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Networks For Knowledge
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Book Synopsis Networks of Knowledge by : Janice Gross Stein
Download or read book Networks of Knowledge written by Janice Gross Stein and published by University of Toronto Press. This book was released on 2001-01-01 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: Examines the 'knowledge network' whose primary mandate is to create and disseminate knowledge based on multidisciplinary research that is informed by problem-solving as well as theoretical agendas.
Book Synopsis Networks in the Knowledge Economy by : Rob Cross
Download or read book Networks in the Knowledge Economy written by Rob Cross and published by Oxford University Press. This book was released on 2003-07-17 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: In today's de-layered, knowledge-intensive organizations, most work of importance is heavily reliant on informal networks of employees within organizations. However, most organizations do not know how to effectively analyze this informal structure in ways that can have a positive impact on organizational performance. Networks in the Knowledge Economy is a collection of readings on the application of social network analysis to managerial concerns. Social network analysis (SNA), a set of analytic tools that can be used to map networks of relationships, allows one to conduct very powerful assessments of information sharing within a network with relatively little effort. This approach makes the invisible web of relationships between people visible, helping managers make informed decisions for improving both their own and their group's performance. Networks in the Knowledge Economy is specifically concerned with networks inside of organizations and addresses three critical areas in the study of social networks: Social Networks as Important Individual and Organizational Assets, Social Network Implications for Knowledge Creation and Sharing, and Managerial Implications of Social Networks in Organizations. Professionals and students alike will find this book especially valuable, as it provides readings on the application of social network analysis that reflect managerial concerns.
Book Synopsis Knowledge Networks by : Denise Bedford
Download or read book Knowledge Networks written by Denise Bedford and published by Emerald Group Publishing. This book was released on 2021-10-26 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Knowledge Networks describes the role of networks in the knowledge economy, explains network structures and behaviors, walks the reader through the design and setup of knowledge network analyses, and offers a step by step methodology for conducting a knowledge network analysis.
Book Synopsis Ancient Knowledge Networks by : Eleanor Robson
Download or read book Ancient Knowledge Networks written by Eleanor Robson and published by UCL Press. This book was released on 2019-11-14 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ancient Knowledge Networks is a book about how knowledge travels, in minds and bodies as well as in writings. It explores the forms knowledge takes and the meanings it accrues, and how these meanings are shaped by the peoples who use it.Addressing the relationships between political power, family ties, religious commitments and literate scholarship in the ancient Middle East of the first millennium BC, Eleanor Robson focuses on two regions where cuneiform script was the predominant writing medium: Assyria in the north of modern-day Syria and Iraq, and Babylonia to the south of modern-day Baghdad. She investigates how networks of knowledge enabled cuneiform intellectual culture to endure and adapt over the course of five world empires until its eventual demise in the mid-first century BC. In doing so, she also studies Assyriological and historical method, both now and over the past two centuries, asking how the field has shaped and been shaped by the academic concerns and fashions of the day. Above all, Ancient Knowledge Networks is an experiment in writing about ‘Mesopotamian science’, as it has often been known, using geographical and social approaches to bring new insights into the intellectual history of the world’s first empires.
Book Synopsis The Origins of Higher Learning by : Roy Lowe
Download or read book The Origins of Higher Learning written by Roy Lowe and published by Taylor & Francis. This book was released on 2016-10-04 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt: Higher education has become a worldwide phenomenon where students now travel internationally to pursue courses and careers, not simply as a global enterprise, but as a network of worldwide interconnections. The Origins of Higher Learning: Knowledge networks and the early development of universities is an account of the first globalisation that has led us to this point, telling of how humankind first developed centres of higher learning across the vast landmass from the Atlantic to the China Sea. This book opens a much-needed debate on the origins of higher learning, exploring how, why and where humankind first began to take a sustained interest in questions that went beyond daily survival. Showing how these concerns became institutionalised and how knowledge came to be transferred from place to place, this book explores important aspects of the forerunners of globalisation. It is a narrative which covers much of Asia, North Africa and Europe, many parts of which were little known beyond their own boundaries. Spanning from the earliest civilisations to the end of the European Middle Ages, around 700 years ago, here the authors set out crucial findings for future research and investigation. This book shows how interconnections across continents are nothing new and that in reality, humankind has been interdependent for a much longer period than is widely recognised. It is a book which challenges existing accounts of the origins of higher learning in Europe and will be of interest to all those who wish to know more about the world of academia.
