Knowledge Graphs
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A knowledge graph is a structured representation of information that organizes data into nodes (entities) and edges (relationships) to show how different pieces of knowledge are interconnected. It enables enhanced data integration, search, and inference by modeling the relationships between concepts and entities in a graph format.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/lamm-mit/PRefLexOR
공식 코드In-situ graph reasoning and knowledge expansion using Graph-PReFLexOR
https://github.com/lamm-mit/SciAgentsDiscovery
공식 코드SciAgents: Automating scientific discovery through multi-agent intelligent graph reasoning
https://github.com/lamm-mit/graphreasoning
공식 코드https://github.com/lanjiuqing64/kgdata
공식 코드ODA: Observation-Driven Agent for integrating LLMs and Knowledge Graphs
https://github.com/lanl/t-elf
공식 코드https://github.com/laowangzi/cikgrec
공식 코드Bridging the User-side Knowledge Gap in Knowledge-aware Recommendations with Large Language Models
https://github.com/laquabe/know3rag
공식 코드Know3-RAG: A Knowledge-aware RAG Framework with Adaptive Retrieval, Generation, and Filtering
https://github.com/lars-research/adaprop
공식 코드AdaProp: Learning Adaptive Propagation for Graph Neural Network based Knowledge Graph Reasoning
https://github.com/lars-research/knowddi
공식 코드Accurate and interpretable drug-drug interaction prediction enabled by knowledge subgraph learning
https://github.com/lautel/meg
공식 코드MEG: Medical Knowledge-Augmented Large Language Models for Question Answering
https://github.com/lavis-nlp/irt2
공식 코드IRT2: Inductive Linking and Ranking in Knowledge Graphs of Varying Scale
https://github.com/lb0828/ftg
공식 코드https://github.com/lbauer6/IdentifyAlignIntegrate
공식 코드Identify, Align, and Integrate: Matching Knowledge Graphs to Commonsense Reasoning Tasks
https://github.com/lcai2/lighttea
공식 코드https://github.com/lcai2/stea
공식 코드https://github.com/lcs2-iiitd/emnlp-coffee
공식 코드https://github.com/leapxcheng/rawnp
공식 코드https://github.com/lechengkong/oneforall
공식 코드One for All: Towards Training One Graph Model for All Classification Tasks
https://github.com/leduckhai/wav2graph
공식 코드wav2graph: A Framework for Supervised Learning Knowledge Graph from Speech
https://github.com/lehaifeng/T-GCN
공식 코드KST-GCN: A Knowledge-Driven Spatial-Temporal Graph Convolutional Network for Traffic Forecasting
https://github.com/lenazellinger/counterfactual_kgr
공식 코드https://github.com/lenkatetkova/knowledge-graphs-for-empirical-concept-retrieval
공식 코드https://github.com/lhrlab/chatkbqa
공식 코드https://github.com/lhrlab/hahe
공식 코드HAHE: Hierarchical Attention for Hyper-Relational Knowledge Graphs in Global and Local Level
https://github.com/lhrlab/nqe
공식 코드NQE: N-ary Query Embedding for Complex Query Answering over Hyper-Relational Knowledge Graphs
https://github.com/liangke23/awesome-knowledge-graph-reasoning
공식 코드A Survey of Knowledge Graph Reasoning on Graph Types: Static, Dynamic, and Multimodal
https://github.com/liaopeiyuan/GAL
공식 코드https://github.com/lihuiliullh/lgot
공식 코드https://github.com/lilv98/logicrec
공식 코드https://github.com/ling-cai/time2box
공식 코드Time in a Box: Advancing Knowledge Graph Completion with Temporal Scopes
https://github.com/liniallab/interfeat
공식 코드InterFeat: An Automated Pipeline for Finding Interesting Hypotheses in Structured Biomedical Data
https://github.com/linxueyuanstdio/tflex
공식 코드https://github.com/lion-zs/er
공식 코드https://github.com/lion-zs/gie
공식 코드https://github.com/lirt1231/degreembed
공식 코드DegreEmbed: incorporating entity embedding into logic rule learning for knowledge graph reasoning
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.