Embedding Knowledge - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Embedding Knowledge write by Henning Hasemann. This book was released on 2015-03-18. Embedding Knowledge available in PDF, EPUB and Kindle. Die Vision der konsequenten Vernetzung verschiedener eingebetter Geräte miteinander und dem bestehenden Internet, das „Internet der Dinge“, steht zunehmend im wissenschaftlichen und wirtschaftlichen Interesse. Aktuelle Standarisierungsbemühungen erstreben eine Interoperabilität unterschiedlichster Geräteklassen bis hin zur Applikationsschicht. Die Darstellung von kommunizierten Informationen auf dieser Schicht allerdings ist üblicherweise in Formaten und Vokabeln kodiert, die spezifisch für eine bestimmte Wissensdomäne sind. Parallel beobachten wir die Entstehung des Semantischen Webs, einer Reihe von Standards, die Wissen im World Wide Web auf universelle und verteilte Weise darstellen. Diese Arbeit untersucht die Verbindung des Internets der Dinge mit dem Semantischen Web, mit dem Ziel einer universellen Wissensdarstellung, die „Dinge“ miteinander und dem bestehenden Internet verbindet. Insbesondere diskutieren wir, inwieweit es möglich ist, semantisches Wissen im Sinne des Sematischen Webs auf verschiedenen ressourcenbeschränkten Systemen zu speichern, zu verarbeiten und abzufragen.
Embedding Knowledge Graphs with RDF2vec
Embedding Knowledge Graphs with RDF2vec - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Embedding Knowledge Graphs with RDF2vec write by Heiko Paulheim. This book was released on 2023-06-03. Embedding Knowledge Graphs with RDF2vec available in PDF, EPUB and Kindle. This book explains the ideas behind one of the most well-known methods for knowledge graph embedding of transformations to compute vector representations from a graph, known as RDF2vec. The authors describe its usage in practice, from reusing pre-trained knowledge graph embeddings to training tailored vectors for a knowledge graph at hand. They also demonstrate different extensions of RDF2vec and how they affect not only the downstream performance, but also the expressivity of the resulting vector representation, and analyze the resulting vector spaces and the semantic properties they encode.
Graph Representation Learning
Graph Representation Learning - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Graph Representation Learning write by William L. William L. Hamilton. This book was released on 2022-06-01. Graph Representation Learning available in PDF, EPUB and Kindle. 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.
Knowledge Graphs and Big Data Processing
Knowledge Graphs and Big Data Processing - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Knowledge Graphs and Big Data Processing write by Valentina Janev. This book was released on 2020-07-15. Knowledge Graphs and Big Data Processing available in PDF, EPUB and Kindle. This open access book is part of the LAMBDA Project (Learning, Applying, Multiplying Big Data Analytics), funded by the European Union, GA No. 809965. Data Analytics involves applying algorithmic processes to derive insights. Nowadays it is used in many industries to allow organizations and companies to make better decisions as well as to verify or disprove existing theories or models. The term data analytics is often used interchangeably with intelligence, statistics, reasoning, data mining, knowledge discovery, and others. The goal of this book is to introduce some of the definitions, methods, tools, frameworks, and solutions for big data processing, starting from the process of information extraction and knowledge representation, via knowledge processing and analytics to visualization, sense-making, and practical applications. Each chapter in this book addresses some pertinent aspect of the data processing chain, with a specific focus on understanding Enterprise Knowledge Graphs, Semantic Big Data Architectures, and Smart Data Analytics solutions. This book is addressed to graduate students from technical disciplines, to professional audiences following continuous education short courses, and to researchers from diverse areas following self-study courses. Basic skills in computer science, mathematics, and statistics are required.
Blackwell Handbook of Social Psychology
Blackwell Handbook of Social Psychology - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Blackwell Handbook of Social Psychology write by Michael A. Hogg. This book was released on 2008-04-15. Blackwell Handbook of Social Psychology available in PDF, EPUB and Kindle. This handbook provides an authoritative, up-to-date overview of the social psychology of group processes. The topics covered include group decisions, juries, group remembering, roles, status, leadership, social identity and group membership, socialization, group performance, negotiation and bargaining, emotion and mood, computer-mediated communication, organizations and mental health. Provides an authoritative, up-to-date overview of the social psychology of group processes. Written by leading researchers from around the world to provide a classic and current overview of research as well as providing a description of future trends within the area. Includes coverage of group decisions, juries, group remembering, roles, status, leadership, social identity and group membership, socialization, group performance, negotiation and bargaining, emotion and mood, computer-mediated communication, organizations and mental health. Essential reading for any serious scholar of group behavior. Now available in full text online via xreferplus, the award-winning reference library on the web from xrefer. For more information, visit www.xreferplus.com
