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_aKnowledge Graph and Semantic Computing: Knowledge Graph Empowers Artificial General Intelligence _h[electronic resource] : _b8th China Conference, CCKS 2023, Shenyang, China, August 24-27, 2023, Revised Selected Papers / _cedited by Haofen Wang, Xianpei Han, Ming Liu, Gong Cheng, Yongbin Liu, Ningyu Zhang. |
250 | _a1st ed. 2023. | ||
264 | 1 |
_aSingapore : _bSpringer Nature Singapore : _bImprint: Springer, _c2023. |
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300 |
_aXIX, 364 p. 93 illus., 79 illus. in color. _bonline resource. |
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_atext _btxt _2rdacontent |
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_acomputer _bc _2rdamedia |
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490 | 1 |
_aCommunications in Computer and Information Science, _x1865-0937 ; _v1923 |
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500 | _aAcceso multiusuario | ||
505 | 0 | _aKnowledge 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. | |
520 | _aThis 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. | ||
541 |
_fUABC ; _cPerpetuidad |
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650 | 0 | _aArtificial intelligence. | |
650 | 0 | _aApplication software. | |
650 | 0 | _aInformation storage and retrieval systems. | |
650 | 0 | _aDatabase management. | |
650 | 0 | _aData mining. | |
650 | 0 |
_aInformation technology _xManagement. |
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650 | 1 | 4 | _aArtificial Intelligence. |
650 | 2 | 4 | _aComputer and Information Systems Applications. |
650 | 2 | 4 | _aInformation Storage and Retrieval. |
650 | 2 | 4 | _aDatabase Management. |
650 | 2 | 4 | _aData Mining and Knowledge Discovery. |
650 | 2 | 4 | _aComputer Application in Administrative Data Processing. |
700 | 1 |
_aWang, Haofen. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
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700 | 1 |
_aHan, Xianpei. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
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700 | 1 |
_aLiu, Ming. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
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700 | 1 |
_aCheng, Gong. _eeditor. _0(orcid)0000-0003-3539-7776 _1https://orcid.org/0000-0003-3539-7776 _4edt _4http://id.loc.gov/vocabulary/relators/edt |
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700 | 1 |
_aLiu, Yongbin. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
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700 | 1 |
_aZhang, Ningyu. _eeditor. _0(orcid)0000-0002-1970-0678 _1https://orcid.org/0000-0002-1970-0678 _4edt _4http://id.loc.gov/vocabulary/relators/edt |
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