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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.
List of contents
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.- MoralEssential 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.
