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E-raamat: 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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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 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.
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