Knowledge Graph And Semantic Computing Knowledge Computing And Language Understanding
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Knowledge Graph and Semantic Computing: Knowledge Computing and Language Understanding by Xiaoyan Zhu,Bing Qin,Xiaodan Zhu,Ming Liu,Longhua Qian Pdf
This book constitutes the refereed proceedings of the 4th China Conference on Knowledge Graph and Semantic Computing, CCKS 2019, held in Hangzhou, China, in August 2019. The 18 revised full papers presented were carefully reviewed and selected from 140 submissions. The papers cover wide research fields including the knowledge graph, the semantic Web, linked data, NLP, information extraction, knowledge representation and reasoning.
Knowledge Graph and Semantic Computing. Knowledge Computing and Language Understanding by Jun Zhao,Frank van Harmelen,Jie Tang,Xianpei Han,Quan Wang,Xianyong Li Pdf
This book constitutes the refereed proceedings of the Third China Conference on Knowledge Graph and Semantic Computing, CCKS 2018, held in Tianjin, China, in August 2018. The 27 revised full papers and 2 revised short papers presented were carefully reviewed and selected from 101 submissions. The papers cover wide research fields including the knowledge graph, information extraction, knowledge representation and reasoning, linked data.
Knowledge Graph and Semantic Computing by Jun Zhao (College teacher),Frank Van Harmelen,Jie Tang (Computer scientist),Xianpei Han,Quan Wang,Xianyong Li Pdf
This book constitutes the refereed proceedings of the Third China Conference on Knowledge Graph and Semantic Computing, CCKS 2018, held in Tianjin, China, in August 2018. The 27 revised full papers and 2 revised short papers presented were carefully reviewed and selected from 101 submissions. The papers cover wide research fields including the knowledge graph, information extraction, knowledge representation and reasoning, linked data.
Knowledge Graphs by Aidan Hogan,Eva Blomqvist,Michael Cochez,Claudia d’Amato,Gerard de Melo,Claudio Gutierrez,Sabrina Kirrane,Jose Emilio Labra Gayo,Roberto Navigli,Sebastian Neumaier,Axel Polleres,Sabbir Rashid,Anisa Rula,Antoine Zimmermann,Lukas Schmelzeisen,Axel-Cyrille Ngonga Ngomo,Juan Sequeda,Steffen Staab Pdf
This book provides a comprehensive and accessible introduction to knowledge graphs, which have recently garnered notable attention from both industry and academia. Knowledge graphs are founded on the principle of applying a graph-based abstraction to data, and are now broadly deployed in scenarios that require integrating and extracting value from multiple, diverse sources of data at large scale. The book defines knowledge graphs and provides a high-level overview of how they are used. It presents and contrasts popular graph models that are commonly used to represent data as graphs, and the languages by which they can be queried before describing how the resulting data graph can be enhanced with notions of schema, identity, and context. The book discusses how ontologies and rules can be used to encode knowledge as well as how inductive techniques—based on statistics, graph analytics, machine learning, etc.—can be used to encode and extract knowledge. It covers techniques for the creation, enrichment, assessment, and refinement of knowledge graphs and surveys recent open and enterprise knowledge graphs and the industries or applications within which they have been most widely adopted. The book closes by discussing the current limitations and future directions along which knowledge graphs are likely to evolve. This book is aimed at students, researchers, and practitioners who wish to learn more about knowledge graphs and how they facilitate extracting value from diverse data at large scale. To make the book accessible for newcomers, running examples and graphical notation are used throughout. Formal definitions and extensive references are also provided for those who opt to delve more deeply into specific topics.
Knowledge Graph and Semantic Computing: Knowledge Graph Empowers Artificial General Intelligence by Haofen Wang,Xianpei Han,Ming Liu,Gong Cheng,Yongbin Liu,Ningyu Zhang Pdf
This book constitutes the refereed proceedings of the 8th China Conference on Knowledge Graph and Semantic Computing: Knowledge Graph Empowers Artificial General Intelligence, CCKS 2023, held in Shenyang, China, during August 24–27, 2023. The 28 full papers included in this book were carefully reviewed and selected from 106 submissions. They were organized in topical sections as follows: knowledge representation and knowledge graph reasoning; knowledge acquisition and knowledge base construction; knowledge integration and knowledge graph management; natural language understanding and semantic computing; knowledge graph applications; knowledge graph open resources; and evaluations.
