東華大學圖書館 |

Knowledge graph and semantic computing = knowledge graph empowers artificial general intelligence : 8th China Conference, CCKS 2023, Shenyang, China, August 24-27, 2023 : revised selected papers /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Knowledge graph and semantic computing/ edited by Haofen Wang ... [et al.].
其他題名:	knowledge graph empowers artificial general intelligence : 8th China Conference, CCKS 2023, Shenyang, China, August 24-27, 2023 : revised selected papers /
其他題名:	CCKS 2023
其他作者:	Wang, Haofen.
團體作者:	CCKS (Conference)
出版者:	Singapore :Springer Nature Singapore : : 2023.,
面頁冊數:	xix, 364 p. :ill. (some col.), digital ;24 cm.
內容註:	Knowledge Representation and Knowledge Graph Reasoning -- Dynamic Weighted Neural Bellman-Ford Network for Knowledge Graph Reasoning -- CausE: Towards Causal Knowledge Graph Embedding -- Exploring the Logical Expressiveness of Graph Neural Networks by establishing a connection with C2 -- Research on Joint Representation Learning Methods for Entity Neighborhood Information and Description Information -- Knowledge Acquisition and Knowledge Base Construction -- Harvesting Event Schemas from Large Language Models -- NTDA: Noise-Tolerant Data Augmentation for Document-Level Event Argument Extraction -- Event-Centric Opinion Mining via In-Context Learning with ChatGPT -- Relation repository based adaptive clustering for Open Relation Extraction -- Knowledge Integration and Knowledge Graph Management -- LNFGP: Local Node Fusion-based Graph Partition By Greedy Clustering -- Natural Language Understanding and Semantic Computing -- Multi-Perspective Frame Element Representation for Machine Reading Comprehension -- A Generalized Strategy of Chinese Grammatical Error Diagnosis based on Task Decomposition and Transformation -- Conversational Search based on Utterance-Mask-Passage Post-training -- Knowledge Graph Applications -- Financial Fraud Detection based on Deep Learning: towards Large-scale Pre-Training Transformer Models -- GERNS: A Graph Embedding with Repeat-free Neighborhood Structure for Subgraph Matching Optimization -- Feature Enhanced Structured Reasoning for Question Answering -- Knowledge Graph Open Resources -- Conditional Knowledge Graph: Design, Dataset and a Preliminary Model -- ODKG: An Official Document Knowledge Graph for the Effective Management -- CCD-ASQP: A Chinese Cross-domain Aspect Sentiment Quadruple Prediction Dataset -- CCD-ASQP: A Chinese Cross-domain Aspect Sentiment Quadruple Prediction Dataset -- Moral Essential Elements: MEE - A Dataset for Moral Judgement -- Evaluations -- Improving Adaptive Knowledge Graph Construction via Large Language Models with Multiple Views -- Single Source Path-based Graph Neural Network for Inductive Knowledge Graph Reasoning -- A Graph Learning Based Method for Inductive Knowledge Graph Relation Prediction -- LLM-Based Sparql Generation with selected Schema from Large scale Knowledge Base -- Robust NL-to-Cypher Translation for KBQA: Harnessing Large Language Model with Chain of Prompts -- In-Context Learning for Knowledge Base Question Answering for Unmanned Systems based on Large Language Models -- A Military Domain Knowledge-based Question Answering Method Based on Large Language Model Enhancement -- Advanced PromptCBLUE Performance: A Novel Approach Leveraging Large Language Models.
Contained By:	Springer Nature eBook
標題:	Semantic computing - Congresses. -
電子資源:	https://doi.org/10.1007/978-981-99-7224-1
ISBN:	9789819972241

Knowledge graph and semantic computing = knowledge graph empowers artificial general intelligence : 8th China Conference, CCKS 2023, Shenyang, China, August 24-27, 2023 : revised selected papers /
Knowledge graph and semantic computingknowledge graph empowers artificial general intelligence : 8th China Conference, CCKS 2023, Shenyang, China, August 24-27, 2023 : revised selected papers /[electronic resource] :CCKS 2023edited by Haofen Wang ... [et al.]. - Singapore :Springer Nature Singapore :2023. - xix, 364 p. :ill. (some col.), digital ;24 cm. - Communications in computer and information science,19231865-0937 ;. - Communications in computer and information science ;1923..

Knowledge Representation and Knowledge Graph Reasoning -- Dynamic Weighted Neural Bellman-Ford Network for Knowledge Graph Reasoning -- CausE: Towards Causal Knowledge Graph Embedding -- Exploring the Logical Expressiveness of Graph Neural Networks by establishing a connection with C2 -- Research on Joint Representation Learning Methods for Entity Neighborhood Information and Description Information -- Knowledge Acquisition and Knowledge Base Construction -- Harvesting Event Schemas from Large Language Models -- NTDA: Noise-Tolerant Data Augmentation for Document-Level Event Argument Extraction -- Event-Centric Opinion Mining via In-Context Learning with ChatGPT -- Relation repository based adaptive clustering for Open Relation Extraction -- Knowledge Integration and Knowledge Graph Management -- LNFGP: Local Node Fusion-based Graph Partition By Greedy Clustering -- Natural Language Understanding and Semantic Computing -- Multi-Perspective Frame Element Representation for Machine Reading Comprehension -- A Generalized Strategy of Chinese Grammatical Error Diagnosis based on Task Decomposition and Transformation -- Conversational Search based on Utterance-Mask-Passage Post-training -- Knowledge Graph Applications -- Financial Fraud Detection based on Deep Learning: towards Large-scale Pre-Training Transformer Models -- GERNS: A Graph Embedding with Repeat-free Neighborhood Structure for Subgraph Matching Optimization -- Feature Enhanced Structured Reasoning for Question Answering -- Knowledge Graph Open Resources -- Conditional Knowledge Graph: Design, Dataset and a Preliminary Model -- ODKG: An Official Document Knowledge Graph for the Effective Management -- CCD-ASQP: A Chinese Cross-domain Aspect Sentiment Quadruple Prediction Dataset -- CCD-ASQP: A Chinese Cross-domain Aspect Sentiment Quadruple Prediction Dataset -- Moral Essential Elements: MEE - A Dataset for Moral Judgement -- Evaluations -- Improving Adaptive Knowledge Graph Construction via Large Language Models with Multiple Views -- Single Source Path-based Graph Neural Network for Inductive Knowledge Graph Reasoning -- A Graph Learning Based Method for Inductive Knowledge Graph Relation Prediction -- LLM-Based Sparql Generation with selected Schema from Large scale Knowledge Base -- Robust NL-to-Cypher Translation for KBQA: Harnessing Large Language Model with Chain of Prompts -- In-Context Learning for Knowledge Base Question Answering for Unmanned Systems based on Large Language Models -- A Military Domain Knowledge-based Question Answering Method Based on Large Language Model Enhancement -- Advanced PromptCBLUE Performance: A Novel Approach Leveraging Large Language Models.

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.

ISBN: 9789819972241

Standard No.: 10.1007/978-981-99-7224-1doiSubjects--Topical Terms:

1085629
Semantic computing
--Congresses.

LC Class. No.: QA76.5913 / .C35 2023

Dewey Class. No.: 006.332

Knowledge graph and semantic computing = knowledge graph empowers artificial general intelligence : 8th China Conference, CCKS 2023, Shenyang, China, August 24-27, 2023 : revised selected papers /
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