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Link Prediction

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하위 태스크: 6
평가표: 79
보존된 평가 기록: 497

Link Prediction is a task in graph and network analysis where the goal is to predict missing or future connections between nodes in a network. Given a partially observed network, the goal of link prediction is to infer which links are most likely to be added or missing based on the observed connections and the structure of the network.

<span style="color:grey; opacity: 0.6">( Image credit: Inductive Representation Learning on Large Graphs )</span>

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/yunchengwang/greenkgc

공식 코드

GreenKGC: A Lightweight Knowledge Graph Completion Method

https://github.com/yushanzhu/k3m

공식 코드

Knowledge Perceived Multi-modal Pretraining in E-commerce

https://github.com/yuvalpinter/m3gm

공식 코드

Predicting Semantic Relations using Global Graph Properties

https://github.com/yuwvandy/topo_lp_gnn

공식 코드

A Topological Perspective on Demystifying GNN-Based Link Prediction Performance

https://github.com/yuzhu2019/fe_embed

공식 코드

Free Energy Node Embedding via Generalized Skip-gram with Negative Sampling

https://github.com/yxzwang/submissionverofyinyangnn

공식 코드

Efficient Link Prediction via GNN Layers Induced by Negative Sampling

https://github.com/yy-ko/cash

공식 코드

Enhancing Hyperedge Prediction with Context-Aware Self-Supervised Learning

https://github.com/zangzelin/paper_code_DMAGE/blob/main/README.md

공식 코드

Unsupervised Deep Manifold Attributed Graph Embedding

https://github.com/zboyd2/hitting_probabilities_metric

공식 코드

A metric on directed graphs and Markov chains based on hitting probabilities

https://github.com/zdh2292390/ParTrans-X

공식 코드

Efficient Parallel Translating Embedding For Knowledge Graphs

https://github.com/zehong-wang/gpm

공식 코드

Beyond Message Passing: Neural Graph Pattern Machine

https://github.com/zehong-wang/simmlp

공식 코드

SimMLP: Training MLPs on Graphs without Supervision

https://github.com/zekarias-tilahun/GAP

공식 코드

Graph Neighborhood Attentive Pooling

https://github.com/zekarias-tilahun/diagram

공식 코드

Which way? Direction-Aware Attributed Graph Embedding

https://github.com/zekarias-tilahun/goat

공식 코드

Gossip and Attend: Context-Sensitive Graph Representation Learning

https://github.com/zequnl/metafill

공식 코드

MetaFill: Text Infilling for Meta-Path Generation on Heterogeneous Information Networks

https://github.com/zexihuang/pole

공식 코드

POLE: Polarized Embedding for Signed Networks

https://github.com/zexihuang/random-walk-embedding

공식 코드

A Broader Picture of Random-walk Based Graph Embedding

https://github.com/zhiqiangzhongddu/hc-gnn

공식 코드

Hierarchical Message-Passing Graph Neural Networks

https://github.com/zhitao-wang/plnlp

공식 코드

Pairwise Learning for Neural Link Prediction

https://github.com/zifengding/fitcarl

공식 코드

Improving Few-Shot Inductive Learning on Temporal Knowledge Graphs using Confidence-Augmented Reinforcement Learning

https://github.com/zihaowang/text_enhanced_kge

공식 코드

Integrating Knowledge Graph embedding and pretrained Language Models in Hypercomplex Spaces

https://github.com/zinux1998/clusterlp

공식 코드

Rethinking the positive role of cluster structure in complex networks for link prediction tasks

https://github.com/zjs123/DTGB

공식 코드

DTGB: A Comprehensive Benchmark for Dynamic Text-Attributed Graphs

https://github.com/zjukg/ankge

공식 코드

Analogical Inference Enhanced Knowledge Graph Embedding

https://github.com/zjukg/earl

공식 코드

Entity-Agnostic Representation Learning for Parameter-Efficient Knowledge Graph Embedding

https://github.com/zjukg/gpht-for-tsp

공식 코드

Start from Zero: Triple Set Prediction for Automatic Knowledge Graph Completion

https://github.com/zjukg/maker

공식 코드

Meta-Learning Based Knowledge Extrapolation for Knowledge Graphs in the Federated Setting

https://github.com/zjukg/morse

공식 코드

Meta-Knowledge Transfer for Inductive Knowledge Graph Embedding

https://github.com/zjukg/neuralkg

공식 코드

NeuralKG: An Open Source Library for Diverse Representation Learning of Knowledge Graphs

https://github.com/zjunet/damf

공식 코드

Accelerating Dynamic Network Embedding with Billions of Parameter Updates to Milliseconds

https://github.com/zjunlp/MKGformer

공식 코드

Hybrid Transformer with Multi-level Fusion for Multimodal Knowledge Graph Completion

https://github.com/zjunlp/PromptKG/tree/main/research/GenKGC

공식 코드

From Discrimination to Generation: Knowledge Graph Completion with Generative Transformer

https://github.com/zjunlp/autokg

공식 코드

LLMs for Knowledge Graph Construction and Reasoning: Recent Capabilities and Future Opportunities

https://github.com/zjunlp/knn-kg

공식 코드

Reasoning Through Memorization: Nearest Neighbor Knowledge Graph Embeddings

https://github.com/zjunlp/relphormer

공식 코드

Relphormer: Relational Graph Transformer for Knowledge Graph Representations

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.