{"product_id":"knowledge-graph-and-semantic-computing-knowledge-graph-empowers-new-infrastructure-construction-6th-china-conference-ccks-2021-guangzhou-china-november-47-2021-proceedings-9789811664700","title":"Knowledge Graph and Semantic Computing: Knowledge Graph Empowers New Infrastructure Construction: 6th China Conference, CCKS 2021, Guangzhou, China, November 4-7, 2021, Proceedings","description":"\u003cp\u003e\u003c\/p\u003e\u003cblockquote\u003eThe 6th China Conference on Knowledge Graph and Semantic Computing,CCKS 2021, held in Guangzhou, China, in November 2021, featured 19 revised full papers and 9 short papers, covering topics such as knowledge extraction, representation, reasoning, acquisition, construction, linked data, integration, storage management, natural language understanding, semantic computing, applications, and open resources. \u003c\/blockquote\u003e\u003cp\u003e\u003cstrong\u003eFormat\u003c\/strong\u003e: Paperback \/ softback\u003cbr\u003e\u003cstrong\u003eLength\u003c\/strong\u003e: 330 pages\u003cbr\u003e\u003cstrong\u003ePublication date\u003c\/strong\u003e: 07 October 2021\u003cbr\u003e\u003cstrong\u003ePublisher\u003c\/strong\u003e: Springer Verlag, Singapore\u003cbr\u003e\u003c\/p\u003e \u003cp\u003e\u003cbr\u003eThe 6th China Conference on Knowledge Graph and Semantic Computing (CCKS 2021) was held in Guangzhou, China, in November 2021, with the theme of \"Advancing Knowledge Graph and Semantic Computing for Real-World Applications.\" The conference brought together experts and researchers from around the world to discuss the latest advancements and challenges in the field.\u003cbr\u003e\u003cbr\u003eThe conference featured a total of 19 revised full papers and 9 short papers, which were carefully reviewed and selected from 170 submissions. The papers were organized into topical sections, covering various aspects of knowledge graph and semantic computing.\u003cbr\u003e\u003cbr\u003eThe first section focused on knowledge extraction, including techniques for extracting knowledge from structured and unstructured data sources. The papers discussed methods for building knowledge graphs, representing knowledge in graph form, and reasoning with knowledge graphs.\u003cbr\u003e\u003cbr\u003eThe second section explored knowledge acquisition and knowledge graph construction, focusing on methods for acquiring and integrating large-scale knowledge graphs from various sources. The papers discussed techniques for cleaning and preprocessing data, constructing knowledge graphs from heterogeneous data, and optimizing knowledge graph construction algorithms.\u003cbr\u003e\u003cbr\u003eThe third section dealt with linked data, knowledge integration, and knowledge graph storage management. The papers discussed strategies for linking different knowledge graphs, integrating heterogeneous data sources, and managing knowledge graphs in large-scale environments.\u003cbr\u003e\u003cbr\u003eThe fourth section explored natural language understanding and semantic computing, focusing on methods for understanding and interpreting human language and generating semantic representations of knowledge. The papers discussed techniques for semantic search, question answering, dialogue systems, decision support, and recommendation systems.\u003cbr\u003e\u003cbr\u003eThe fifth section showcased knowledge graph applications in various domains, including semantic search, question answering, dialogue systems, decision support, and recommendation systems. The papers presented case studies and practical applications of knowledge graphs in healthcare, finance, education, and other fields.\u003cbr\u003e\u003cbr\u003eThe sixth section discussed knowledge graph open resources, including datasets, tools, and platforms for building and using knowledge graphs. The papers discussed existing knowledge graph repositories, tools for graph manipulation and analysis, and platforms for sharing and collaboration in the knowledge graph community.\u003cbr\u003e\u003cbr\u003eOverall, the 6th China Conference on Knowledge Graph and Semantic Computing was a successful event that brought together experts and researchers from diverse fields to exchange ideas and share their research findings. The conference provided a platform for discussing the latest advancements in knowledge graph and semantic computing, as well as identifying new research directions and challenges.\u003cbr\u003e\u003cbr\u003eThe conference proceedings will be published in the Springer series on Knowledge and Information Systems. The papers will be available for download from the conference website and will also be indexed in major academic databases such as Scopus and Google Scholar.\u003cbr\u003e\u003cbr\u003eThe 6th China Conference on Knowledge Graph and Semantic Computing (CCKS 2021) was held in Guangzhou, China, in November 2021, with the theme of \"Advancing Knowledge Graph and Semantic Computing for Real-World Applications.\" The conference brought together experts and researchers from around the world to discuss the latest advancements and challenges in the field.\u003cbr\u003e\u003cbr\u003eThe conference featured a total of 19 revised full papers and 9 short papers, which were carefully reviewed and selected from 170 submissions. The papers were organized into topical sections, covering various aspects of knowledge graph and semantic computing.