enabler, from daily routines to important national decisions. But from time to time, as society adapts to frequent and rapid changes in technology, software development fails to come up to expectations due to issues with efficiency, reliability and security, and with the robustness of methodologies, tools and techniques not keeping pace with the rapidly evolving market. This book presents the proceedings of SoMeT_19, the 18th International Conference on New Trends in Intelligent Software Methodologies, Tools and Techniques, held in Kuching, Malaysia, from 23–25 September 2019. The book explores new trends and theories that highlight the direction and development of software methodologies, tools and techniques, and aims to capture the essence of a new state of the art in software science and its supporting technology, and to identify the challenges that such a technology will have to master. The book also investigates other comparable theories and practices in software science, including emerging technologies, from their computational foundations in terms of models, methodologies, and tools. The 56 papers included here are divided into 5 chapters: Intelligent software systems design and techniques in software engineering; Machine learning techniques for software systems; Requirements engineering, software design and development techniques; Software methodologies, tools and techniques for industry; and Knowledge science and intelligent computing. This comprehensive overview of information systems and research projects will be invaluable to all those whose work involves the assessment and solution of real-world software problems.

The management of any modern organisation involves data, but the volume of information has become almost impossible for even the most up-to-date computer system to handle. Fortunately, big-data technologies are now enabling new ways of dealing with the flood of information, making an approximate solution possible in a reasonable time-frame, as an alternative to waiting for an exact result taking much longer. This book contains the 17 papers presented at the inaugural conference of the new series: Modern Management based on Big Data (MMBD 2020). The conference was originally scheduled to be held in Beijing, China, but due to measures to prevent the spread of the COVID-19 pandemic, the conference was held online from 18-21 October 2020. As its name suggests, the conference covers the connected aspects of Big Data and Modern Management, and the 17 papers included here, accepted from a total of 68 submissions, cover topics including data capture and storage; search, sharing and analytics; data visualization; machine learning algorithms for big data; distributed file systems and databases; management strategy and decision making; manufacturing and logistics systems; total quality management; management information systems; human factor engineering; and human resources. Providing an overview of current developments in modern management based on Big Data, the book will be of interest to all those working in the field.

Machine learning and artificial intelligence are already widely applied to facilitate our daily lives, as well as scientific research, but with the world currently facing a global COVID-19 pandemic, their capacity to provide an important tool to support those searching for a way to combat the novel corona virus has never been more important. This book presents the proceedings of the International Conference on Machine Learning and Intelligent Systems (MLIS 2020), which was due to be held in Seoul, Korea, from 25-28 October 2020, but which was delivered as an online conference on the same dates due to COVID-19 restrictions. MLIS 2020 was the latest in a series of annual conferences that aim to provide a platform for exchanging knowledge about the most recent scientific and technological advances in the field of machine learning and intelligent systems. The annual conference also strengthens links within the scientific community in related research areas. The book contains 53 papers, selected from more than 160 submissions and presented at MLIS 2020. Selection was based on the results of review and scored on: originality, scientific/practical significance, compelling logical reasoning and language. Topics covered include: data mining, image processing, neural networks, human health, natural language processing, video processing, computational intelligence, expert systems, human-computer interaction, deep learning, and robotics. Offering a current overview of research and developments in machine learning and artificial intelligence, the book will be of interest to all those working in the field.