Improving Knowledge Graph Construction Through Multi-Agent Collaboration: The CooperKGC Framework
Collaborating large language model agents, specialized in different knowledge graph construction tasks, outperform single-agent approaches by leveraging iterative feedback and knowledge sharing for improved entity, relation, and event extraction.
산림 정책 지식 그래프 구축 프레임워크(ForPKG-1.0) 및 적용 분석
본 논문에서는 효율적인 산림 정책 분석을 위한 지식 그래프 구축 프레임워크(ForPKG-1.0)를 제안하고, 이를 대규모 언어 모델의 정보 검색 및 생성 작업에 적용하여 그 실용적 가치를 입증합니다.
ForPKG-1.0: A Framework for Constructing a Forestry Policy Knowledge Graph and Its Application in Retrieval-Augmented Generation
This paper introduces a novel framework, ForPKG-1.0, for constructing a knowledge graph specifically for forestry policies, utilizing open-source large language models (LLMs) for information extraction and demonstrating its value in enhancing the performance of LLMs in retrieval-augmented generation tasks.
Automatic Construction of Hierarchical Knowledge Graphs from Images for E-Commerce Applications
This paper proposes a novel, fully automated method for constructing hierarchical knowledge graphs from product images, leveraging the power of Vision-Language Models (VLMs) and Large Language Models (LLMs) to enhance e-commerce applications.
Construction of a Liver Cancer Knowledge Graph from Electronic Medical Records Using Dynamic Entity Replacement and a RoBERTa-BiLSTM-CRF Model
This research proposes a novel approach to constructing a knowledge graph specifically for liver cancer from Chinese Electronic Medical Records (EMRs), leveraging deep learning techniques for entity recognition and knowledge fusion to improve the accuracy and completeness of medical knowledge representation.
Graphusion: A Novel Framework for Constructing Scientific Knowledge Graphs from Free Text Using Large Language Models with a Global Perspective and Application in Educational Question Answering
Graphusion, a novel framework leveraging large language models (LLMs) and a global perspective, effectively constructs scientific knowledge graphs (KGs) from free text, demonstrating significant improvement in educational question answering tasks.
Distilling Knowledge Graph Synthesis for Improved Coverage and Efficiency: Introducing Distill-SynthKG and a Novel Graph-Based Retrieval Framework
This paper introduces Distill-SynthKG, a novel approach for efficient and effective knowledge graph (KG) construction from text, and demonstrates its superior performance in retrieval and question-answering tasks.
SAKA: 사용자 친화적인 준 자동화 지식 그래프 구축 및 활용 플랫폼
SAKA는 사용자가 구조화된 데이터 또는 오디오 데이터에서 준 자동으로 지식 그래프를 구축하고, 이를 활용하여 질의응답 시스템을 구축할 수 있는 플랫폼이다.
SAKA: A User-Friendly Platform for Semi-Automated Knowledge Graph Construction and Application with Audio Processing Capabilities
SAKA is a novel platform that simplifies knowledge graph construction and application by enabling semi-automated extraction of information from structured data and audio, making KG technology accessible to a wider audience.
PubMed Knowledge Graph 2.0: Integrating Papers, Patents, and Clinical Trials for a Comprehensive View of Biomedical Science
PKG 2.0 is a comprehensive knowledge graph that integrates papers, patents, and clinical trials in biomedicine, providing a holistic view of the research landscape and enabling researchers to uncover patterns and insights previously obscured by siloed data.
