Graph Representation Learning, Hamilton, William L.
Автор: Haemmerl? Название: Graph-Based Representation and Reasoning ISBN: 3319409840 ISBN-13(EAN): 9783319409849 Издательство: Springer Рейтинг: Цена: 6988.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the proceedings of the 22th International Conference on Conceptual Structures, ICCS 2016, held in Annecy, France, in July 2016. The 14 full papers and 5 short papers presented in this volume were carefully reviewed and selected from 40 submissions.
Описание: Extended Workshop Papers.- Active Semantic Relations in Layered Enterprise Architecture Development.- A Belief Update System Using an Event Model for Location of People in a Smart Home.- A Natural Language Generation Technique for Automated Psychotherapy.- Creative Composition Problem: A Knowledge Graph Logical-based AI Construction and Optimization Solution.- Set Visualisations with Euler and Hasse Diagrams.- Usage Patterns Identification Using Graphs and Machine Learning.- Collaborative Design and Manufacture: Information Structures for Team Formation and Coordination.- Invited Additional Contributions.- Approximate Knowledge Graph Query Answering: From Ranking to Binary Classification.- Galois Connections for Patterns: An Algebra of Labelled Graphs.
Автор: Madalina Croitoru; Sebastian Rudolph; Stefan Woltr Название: Graph Structures for Knowledge Representation and Reasoning ISBN: 3319045334 ISBN-13(EAN): 9783319045337 Издательство: Springer Рейтинг: Цена: 8803.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the thoroughly refereed post-conference proceedings of the Third International Workshop on Graph Structures for Knowledge Representation and Reasoning, GKR 2013, held in Beijing, China, in August 2013, associated with IJCAI 2013, the 23rd International Joint Conference on Artificial Intelligence.
Автор: Nathalie Hernandez; Robert J?schke; Madalina Croit Название: Graph-Based Representation and Reasoning ISBN: 3319083880 ISBN-13(EAN): 9783319083889 Издательство: Springer Рейтинг: Цена: 10201.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the proceedings of the 21st International Conference on Conceptual Structures, ICCS 2014, held in Iasi, Romania, in July 2014.
Автор: Madalina Croitoru; Pierre Marquis; Sebastian Rudol Название: Graph Structures for Knowledge Representation and Reasoning ISBN: 331928701X ISBN-13(EAN): 9783319287010 Издательство: Springer Рейтинг: Цена: 5590.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the thoroughly refereed post-conference proceedings of the 4th International Workshop on Graph Structures for Knowledge Representation and Reasoning, GKR 2015, held in Buenos Aires, Argentina, in July 2015, associated with IJCAI 2015, the 24th International Joint Conference on Artificial Intelligence.
Автор: Croitoru Название: Graph Structures for Knowledge Representation and Reasoning ISBN: 3319781014 ISBN-13(EAN): 9783319781013 Издательство: Springer Рейтинг: Цена: 5870.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the thoroughly refereed post-conference proceedings of the 5th International Workshop on Graph Structures for Knowledge Representation and Reasoning, GKR 2017, held in Melbourne, VIC, Australia, in August 2017, associated with IJCAI 2017, the 26th International Joint Conference on Artificial Intelligence.
Автор: Michel Chein; Marie-Laure Mugnier Название: Graph-based Knowledge Representation ISBN: 1849967695 ISBN-13(EAN): 9781849967693 Издательство: Springer Рейтинг: Цена: 20263.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In addressing the question of how far it is possible to go in knowledge representation and reasoning through graphs, the authors cover basic conceptual graphs, computational aspects, and kernel extensions. The basic mathematical notions are summarized.
Автор: Chapman Название: Graph-Based Representation and Reasoning ISBN: 3319913786 ISBN-13(EAN): 9783319913780 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the proceedings of the 23rd International Conference on Conceptual Structures, ICCS 2018, held in Edinburgh, UK, in June 2018. The 10 full papers, 2 short papers and 2 posters presented were carefully reviewed and selected from 21 submissions. computer- human interaction and human cognition;
Автор: Bergman, Michael K. Название: A knowledge representation practionary ISBN: 3319980912 ISBN-13(EAN): 9783319980911 Издательство: Springer Рейтинг: Цена: 27950.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
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.
Автор: E. Cornell Way Название: Knowledge Representation and Metaphor ISBN: 904814079X ISBN-13(EAN): 9789048140794 Издательство: Springer Рейтинг: Цена: 27245.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 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.
Автор: Shi Chuan, Wang Xiao, Yu Philip S. Название: Heterogeneous Graph Representation Learning and Applications ISBN: 9811661650 ISBN-13(EAN): 9789811661655 Издательство: Springer Рейтинг: Цена: 22359.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 1. Introduction
1.1 Basic concepts and definitions
1.2 Graph representation
1.3 Heterogeneous graph representation and challenges
1.4 Organization of the book
2. The State-of-the-art of Heterogeneous Graph Representation
Описание: Representation learning in heterogeneous graphs (HG) is intended to provide a meaningful vector representation for each node so as to facilitate downstream applications such as link prediction, personalized recommendation, node classification, etc. This task, however, is challenging not only because of the need to incorporate heterogeneous structural (graph) information consisting of multiple types of node and edge, but also the need to consider heterogeneous attributes or types of content (e.g. text or image) associated with each node. Although considerable advances have been made in homogeneous (and heterogeneous) graph embedding, attributed graph embedding and graph neural networks, few are capable of simultaneously and effectively taking into account heterogeneous structural (graph) information as well as the heterogeneous content information of each node. In this book, we provide a comprehensive survey of current developments in HG representation learning. More importantly, we present the state-of-the-art in this field, including theoretical models and real applications that have been showcased at the top conferences and journals, such as TKDE, KDD, WWW, IJCAI and AAAI. The book has two major objectives: (1) to provide researchers with an understanding of the fundamental issues and a good point of departure for working in this rapidly expanding field, and (2) to present the latest research on applying heterogeneous graphs to model real systems and learning structural features of interaction systems. To the best of our knowledge, it is the first book to summarize the latest developments and present cutting-edge research on heterogeneous graph representation learning. To gain the most from it, readers should have a basic grasp of computer science, data mining and machine learning.
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