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Link Prediction
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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>
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs
Understanding Generalization in Node and Link Prediction
Context-Driven Knowledge Graph Completion with Semantic-Aware Relational Message Passing
Directed Link Prediction using GNN with Local and Global Feature Fusion
Demystifying Distributed Training of Graph Neural Networks for Link Prediction
Call Me Maybe: Enhancing JavaScript Call Graph Construction using Graph Neural Networks
A Transfer Learning Framework for Multilayer Networks via Model Averaging
How do Probabilistic Graphical Models and Graph Neural Networks Look at Network Data?
Learnable Spatial-Temporal Positional Encoding for Link Prediction
A Survey of Link Prediction in N-ary Knowledge Graphs
Invariant Link Selector for Spatial-Temporal Out-of-Distribution Problem
GenIC: An LLM-Based Framework for Instance Completion in Knowledge Graphs
Bridging Source and Target Domains via Link Prediction for Unsupervised Domain Adaptation on Graphs
Directed Homophily-Aware Graph Neural Network
Broad Spectrum Structure Discovery in Large-Scale Higher-Order Networks
Future Link Prediction Without Memory or Aggregation
Graph Guided Diffusion: Unified Guidance for Conditional Graph Generation
OCN: Effectively Utilizing Higher-Order Common Neighbors for Better Link Prediction
G1: Teaching LLMs to Reason on Graphs with Reinforcement Learning
EC-LDA : Label Distribution Inference Attack against Federated Graph Learning with Embedding Compression
Higher-order Structure Boosts Link Prediction on Temporal Graphs
Unify Graph Learning with Text: Unleashing LLM Potentials for Session Search
A PID-Controlled Tensor Wheel Decomposition Model for Dynamic Link Prediction
MPRM: A Markov Path-based Rule Miner for Efficient and Interpretable Knowledge Graph Reasoning
VITA: Versatile Time Representation Learning for Temporal Hyper-Relational Knowledge Graphs
VitaGraph: Building a Knowledge Graph for Biologically Relevant Learning Tasks
MUST: Multi-Scale Structural-Temporal Link Prediction Model for UAV Ad Hoc Networks
Open the Eyes of MPNN: Vision Enhances MPNN in Link Prediction
Learning from Samples: Inverse Problems over measures via Sharpened Fenchel-Young Losses
Structural Alignment in Link Prediction
Community and hyperedge inference in multiple hypergraphs
Social Biases in Knowledge Representations of Wikidata separates Global North from Global South
Understanding the Mechanisms Behind Structural Influences on Link Prediction: A Case Study on FB15k-237
Scalability Matters: Overcoming Challenges in InstructGLM with Similarity-Degree-Based Sampling
ABG-NAS: Adaptive Bayesian Genetic Neural Architecture Search for Graph Representation Learning
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