Book Synopsis Knowledge Networks by : Paul M. Hildreth
Download or read book Knowledge Networks written by Paul M. Hildreth and published by IGI Global. This book was released on 2004-01-01 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: Knowledge Networks: Innovation Through Communities of Practice explores the inner workings of an organizational, internationally distributed Community of Practice. The book highlights the weaknesses of the 'traditional' KM approach of 'capture-codify-store' and asserts that communities of practice are recognized as groups where soft (knowledge that cannot be captured) knowledge is created and sustained. Readers will gain insight into a period the life of a distributed international community of practice by following the members as they work, meet, collaborate, interact and socialize.
Book Synopsis Empires of Knowledge by : Paula Findlen
Download or read book Empires of Knowledge written by Paula Findlen and published by Routledge. This book was released on 2018-10-26 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: Empires of Knowledge charts the emergence of different kinds of scientific networks – local and long-distance, informal and institutional, religious and secular – as one of the important phenomena of the early modern world. It seeks to answer questions about what role these networks played in making knowledge, how information traveled, how it was transformed by travel, and who the brokers of this world were. Bringing together an international group of historians of science and medicine, this book looks at the changing relationship between knowledge and community in the early modern period through case studies connecting Europe, Asia, the Ottoman Empire, and the Americas. It explores a landscape of understanding (and misunderstanding) nature through examinations of well-known intelligencers such as overseas missions, trading companies, and empires while incorporating more recent scholarship on the many less prominent go-betweens, such as translators and local experts, which made these networks of knowledge vibrant and truly global institutions. Empires of Knowledge is the perfect introduction to the global history of early modern science and medicine.
Book Synopsis Knowledge Networks and Tourism by : Michelle McLeod
Download or read book Knowledge Networks and Tourism written by Michelle McLeod and published by Routledge. This book was released on 2014-11-20 with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt: The receipt of knowledge is a key ingredient by which the tourism sector can adjust and adapt to its dynamic environment. However although its importance has long been recognised the fragmentation within the sector, largely as a result of it being comprised of small and medium sized businesses, makes understanding knowledge management challenging. This book applies knowledge management and social network theories to the business of tourism to shed light on successful operations of tourism knowledge networks. It contributes specifically to understanding a network perspective of the tourism sector, the information needs of tourism businesses, social network dynamics of tourism business operation, knowledge flows within the tourism sector and the transformation of the tourism sector through knowledge networks. Social Network Analysis is applied to fully explore the growth and maintenance of tourism knowledge networks and the relationships between tourism sector stakeholders in relation to their knowledge requirements. Knowledge Networks and Tourism will be valuable reading for all those interested in successful operations of tourism knowledge networks.
Download or read book Deep Learning written by Ian Goodfellow and published by MIT Press. This book was released on 2016-11-10 with total page 801 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.
Book Synopsis Networks, Knowledge Brokers, and the Public Policymaking Process by : Matthew S. Weber
Download or read book Networks, Knowledge Brokers, and the Public Policymaking Process written by Matthew S. Weber and published by Springer Nature. This book was released on 2021-11-03 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: Social network analysis provides a meaningful lens for advancing a more nuanced understanding of the communication networks and practices that bring together policy advocates and practitioners in their day-to-day efforts to broker evidence into policymaking processes. This book advances knowledge brokerage scholarship and methodology as applied to policymaking contexts, focusing on the ways in which knowledge and research are utilized, and go on to influence policy and practice decisions across domains, including communication, health and education. There is a growing recognition that knowledge brokers – key intermediaries – have an important role in calling attention to research evidence that can facilitate the successful implementation of evidence-informed policies and practices. The chapters in this volume focus explicitly on the history of knowledge brokerage research in these contexts and the frameworks and methodologies that bridge these disparate domains. The contributors to this volume offer useful typologies of knowledge brokerage and explicate the range of causal mechanisms that enable knowledge brokers’ influence on policymaking. The work included in this volume responds to this emerging interest by comparing, assessing, and delineating social network approaches to knowledge brokerage across domains. The book is a useful resource for students and scholars of social network analysis and policymaking, including in health, communication, public policy and education policy.