\u003cbr\u003e\u003cbr\u003eThe first section focused on knowledge extraction, including techniques for extracting knowledge from structured and unstructured data sources. The papers discussed methods for building knowledge graphs, representing knowledge in graph form, and reasoning with knowledge graphs.\u003cbr\u003e\u003cbr\u003eThe second section explored knowledge acquisition and knowledge graph construction, focusing on methods for acquiring and integrating large-scale knowledge graphs from various sources. The papers discussed techniques for cleaning and preprocessing data, constructing knowledge graphs from heterogeneous data, and optimizing knowledge graph construction algorithms.\u003cbr\u003e\u003cbr\u003eThe third section dealt with linked data, knowledge integration, and knowledge graph storage management. The papers discussed strategies for linking different knowledge graphs, integrating heterogeneous data sources, and managing knowledge graphs in large-scale environments.\u003cbr\u003e\u003cbr\u003eThe fourth section explored natural language understanding and semantic computing, focusing on methods for understanding and interpreting human language and generating semantic representations of knowledge. The papers discussed techniques for semantic search, question answering, dialogue systems, decision support, and recommendation systems.\u003cbr\u003e\u003cbr\u003eThe fifth section showcased knowledge graph applications in various domains, including semantic search, question answering, dialogue systems, decision support, and recommendation systems. The papers presented case studies and practical applications of knowledge graphs in healthcare, finance, education, and other fields.\u003cbr\u003e\u003cbr\u003eThe sixth section discussed knowledge graph open resources, including datasets, tools, and platforms for building and using knowledge graphs. The papers discussed existing knowledge graph repositories, tools for graph manipulation and analysis, and platforms for sharing and collaboration in the knowledge graph community.\u003cbr\u003e\u003cbr\u003eOverall, the 6th China Conference on Knowledge Graph and Semantic Computing was a successful event that brought together experts and researchers from diverse fields to exchange ideas and share their research findings. The conference provided a platform for discussing the latest advancements in knowledge graph and semantic computing, as well as identifying new research directions and challenges.\u003cbr\u003e\u003cbr\u003eThe conference proceedings will be published in the Springer series on Knowledge and Information Systems. The papers will be available for download from the conference website and will also be indexed in major academic databases such as Scopus and Google Scholar.\u003cbr\u003e\u003cbr\u003eThe 6th China Conference on Knowledge Graph and Semantic Computing (CCKS 2021) was held in Guangzhou, China, in November 2021, with the theme of \"Advancing Knowledge Graph and Semantic Computing for Real-World Applications.\" The conference brought together experts and researchers from around the world to discuss the latest advancements and challenges in the field.\u003cbr\u003e\u003cbr\u003eThe conference featured a total of 19 revised full papers and 9 short papers, which were carefully reviewed and selected from 170 submissions. The papers were organized into topical sections, covering various aspects of knowledge graph and semantic computing.\u003cbr\u003e\u003cbr\u003eThe first section focused on knowledge extraction, including techniques for extracting knowledge from structured and unstructured data sources. The papers discussed methods for building knowledge graphs, representing knowledge in graph form, and reasoning with knowledge graphs.\u003cbr\u003e\u003cbr\u003eThe second section explored knowledge acquisition and knowledge graph construction, focusing on methods for acquiring and integrating large-scale knowledge graphs from various sources. The papers discussed techniques for cleaning and preprocessing data, constructing knowledge graphs from heterogeneous data, and optimizing knowledge graph construction algorithms.\u003cbr\u003e\u003cbr\u003eThe third section dealt with linked data, knowledge integration, and knowledge graph storage management. The papers discussed strategies for linking different knowledge graphs, integrating heterogeneous data sources, and managing knowledge graphs in large-scale environments.\u003cbr\u003e\u003cbr\u003eThe fourth section explored natural language understanding and semantic computing, focusing on methods for understanding and interpreting human language and generating semantic representations of knowledge. The papers discussed techniques for semantic search, question answering, dialogue systems, decision support, and recommendation systems.\u003cbr\u003e\u003cbr\u003eThe fifth section showcased knowledge graph applications in various domains, including semantic search, question answering, dialogue systems, decision support, and recommendation systems. The papers presented case studies and practical applications of knowledge graphs in healthcare, finance, education, and other fields.