Download or read book Understanding Meaning and Knowledge Representation written by Eva Mestre Mestre and published by Cambridge Scholars Publishing. This book was released on 2016-01-14 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt: Today, there is a need to develop natural language processing (NLP) systems from deeper linguistic approaches. Although there are many NLP applications which can work without taking into account any linguistic theory, this type of system can only be described as “deceptively intelligent”. On the other hand, however, those computer programs requiring some language comprehension capability should be grounded in a robust linguistic model if they are to display the expected behaviour. The purpose of this book is to examine and discuss recent work in meaning and knowledge representation within theoretical linguistics and cognitive linguistics, particularly research which can be reused to model NLP applications.
Download or read book A Knowledge Representation Practionary written by Michael K. Bergman and published by Springer. This book was released on 2018-12-12 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt: This major work on knowledge representation is based on the writings of Charles S. Peirce, a logician, scientist, and philosopher of the first rank at the beginning of the 20th century. This book follows Peirce's practical guidelines and universal categories in a structured approach to knowledge representation that captures differences in events, entities, relations, attributes, types, and concepts. Besides the ability to capture meaning and context, the Peircean approach is also well-suited to machine learning and knowledge-based artificial intelligence. Peirce is a founder of pragmatism, the uniquely American philosophy. Knowledge representation is shorthand for how to represent human symbolic information and knowledge to computers to solve complex questions. KR applications range from semantic technologies and knowledge management and machine learning to information integration, data interoperability, and natural language understanding. Knowledge representation is an essential foundation for knowledge-based AI. This book is structured into five parts. The first and last parts are bookends that first set the context and background and conclude with practical applications. The three main parts that are the meat of the approach first address the terminologies and grammar of knowledge representation, then building blocks for KR systems, and then design, build, test, and best practices in putting a system together. Throughout, the book refers to and leverages the open source KBpedia knowledge graph and its public knowledge bases, including Wikipedia and Wikidata. KBpedia is a ready baseline for users to bridge from and expand for their own domain needs and applications. It is built from the ground up to reflect Peircean principles. This book is one of timeless, practical guidelines for how to think about KR and to design knowledge management (KM) systems. The book is grounded bedrock for enterprise information and knowledge managers who are contemplating a new knowledge initiative. This book is an essential addition to theory and practice for KR and semantic technology and AI researchers and practitioners, who will benefit from Peirce's profound understanding of meaning and context.
Download or read book Knowledge Representation and Metaphor written by E. Cornell Way and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: This series will include monographs and collections of studies devoted to the investigation and exploration of knowledge, information, and data processing systems of all kinds, no matter whether human, (other) animal, or machine. Its scope is intended to span the full range of interests from classical problems in the philosophy of mind and philosophical psychol ogy through issues in cognitive psychology and sociobiology (concerning the mental capabilities of other species) to ideas related to artificial intelligence and computer science. While primary emphasis will be placed upon theoretical, conceptual, and epistemological aspects of these problems and domains, empirical, experimental, and methodological studies will also appear from time to time. The problems posed by metaphor and analogy are among the most challenging that confront the field of knowledge representation. In this study, Eileen Way has drawn upon the combined resources of philosophy, psychology, and computer science in developing a systematic and illuminating theoretical framework for understanding metaphors and analogies. While her work provides solutions to difficult problems of knowledge representation, it goes much further by investigating some of the most important philosophical assumptions that prevail within artificial intelligence today. By exposing the limitations inherent in the assumption that languages are both literal and truth-functional, she has advanced our grasp of the nature of language itself. J.R.F.