Knowledge Graph and Semantic Computing: Knowledge Graph Empowers the Digital Economy by Maosong Sun,Guilin Qi,Kang Liu,Jiadong Ren,Bin Xu,Yansong Feng,Yongbin Liu,Yubo Chen Pdf
This book constitutes the refereed proceedings of the 7th China Conference on Knowledge Graph and Semantic Computing: Knowledge Graph Empowers the Digital Economy, CCKS 2022, in Qinhuangdao, China, August 24–27, 2022. The 15 full papers and 2 short papers included in this book were carefully reviewed and selected from 100 submissions. They were organized in topical sections as follows: knowledge representation and reasoning; knowledge acquisition and knowledge base construction; linked data, knowledge integration, and knowledge graph storage managements; natural language understanding and semantic computing; knowledge graph applications; and knowledge graph open resources.
Knowledge Graph and Semantic Computing. Language, Knowledge, and Intelligence by Juanzi Li,Ming Zhou,Guilin Qi,Ni Lao,Tong Ruan,Jianfeng Du Pdf
This book constitutes the refereed proceedings of the Second China Conference on Knowledge Graph and Semantic Computing, CCKS 2017, held in Chengdu, China, in August 2017. The 11 revised full papers and 6 revised short papers presented were carefully reviewed and selected from 85 submissions. The papers cover wide research fields including the knowledge graph, the Semantic Web, linked data, NLP, knowledge representation, graph databases.
Knowledge Graph and Semantic Computing: Knowledge Graph Empowers New Infrastructure Construction by Bing Qin,Zhi Jin,Haofen Wang,Jeff Pan,Yongbin Liu,Bo An Pdf
This book constitutes the refereed proceedings of the 6th China Conference on Knowledge Graph and Semantic Computing, CCKS 2021, held in Guangzhou, China, in November 2021. The 19 revised full papers and 9 short papers presented were carefully reviewed and selected from 170 submissions. The papers are organized in topical sections on knowledge extraction: knowledge graph representation and reasoning; knowledge acquisition and knowledge graph construction; linked data, knowledge integration, and knowledge graph storage management; natural language understanding and semantic computing; knowledge graph applications: semantic search, question answering, dialogue, decision support, and recommendation; knowledge graph open resources.
Knowledge Graph and Semantic Computing: Knowledge Graph and Cognitive Intelligence by Huajun Chen,Kang Liu,Yizhou Sun,Suge Wang,Lei Hou Pdf
This book constitutes the refereed proceedings of the 5th China Conference on Knowledge Graph and Semantic Computing, CCKS 2020, held in Nanchang, China, in November 2020. The 26 revised full papers presented were carefully reviewed and selected from 173 submissions. The papers are organized in topical sections on knowledge extraction: lexical and entity; knowledge extraction: relation; knowledge extraction: event; knowledge applications: question answering, dialogue, decision support, and recommendation.
Knowledge Graph and Semantic Computing by Maosong Sun,Guilin Qi,Kang Liu,Jiadong Ren,Bin Xu (Mathematician),Yansong Feng,Yongbin Liu,Yubo Chen Pdf
This book constitutes the refereed proceedings of the 7th China Conference on Knowledge Graph and Semantic Computing: Knowledge Graph Empowers the Digital Economy, CCKS 2022, in Qinhuangdao, China, August 24-27, 2022. The 15 full papers and 2 short papers included in this book were carefully reviewed and selected from 100 submissions. They were organized in topical sections as follows: knowledge representation and reasoning; knowledge acquisition and knowledge base construction; linked data, knowledge integration, and knowledge graph storage managements; natural language understanding and semantic computing; knowledge graph applications; and knowledge graph open resources.