Book Synopsis Graph Representation Learning by : William L. William L. Hamilton
Download or read book Graph Representation Learning written by William L. William L. Hamilton and published by Springer Nature. This book was released on 2022-06-01 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational inductive biases into deep learning architectures is crucial for creating systems that can learn, reason, and generalize from this kind of data. Recent years have seen a surge in research on graph representation learning, including techniques for deep graph embeddings, generalizations of convolutional neural networks to graph-structured data, and neural message-passing approaches inspired by belief propagation. These advances in graph representation learning have led to new state-of-the-art results in numerous domains, including chemical synthesis, 3D vision, recommender systems, question answering, and social network analysis. This book provides a synthesis and overview of graph representation learning. It begins with a discussion of the goals of graph representation learning as well as key methodological foundations in graph theory and network analysis. Following this, the book introduces and reviews methods for learning node embeddings, including random-walk-based methods and applications to knowledge graphs. It then provides a technical synthesis and introduction to the highly successful graph neural network (GNN) formalism, which has become a dominant and fast-growing paradigm for deep learning with graph data. The book concludes with a synthesis of recent advancements in deep generative models for graphs—a nascent but quickly growing subset of graph representation learning.
Book Synopsis Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering by : Nikola K. Kasabov
Download or read book Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering written by Nikola K. Kasabov and published by Marcel Alencar. This book was released on 1996 with total page 581 pages. Available in PDF, EPUB and Kindle. Book excerpt: Combines the study of neural networks and fuzzy systems with symbolic artificial intelligence (AI) methods to build comprehensive AI systems. Describes major AI problems (pattern recognition, speech recognition, prediction, decision-making, game-playing) and provides illustrative examples. Includes applications in engineering, business and finance.
Book Synopsis Building the Knowledge Management Network by : Cliff Figallo
Download or read book Building the Knowledge Management Network written by Cliff Figallo and published by John Wiley & Sons. This book was released on 2002-10-15 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: A complete set of best practices, tools, and techniques for turning conversations into a rich source of business information Many organizations are now recognizing that the untapped knowledge of their members can be used to benefit every aspect of their business, from making smarter and faster decisions to improving products and efficiency. This book offers a clear-cut road map for building a successful knowledge management system to capture and fully exploit the knowledge exchanged in conversations. Written by two of the foremost experts in online communities, this book covers a set of best practices, tools, and techniques for using conversation and online interaction to provide affordable and effective knowledge-based benefits and solutions. With a unique and invaluable perspective, the authors offer guidance for collecting, capturing, and cataloging knowledge so that it can be used to improve efficiency and reduce costs in areas ranging from internal procedures through customer relations and product development. This book provides step-by-step solutions for developing an effective knowledge network, including how to: * Formulate strategies and create action plans * Select the right tools for peer-to-peer networks, interactive communities, and events * Work with legacy systems * Train staff and stimulate participation * Improve productivity and measurement criteria The companion Web site contains templates, checklists, a discussion board, and links to software.
Book Synopsis Principles of Semantic Networks by : John F. Sowa
Download or read book Principles of Semantic Networks written by John F. Sowa and published by Morgan Kaufmann. This book was released on 2014-07-10 with total page 595 pages. Available in PDF, EPUB and Kindle. Book excerpt: Principles of Semantic Networks: Explorations in the Representation of Knowledge provides information pertinent to the theory and applications of semantic networks. This book deals with issues in knowledge representation, which discusses theoretical topics independent of particular implementations. Organized into three parts encompassing 19 chapters, this book begins with an overview of semantic network structure for representing knowledge as a pattern of interconnected nodes and arcs. This text then analyzes the concepts of subsumption and taxonomy and synthesizes a framework that integrates many previous approaches and goes beyond them to provide an account of abstract and partially defines concepts. Other chapters consider formal analyses, which treat the methods of reasoning with semantic networks and their computational complexity. This book discusses as well encoding linguistic knowledge. The final chapter deals with a formal approach to knowledge representation that builds on ideas originating outside the artificial intelligence literature in research on foundations for programming languages. This book is a valuable resource for mathematicians.
