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Papers direct the focus of interest to the development and use of conceptual models in information systems of various kinds and aim at improving awareness about general or specific problems and solutions in conceptual modelling.
This book describes in detail the relationship between symbolic representations of knowledge and abstract states of knowledge, exploring along the way the foundations of knowledge, knowledge bases, knowledge-based systems, and knowledge representation and reasoning. The idea of knowledge bases lies at the heart of symbolic, or "traditional," artificial intelligence. A knowledge-based system decides how to act by running formal reasoning procedures over a body of explicitly represented knowledge—a knowledge base. The system is not programmed for specific tasks; rather, it is told what it needs to know and expected to infer the rest. This book is about the logic of such knowledge bases. It describes in detail the relationship between symbolic representations of knowledge and abstract states of knowledge, exploring along the way the foundations of knowledge, knowledge bases, knowledge-based systems, and knowledge representation and reasoning. Assuming some familiarity with first-order predicate logic, the book offers a new mathematical model of knowledge that is general and expressive yet more workable in practice than previous models. The book presents a style of semantic argument and formal analysis that would be cumbersome or completely impractical with other approaches. It also shows how to treat a knowledge base as an abstract data type, completely specified in an abstract way by the knowledge-level operations defined over it.
Information modeling and knowledge bases have become an important area of academic and industry research in the 21st century, addressing complexities of modeling that reach beyond the traditional borders of information systems and academic computer science research. This book presents 32 reviewed, selected and updated papers delivered at the 29th International Conference on Information Modeling and Knowledge Bases (EJC2019), held in Lappeenranta, Finland, from 3 to 7 June 2019. In addition, two papers based on the keynote presentations and one paper edited from the discussion of the panel session are included in the book. The conference provided a forum to exchange scientific results and experience, and attracted academics and practitioners working with information and knowledge. The papers cover a wide range of topics, ranging from knowledge discovery through conceptual and linguistic modeling, knowledge and information modeling and discovery, cross-cultural communication and social computing, environmental modeling and engineering, and multimedia data modeling and systems to complex scientific problem-solving. The conference presentation sessions: Learning and Linguistics; Systems and Processes; Data and Knowledge Representation; Models and Interface; Formalizations and Reasoning; Models and Modeling; Machine Learning; Models and Programming; Environment and Predictions; and Emotion Modeling and Social Networks reflect the main themes of the conference. The book also includes 2 extended publications of keynote addresses: ‘Philosophical Foundations of Conceptual Modeling’ and ́Sustainable Solid Waste Management using Life Cycle Modeling for Environmental Impact Assessment’, as well as additional material covering the discussion and findings of the panel session. Providing an overview of current research in the field, the book will be of interest to all those working with information systems, information modeling and knowledge bases.
A monograph for specialists interested in building maintainable knowledge based systems, giving a unified methodology for the design of such systems
Information modelling and knowledge bases have become ever more essential in recent years because of the need to handle and process the vast amounts of data which now form part of everyday life. The machine to machine communication of the Internet of Things (IoT), in particular, can generate unexpectedly large amounts of raw data. This book presents the proceedings of the 27th International Conference on Information Modelling and Knowledge Bases (EJC2017), held in Krabi, Thailand, in June 2017. The EJC conferences originally began in 1982 as a co-operative initiative between Japan and Finland, but have since become a world-wide research forum bringing together researchers and practitioners in information modelling and knowledge bases for the exchange of scientific results and achievements. Of the 42 papers submitted, 29 were selected for publication here, and these cover a wide range of information-modelling topics, including the theory of concepts, semantic computing, data mining, context-based information retrieval, ontological technology, image databases, temporal and spatial databases, document data management, software engineering, cross-cultural computing, environmental analysis, social networks, and WWW information. The book will be of interest to all those whose work involves dealing with large amounts of data.