Download or read book Knowledge Representation and the Semantics of Natural Language written by Hermann Helbig and published by Springer Science & Business Media. This book was released on 2005-12-19 with total page 652 pages. Available in PDF, EPUB and Kindle. Book excerpt: Natural Language is not only the most important means of communication between human beings, it is also used over historical periods for the pres- vation of cultural achievements and their transmission from one generation to the other. During the last few decades, the ?ood of digitalized information has been growing tremendously. This tendency will continue with the globali- tion of information societies and with the growing importance of national and international computer networks. This is one reason why the theoretical und- standing and the automated treatment of communication processes based on natural language have such a decisive social and economic impact. In this c- text, the semantic representation of knowledge originally formulated in natural language plays a central part, because it connects all components of natural language processing systems, be they the automatic understanding of natural language (analysis), the rational reasoning over knowledge bases, or the g- eration of natural language expressions from formal representations. This book presents a method for the semantic representation of natural l- guage expressions (texts, sentences, phrases, etc. ) which can be used as a u- versal knowledge representation paradigm in the human sciences, like lingu- tics, cognitive psychology, or philosophy of language, as well as in com- tational linguistics and in arti?cial intelligence. It is also an attempt to close the gap between these disciplines, which to a large extent are still working separately.
Download or read book Representation Learning for Natural Language Processing written by Zhiyuan Liu and published by Springer Nature. This book was released on 2020-07-03 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including words, phrases, sentences and documents. Part II then introduces the representation techniques for those objects that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, networks, and cross-modal entries. Lastly, Part III provides open resource tools for representation learning techniques, and discusses the remaining challenges and future research directions. The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, social network analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing.
Download or read book Encyclopedia of Systems Biology written by Werner Dubitzky and published by Springer. This book was released on 2013-06-05 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Systems biology refers to the quantitative analysis of the dynamic interactions among several components of a biological system and aims to understand the behavior of the system as a whole. Systems biology involves the development and application of systems theory concepts for the study of complex biological systems through iteration over mathematical modeling, computational simulation and biological experimentation. Systems biology could be viewed as a tool to increase our understanding of biological systems, to develop more directed experiments, and to allow accurate predictions. The Encyclopedia of Systems Biology is conceived as a comprehensive reference work covering all aspects of systems biology, in particular the investigation of living matter involving a tight coupling of biological experimentation, mathematical modeling and computational analysis and simulation. The main goal of the Encyclopedia is to provide a complete reference of established knowledge in systems biology – a ‘one-stop shop’ for someone seeking information on key concepts of systems biology. As a result, the Encyclopedia comprises a broad range of topics relevant in the context of systems biology. The audience targeted by the Encyclopedia includes researchers, developers, teachers, students and practitioners who are interested or working in the field of systems biology. Keeping in mind the varying needs of the potential readership, we have structured and presented the content in a way that is accessible to readers from wide range of backgrounds. In contrast to encyclopedic online resources, which often rely on the general public to author their content, a key consideration in the development of the Encyclopedia of Systems Biology was to have subject matter experts define the concepts and subjects of systems biology.
Download or read book Natural Language Processing and Knowledge Representation written by Łucja M. Iwańska and published by AAAI Press. This book was released on 2000-06-19 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Traditionally, knowledge representation and reasoning systems have incorporated natural language as interfaces to expert systems or knowledge bases that performed tasks separate from natural language processing. As this book shows, however, the computational nature of representation and inference in natural language makes it the ideal model for all tasks in an intelligent computer system. Natural language processing combines the qualitative characteristics of human knowledge processing with a computer's quantitative advantages, allowing for in-depth, systematic processing of vast amounts of information.
Download or read book Approaches to Knowledge Representation written by Gordon A. Ringland and published by John Wiley & Sons. This book was released on 1988 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Knowledge Representation and Reasoning written by Ronald Brachman and published by Morgan Kaufmann. This book was released on 2004-05-19 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: Knowledge representation is at the very core of a radical idea for understanding intelligence. This book talks about the central concepts of knowledge representation developed over the years. It is suitable for researchers and practitioners in database management, information retrieval, object-oriented systems and artificial intelligence.
