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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/dmlc/dgl/tree/master/examples/tensorflow/rgcn
https://github.com/eBay/KPRN
Explainable Reasoning over Knowledge Graphs for Recommendation
https://github.com/epfl-nlp/kogito
COMET-ATOMIC 2020: On Symbolic and Neural Commonsense Knowledge Graphs
https://github.com/eric-ai-lab/probmed
MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI
https://github.com/filco306/challenging-structural-assumptions
Generative Adversarial Zero-Shot Relational Learning for Knowledge Graphs
https://github.com/fs302/EasyLink
Neural Bellman-Ford Networks: A General Graph Neural Network Framework for Link Prediction
https://github.com/fs302/EasyLink/blob/main/example/ogbl_ppa_ra.py
Neural Bellman-Ford Networks: A General Graph Neural Network Framework for Link Prediction
https://github.com/fumiyo0607/KGAN
https://github.com/gengchenmai/se-kge
Contextual Graph Attention for Answering Logical Queries over Incomplete Knowledge Graphs
https://github.com/giacoballoccu/rep-path-reasoning-recsys
Reinforcement Recommendation Reasoning through Knowledge Graphs for Explanation Path Quality
https://github.com/giantonia/KGATv2
https://github.com/giuseppefutia/semi
https://github.com/graphcore-research/bess-kge
BESS: Balanced Entity Sampling and Sharing for Large-Scale Knowledge Graph Completion
https://github.com/graphcore/ogb-lsc-pcqm4mv2
OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs
https://github.com/guillaumejaume/tuto-dl-on-graphs
https://github.com/guixiangyu1/KGE-HAKE-master
Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction
https://github.com/hannaabiakl/psychic
PSYCHIC: A Neuro-Symbolic Framework for Knowledge Graph Question-Answering Grounding
https://github.com/hsientzucheng/MKR.PyTorch
Multi-Task Feature Learning for Knowledge Graph Enhanced Recommendation
https://github.com/hubiodatalab/druggen
https://github.com/hwwang55/KGCN
Multi-Task Feature Learning for Knowledge Graph Enhanced Recommendation
https://github.com/hwwang55/KGNN-LS
Knowledge-aware Graph Neural Networks with Label Smoothness Regularization for Recommender Systems
https://github.com/hyren/PathCon
https://github.com/hzli-ucas/StarGraph
StarGraph: Knowledge Representation Learning based on Incomplete Two-hop Subgraph
https://github.com/icml2024357/hombasis-gnn
Open Graph Benchmark: Datasets for Machine Learning on Graphs
https://github.com/jaemuzzin/plagnn
https://github.com/jennyzhang0215/DGL-KGAT
https://github.com/jerermyyoung/AutoWeird
Open Graph Benchmark: Datasets for Machine Learning on Graphs
https://github.com/jiean001/models_m/tree/main/hake
Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction
https://github.com/jiean001/models_m/tree/main/rotate
RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space
https://github.com/jingsonglv/CFG
Open Graph Benchmark: Datasets for Machine Learning on Graphs
https://github.com/johannesmessner/boxte
https://github.com/julessanchez/x-nesyl
https://github.com/kamigaito/icml2022
Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction
https://github.com/kingcong/models/tree/main/hake
Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction
https://github.com/knowlab/bi-weekly-paper-presentation
Understanding the Performance of Knowledge Graph Embeddings in Drug Discovery
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.