Within the last three decades, information modelling and knowledge bases have become essential subjects, not only for academic communities related to information systems and computer science, but also for businesses where information technology is applied. This book presents the proceedings of EJC 2014, the 24th International Conference on Information Modelling and Knowledge Bases, held in Kiel, Germany, in June 2014. The main themes of the conference were: conceptual modelling, including modelling and specification languages, domain specific conceptual modelling, and validating and communicating conceptual models; knowledge and information modelling and discovery, including knowledge representation and knowledge management, advanced data mining and analysis methods, as well as information recognition and information modelling; linguistics modelling; cross-cultural communication and social computing; environmental modelling; and multimedia data modelling and systems, which includes modelling multimedia information and knowledge, content-based multimedia data management, content-based multimedia retrieval as well as privacy and context enhancing technologies. This book will be of interest to all those who wish to keep abreast of new developments in the field of information modelling and knowledge bases.
There is an increasing need throughout the biomedical sciences for a greater understanding of knowledge-based systems and their application to genomic and proteomic research. This book discusses knowledge-based and statistical approaches, along with applications in bioinformatics and systems biology. The text emphasizes the integration of different methods for analysing and interpreting biomedical data. This, in turn, can lead to breakthrough biomolecular discoveries, with applications in personalized medicine. Key Features: Explores the fundamentals and applications of knowledge-based and statistical approaches in bioinformatics and systems biology. Helps readers to interpret genomic, proteomic, and metabolomic data in understanding complex biological molecules and their interactions. Provides useful guidance on dealing with large datasets in knowledge bases, a common issue in bioinformatics. Written by leading international experts in this field. Students, researchers, and industry professionals with a background in biomedical sciences, mathematics, statistics, or computer science will benefit from this book. It will also be useful for readers worldwide who want to master the application of bioinformatics to real-world situations and understand biological problems that motivate algorithms.
This book provides a comprehensive yet concise coverage of the concepts and technology of database systems and their evolution into knowledge-bases. The traditional material on database systems at senior undergraduate level is covered. An understanding of concepts is emphasized avoiding extremes in formalism or detail.Rather than be restricted to a single example used over an entire book, a variety of examples are used. These enable the reader to understand the basic abstractions which underlie description of many practical situations.A major portion of the book concerns database system technology with focus on the relational model. Various topics are discussed in detail, preparing the ground for more advanced work.
This open access book covers all facets of entity-oriented search—where “search” can be interpreted in the broadest sense of information access—from a unified point of view, and provides a coherent and comprehensive overview of the state of the art. It represents the first synthesis of research in this broad and rapidly developing area. Selected topics are discussed in-depth, the goal being to establish fundamental techniques and methods as a basis for future research and development. Additional topics are treated at a survey level only, containing numerous pointers to the relevant literature. A roadmap for future research, based on open issues and challenges identified along the way, rounds out the book. The book is divided into three main parts, sandwiched between introductory and concluding chapters. The first two chapters introduce readers to the basic concepts, provide an overview of entity-oriented search tasks, and present the various types and sources of data that will be used throughout the book. Part I deals with the core task of entity ranking: given a textual query, possibly enriched with additional elements or structural hints, return a ranked list of entities. This core task is examined in a number of different variants, using both structured and unstructured data collections, and numerous query formulations. In turn, Part II is devoted to the role of entities in bridging unstructured and structured data. Part III explores how entities can enable search engines to understand the concepts, meaning, and intent behind the query that the user enters into the search box, and how they can provide rich and focused responses (as opposed to merely a list of documents)—a process known as semantic search. The final chapter concludes the book by discussing the limitations of current approaches, and suggesting directions for future research. Researchers and graduate students are the primary target audience of this book. A general background in information retrieval is sufficient to follow the material, including an understanding of basic probability and statistics concepts as well as a basic knowledge of machine learning concepts and supervised learning algorithms.
Information modeling and knowledge bases have become essential subjects in the last three decades, not only in academic communities related to information systems and computer science, but also in the areas of business where information technology is applied. This book presents the proceedings of the 28th International Conference on Information Modelling and Knowledge Bases (EJC2018), held in Riga, Latvia from 4–8 June 2018. The aim of the conference was to bring together experts with a common interest in the understanding and solving of problems on information modelling and knowledge bases, as well as those from different areas of computer science and other disciplines who apply the results of research to practice. The 39 accepted papers collected here cover a variety of topics, including: conceptual modeling; knowledge and information modeling and discovery; linguistic modeling; cross-cultural communication and social computing; multimedia data modeling and systems; and environmental modeling and engineering. The book will be of interest to researchers and practitioners alike, and to anyone wanting a better understanding of current advances in information technology.