Book Synopsis Collaboration and the Semantic Web: Social Networks, Knowledge Networks, and Knowledge Resources by : Brüggemann, Stefan
Download or read book Collaboration and the Semantic Web: Social Networks, Knowledge Networks, and Knowledge Resources written by Brüggemann, Stefan and published by IGI Global. This book was released on 2012-04-30 with total page 387 pages. Available in PDF, EPUB and Kindle. Book excerpt: Collaborative working has been increasingly viewed as a good practice for organizations to achieve efficiency. Organizations that work well in collaboration may have access to new sources of funding, deliver new, improved, and more integrated services, make savings on shared costs, and exchange knowledge, information and expertise. Collaboration and the Semantic Web: Social Networks, Knowledge Networks and Knowledge Resources showcases cutting-edge research on the intersections of Semantic Web, collaborative work, and social media research, exploring how the resources of so-called social networking applications, which bring people together to interact and encourage sharing of personal information and ideas, can be tapped by Semantic Web techniques, making shared Web contents readable and processable for machine and intelligent applications, as well as humans. Semantic technologies have shown their potential for integrating valuable knowledge, and they are being applied to the composition of digital learning and working platforms. Integrated semantic applications, linked data, social networks, and networked digital solutions can now be used in collaborative environments and present participants with the context-aware information that they need.
Book Synopsis Intelligent Internet Knowledge Networks by : Syed V. Ahamed
Download or read book Intelligent Internet Knowledge Networks written by Syed V. Ahamed and published by John Wiley & Sons. This book was released on 2006-12-13 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introducing the basic concepts in total program control of the intelligent agents and machines, Intelligent Internet Knowledge Networks explores the design and architecture of information systems that include and emphasize the interactive role of modern computer/communication systems and human beings. Here, you’ll discover specific network configurations that sense environments, presented through case studies of IT platforms, electrical governments, medical networks, and educational networks.
Book Synopsis Neural Networks and Deep Learning by : Charu C. Aggarwal
Download or read book Neural Networks and Deep Learning written by Charu C. Aggarwal and published by Springer. This book was released on 2018-08-25 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. The theory and algorithms of neural networks are particularly important for understanding important concepts, so that one can understand the important design concepts of neural architectures in different applications. Why do neural networks work? When do they work better than off-the-shelf machine-learning models? When is depth useful? Why is training neural networks so hard? What are the pitfalls? The book is also rich in discussing different applications in order to give the practitioner a flavor of how neural architectures are designed for different types of problems. Applications associated with many different areas like recommender systems, machine translation, image captioning, image classification, reinforcement-learning based gaming, and text analytics are covered. The chapters of this book span three categories: The basics of neural networks: Many traditional machine learning models can be understood as special cases of neural networks. An emphasis is placed in the first two chapters on understanding the relationship between traditional machine learning and neural networks. Support vector machines, linear/logistic regression, singular value decomposition, matrix factorization, and recommender systems are shown to be special cases of neural networks. These methods are studied together with recent feature engineering methods like word2vec. Fundamentals of neural networks: A detailed discussion of training and regularization is provided in Chapters 3 and 4. Chapters 5 and 6 present radial-basis function (RBF) networks and restricted Boltzmann machines. Advanced topics in neural networks: Chapters 7 and 8 discuss recurrent neural networks and convolutional neural networks. Several advanced topics like deep reinforcement learning, neural Turing machines, Kohonen self-organizing maps, and generative adversarial networks are introduced in Chapters 9 and 10. The book is written for graduate students, researchers, and practitioners. Numerous exercises are available along with a solution manual to aid in classroom teaching. Where possible, an application-centric view is highlighted in order to provide an understanding of the practical uses of each class of techniques.