Download or read book Understanding Representation written by Jen Webb and published by SAGE. This book was released on 2008-12-01 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This is an extraordinarily lucid book. I am not sure that there is anyone who can do this sort of thing better than Jen Webb. It is a gift to students; extremely accessible yet complex and sophisticated in its treatment of theories and concepts of representation." - Jim McGuigan, Loughborough University Understanding Representation offers a contemporary, coherent and genuinely interdisciplinary introduction to the concept of representation. Drawing together the full range of ideas, practices, techniques and disciplines associated with the subject, this book locates them in a historical context, presents them in a readable fashion, and shows their relevance to everyday life in an engaging and accessible manner. Readers will be shown how to develop a sophisticated attitude to meaning, and understand the relationship to truth and identity that is brought into focus by communicative practices. With chapters on linguistic and political representation, art and media, and philosophical and cognitive approaches, this book: Guides readers through complex theoretical terrain with a highly readable and refreshing writing style. Explains the techniques and perspectives offered by semiotics, discourse analysis, poetics, politics, narratology, visual culture, cognitive theory, performance theory and theories of embodied subjectivity. Covers the new ideas and practices that have emerged since the work of Barthes, Eco and Foucault - especially communication and meaning-making in the digital environment, and the new paradigms of understanding associated with cognitive theories of identity and language. Teaches readers how to interpret and interrogate the world of signs in which they live. Understanding Representation provides students across the social sciences and humanities with an invaluable introduction to what is meant by ′representation′.
Download or read book Knowledge Representation written by Arthur B. Markman and published by Psychology Press. This book was released on 2013-06-17 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: Knowledge representation is fundamental to the study of mind. All theories of psychological processing are rooted in assumptions about how information is stored. These assumptions, in turn, influence the explanatory power of theories. This book fills a gap in the existing literature by providing an overview of types of knowledge representation techniques and their use in cognitive models. Organized around types of representations, this book begins with a discussion of the foundations of knowledge representation, then presents discussions of different ways that knowledge representation has been used. Both symbolic and connectionist approaches to representation are discussed and a set of recommendations about the way representations should be used is presented. This work can be used as the basis for a course on knowledge representation or can be read independently. It will be useful to students of psychology as well as people in related disciplines--computer science, philosophy, anthropology, and linguistics--who want an introduction to techniques for knowledge representation.
Download or read book The Knowledge Frontier written by Nick Cercone and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 545 pages. Available in PDF, EPUB and Kindle. Book excerpt: Knowledge representation is perhaps the most central problem confronting artificial intelligence. Expert systems need knowledge of their domain of expertise in order to function properly. Computer vlslOn systems need to know characteristics of what they are "seeing" in order to be able to fully interpret scenes. Natural language systems are invaluably aided by knowledge of the subject of the natural language discourse and knowledge of the participants in the discourse. Knowledge can guide learning systems towards better understanding and can aid problem solving systems in creating plans to solve various problems. Applications such as intelligent tutoring. computer-aided VLSI design. game playing. automatic programming. medical reasoning. diagnosis in various domains. and speech recogOltlOn. to name a few. are all currently experimenting with knowledge-based approaches. The problem of knowledge representation breaks down into several subsidiary problems including what knowledge to represent in a particular application. how to extract or create that knowledge. how to represent the knowledge efficiently and effectively. how to implement the knowledge representation scheme chosen. how to modify the knowledge in the face of a changing world. how to reason with the knowledge. and how tc use the knowledge appropriately in the creation of the application solution. This volume contains an elaboration of many of these basic issues from a variety of perspectives.
Download or read book Knowledge Representation written by Han Reichgelt and published by Intellect (UK). This book was released on 1991 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most researchers to date in artificial intelligence has been based on the knowledge representation hypothesis, that is, the assumption that in any artificial intelligence (AI) programme there is a separate module which represents the information that the programme has about the world. As a result, a number of so-called knowlege representation formalisms have been developed for representing this kind of information in a computer.
Download or read book Semantic Knowledge Representation for Information Retrieval written by Winfried Gödert and published by Walter de Gruyter GmbH & Co KG. This book was released on 2014-08-19 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the basics of semantic web technologies and indexing languages, and describes their contribution to improve methods of formal knowledge representation and reasoning. The methodologies included combine the specifics of indexing languages, Web representation languages and intersystem relations, and explain their contribution to search functionalities in information retrieval scenarios. An example oriented discussion, considering aspects of conceptual and semantic interoperability in processes of subject querying and knowledge exploration is provided. The book is relevant to information scientists, knowledge workers and indexers. It provides a suitable combination of theoretical foundations and practical applications.