\u003cbr\u003e\u003cbr\u003eThe sixth section discussed knowledge graph open resources, including datasets, tools, and platforms for building and using knowledge graphs. The papers discussed existing knowledge graph repositories, tools for graph manipulation and analysis, and platforms for sharing and collaboration in the knowledge graph community.\u003cbr\u003e\u003cbr\u003eOverall, the 6th China Conference on Knowledge Graph and Semantic Computing was a successful event that brought together experts and researchers from diverse fields to exchange ideas and share their research findings. The conference provided a platform for discussing the latest advancements in knowledge graph and semantic computing, as well as identifying new research directions and challenges.\u003cbr\u003e\u003cbr\u003eThe conference proceedings will be published in the Springer series on Knowledge and Information Systems. The papers will be available for download from the conference website and will also be indexed in major academic databases such as Scopus and Google Scholar.\u003cbr\u003e\u003cbr\u003eThe 6th China Conference on Knowledge Graph and Semantic Computing (CCKS 2021) was held in Guangzhou, China, in November 2021, with the theme of \"Advancing Knowledge Graph and Semantic Computing for Real-World Applications.\" The conference brought together experts and researchers from around the world to discuss the latest advancements and challenges in the field.\u003cbr\u003e\u003cbr\u003eThe conference featured a total of 19 revised full papers and 9 short papers, which were carefully reviewed and selected from 170 submissions. The papers were organized into topical sections, covering various aspects of knowledge graph and semantic computing.\u003cbr\u003e\u003cbr\u003eThe first section focused on knowledge extraction, including techniques for extracting knowledge from structured and unstructured data sources. The papers discussed methods for building knowledge graphs, representing knowledge in graph form, and reasoning with knowledge graphs.\u003cbr\u003e\u003cbr\u003eThe second section explored knowledge acquisition and knowledge graph construction, focusing on methods for acquiring and integrating large-scale knowledge graphs from various sources. The papers discussed techniques for cleaning and preprocessing data, constructing knowledge graphs from heterogeneous data, and optimizing knowledge graph construction algorithms.\u003cbr\u003e\u003cbr\u003eThe third section dealt with linked data, knowledge integration, and knowledge graph storage management. The papers discussed strategies for linking different knowledge graphs, integrating heterogeneous data sources, and managing knowledge graphs in large-scale environments.\u003cbr\u003e\u003cbr\u003eThe fourth section explored natural language understanding and semantic computing, focusing on methods for understanding and interpreting human language and generating semantic representations of knowledge. The papers discussed techniques for semantic search, question answering, dialogue systems, decision support, and recommendation systems.\u003cbr\u003e\u003cbr\u003eThe fifth section showcased knowledge graph applications in various domains, including semantic search, question answering, dialogue systems, decision support, and recommendation systems. The papers presented case studies and practical applications of knowledge graphs in healthcare, finance, education, and other fields.\u003cbr\u003e\u003cbr\u003eThe sixth section discussed knowledge graph open resources, including datasets, tools, and platforms for building and using knowledge graphs. The papers discussed existing knowledge graph repositories, tools for graph manipulation and analysis, and platforms for sharing and collaboration in the knowledge graph community.\u003cbr\u003e\u003cbr\u003eOverall, the 6th China Conference on Knowledge Graph and Semantic Computing was a successful event that brought together experts and researchers from diverse fields to exchange ideas and share their research findings. The conference provided a platform for discussing the latest advancements in knowledge graph and semantic computing, as well as identifying new research directions and challenges.\u003cbr\u003e\u003cbr\u003eThe conference proceedings will be published in the Springer series on Knowledge and Information Systems. The papers will be available for download from the conference website and will also be indexed in major academic databases such as Scopus and Google Scholar.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWeight\u003c\/strong\u003e: 534g\u003cbr\u003e\u003cstrong\u003eDimension\u003c\/strong\u003e: 235 x 155 (mm)\u003cbr\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e: 9789811664700\u003cbr\u003e \u003cstrong\u003eEdition number\u003c\/strong\u003e: 1st ed. 2021\u003c\/p\u003e","brand":"Shulph Ink","offers":[{"title":"Paperback \/ softback","offer_id":44103091749114,"sku":"9789811664700","price":58.3,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0522\/4297\/2845\/products\/1646108911526_book.jpg?v=1646467510","url":"https:\/\/shulphink.com\/products\/knowledge-graph-and-semantic-computing-knowledge-graph-empowers-new-infrastructure-construction-6th-china-conference-ccks-2021-guangzhou-china-november-47-2021-proceedings-9789811664700","provider":"Shulph Ink","version":"1.0","type":"link"}