Knowledge Graph and Semantic Computing: Semantic, Knowledge, and Linked Big Data by Huajun Chen,Heng Ji,Le Sun,Haixun Wang,Tieyun Qian,Tong Ruan Pdf
This book constitutes the refereed proceedings of the first China Conference on Knowledge Graph and Semantic Computing, CCKS, held in Beijing, China, in September 2016. The 19 revised full papers presented together with 6 shared tasks were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on knowledge representation and learning; knowledge graph construction and information extraction; linked data and knowledge-based systems; shared tasks.
Knowledge Graphs: Semantics, Machine Learning, and Languages by M. Acosta,S. Peroni,S. Vahdati Pdf
Semantic computing is an integral part of modern technology, an essential component of fields as diverse as artificial intelligence, data science, knowledge discovery and management, big data analytics, e-commerce, enterprise search, technical documentation, document management, business intelligence, and enterprise vocabulary management. This book presents the proceedings of SEMANTICS 2023, the 19th International Conference on Semantic Systems, held in Leipzig, Germany, from 20 to 22 September 2023. The conference is a pivotal event for those professionals and researchers actively engaged in harnessing the power of semantic computing, an opportunity to increase their understanding of the subject’s transformative potential while confronting its practical limitations. Attendees include information managers, IT architects, software engineers, and researchers from a broad spectrum of organizations, including research facilities, non-profit entities, public administrations, and the world's largest corporations. For this year’s conference a total of 54 submissions were received in response to a call for papers. These were subjected to a rigorous, double-blind review process, with at least three independent reviews conducted for each submission. The 16 papers included here were ultimately accepted for presentation, with an acceptance rate of 29.6%. Areas covered include novel research challenges in areas such as data science, machine learning, logic programming, content engineering, social computing, and the Semantic Web. The book provides an up-to-date overview, which will be of interest to all those wishing to stay abreast of emerging trends and themes within the vast field of semantic computing.
Further with Knowledge Graphs by M. Alam,P. Groth,V. de Boer Pdf
The field of semantic computing is highly diverse, linking areas such as artificial intelligence, data science, knowledge discovery and management, big data analytics, e-commerce, enterprise search, technical documentation, document management, business intelligence, and enterprise vocabulary management. As such it forms an essential part of the computing technology that underpins all our lives today. This volume presents the proceedings of SEMANTiCS 2021, the 17th International Conference on Semantic Systems. As a result of the continuing Coronavirus restrictions, SEMANTiCS 2021 was held in a hybrid form in Amsterdam, the Netherlands, from 6 to 9 September 2021. The annual SEMANTiCS conference provides an important platform for semantic computing professionals and researchers, and attracts information managers, ITarchitects, software engineers, and researchers from a wide range of organizations, such as research facilities, NPOs, public administrations and the largest companies in the world. The subtitle of the 2021 conference’s was “In the Era of Knowledge Graphs”, and 66 submissions were received, from which the 19 papers included here were selected following a rigorous single-blind reviewing process; an acceptance rate of 29%. Topics covered include data science, machine learning, logic programming, content engineering, social computing, and the Semantic Web, as well as the additional sub-topics of digital humanities and cultural heritage, legal tech, and distributed and decentralized knowledge graphs. Providing an overview of current research and development, the book will be of interest to all those working in the field of semantic systems.
Knowledge Graphs by Mayank Kejriwal,Craig A. Knoblock,Pedro Szekely Pdf
A rigorous and comprehensive textbook covering the major approaches to knowledge graphs, an active and interdisciplinary area within artificial intelligence. The field of knowledge graphs, which allows us to model, process, and derive insights from complex real-world data, has emerged as an active and interdisciplinary area of artificial intelligence over the last decade, drawing on such fields as natural language processing, data mining, and the semantic web. Current projects involve predicting cyberattacks, recommending products, and even gleaning insights from thousands of papers on COVID-19. This textbook offers rigorous and comprehensive coverage of the field. It focuses systematically on the major approaches, both those that have stood the test of time and the latest deep learning methods.