Download or read book Encyclopedia of the Sciences of Learning written by Norbert M. Seel and published by Springer Science & Business Media. This book was released on 2011-10-05 with total page 3643 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past century, educational psychologists and researchers have posited many theories to explain how individuals learn, i.e. how they acquire, organize and deploy knowledge and skills. The 20th century can be considered the century of psychology on learning and related fields of interest (such as motivation, cognition, metacognition etc.) and it is fascinating to see the various mainstreams of learning, remembered and forgotten over the 20th century and note that basic assumptions of early theories survived several paradigm shifts of psychology and epistemology. Beyond folk psychology and its naïve theories of learning, psychological learning theories can be grouped into some basic categories, such as behaviorist learning theories, connectionist learning theories, cognitive learning theories, constructivist learning theories, and social learning theories. Learning theories are not limited to psychology and related fields of interest but rather we can find the topic of learning in various disciplines, such as philosophy and epistemology, education, information science, biology, and – as a result of the emergence of computer technologies – especially also in the field of computer sciences and artificial intelligence. As a consequence, machine learning struck a chord in the 1980s and became an important field of the learning sciences in general. As the learning sciences became more specialized and complex, the various fields of interest were widely spread and separated from each other; as a consequence, even presently, there is no comprehensive overview of the sciences of learning or the central theoretical concepts and vocabulary on which researchers rely. The Encyclopedia of the Sciences of Learning provides an up-to-date, broad and authoritative coverage of the specific terms mostly used in the sciences of learning and its related fields, including relevant areas of instruction, pedagogy, cognitive sciences, and especially machine learning and knowledge engineering. This modern compendium will be an indispensable source of information for scientists, educators, engineers, and technical staff active in all fields of learning. More specifically, the Encyclopedia provides fast access to the most relevant theoretical terms provides up-to-date, broad and authoritative coverage of the most important theories within the various fields of the learning sciences and adjacent sciences and communication technologies; supplies clear and precise explanations of the theoretical terms, cross-references to related entries and up-to-date references to important research and publications. The Encyclopedia also contains biographical entries of individuals who have substantially contributed to the sciences of learning; the entries are written by a distinguished panel of researchers in the various fields of the learning sciences.
Download or read book Readings in Knowledge Representation written by Ronald J. Brachman and published by Morgan Kaufmann Publishers. This book was released on 1985 with total page 600 pages. Available in PDF, EPUB and Kindle. Book excerpt: In Artificial Intelligence, it is often said that the representation of knowledge is the key to the design of robust intelligent systems. In one form or another the principles of Knowledge Representation are fundamental to work in natural language processing, computer vision, knowledge-based expert systems, and other areas. The papers reprinted in this volume have been collected to allow the reader with a general technical background in AI to explore the subtleties of this key subarea. These seminal articles, spanning a quarter-century of research, cover the most important ideas and developments in the representation field. The editors introduce each paper, discuss its relevance and context, and provide an extensive bibliography of other work. "Readings in Knowledge Representation" is intended to serve as a complete sourcebook for the study of this crucial subject.
Download or read book How People Learn II written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2018-09-27 with total page 347 pages. Available in PDF, EPUB and Kindle. Book excerpt: There are many reasons to be curious about the way people learn, and the past several decades have seen an explosion of research that has important implications for individual learning, schooling, workforce training, and policy. In 2000, How People Learn: Brain, Mind, Experience, and School: Expanded Edition was published and its influence has been wide and deep. The report summarized insights on the nature of learning in school-aged children; described principles for the design of effective learning environments; and provided examples of how that could be implemented in the classroom. Since then, researchers have continued to investigate the nature of learning and have generated new findings related to the neurological processes involved in learning, individual and cultural variability related to learning, and educational technologies. In addition to expanding scientific understanding of the mechanisms of learning and how the brain adapts throughout the lifespan, there have been important discoveries about influences on learning, particularly sociocultural factors and the structure of learning environments. How People Learn II: Learners, Contexts, and Cultures provides a much-needed update incorporating insights gained from this research over the past decade. The book expands on the foundation laid out in the 2000 report and takes an in-depth look at the constellation of influences that affect individual learning. How People Learn II will become an indispensable resource to understand learning throughout the lifespan for educators of students and adults.
