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Link prediction is a task to estimate the probability of links between nodes in a graph.

( Image credit: Inductive Representation Learning on Large Graphs )

Benchmarks

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Subtasks

Datasets

Latest papers without code

Graph Learning: A Survey

3 May 2021

In this survey, we present a comprehensive overview on the state-of-the-art of graph learning.

COMBINATORIAL OPTIMIZATION GRAPH LEARNING KNOWLEDGE GRAPHS LINK PREDICTION

MUSE: Multi-faceted Attention for Signed Network Embedding

29 Apr 2021

Signed network embedding is an approach to learn low-dimensional representations of nodes in signed networks with both positive and negative links, which facilitates downstream tasks such as link prediction with general data mining frameworks.

LINK PREDICTION NETWORK EMBEDDING

Biased Edge Dropout for Enhancing Fairness in Graph Representation Learning

29 Apr 2021

In this paper, we propose a biased edge dropout algorithm (FairDrop) to counter-act homophily and improve fairness in graph representation learning.

FAIRNESS GRAPH REPRESENTATION LEARNING LINK PREDICTION

Network Embedding via Deep Prediction Model

27 Apr 2021

This paper proposes a network embedding framework to capture the transfer behaviors on structured networks via deep prediction models.

FEATURE ENGINEERING LINK PREDICTION NETWORK EMBEDDING

HYPER^2: Hyperbolic Poincare Embedding for Hyper-Relational Link Prediction

20 Apr 2021

Link Prediction, addressing the issue of completing KGs with missing facts, has been broadly studied.

LINK PREDICTION

Locate Who You Are: Matching Geo-location to Text for Anchor Link Prediction

19 Apr 2021

However, encouraged by online services, users would also post asymmetric information across networks, such as geo-locations and texts.

ANCHOR LINK PREDICTION

CEAR: Cross-Entity Aware Reranker for Knowledge Base Completion

18 Apr 2021

Pre-trained language models (LMs) like BERT have shown to store factual knowledge about the world.

KNOWLEDGE BASE COMPLETION LINK PREDICTION

Membership Inference Attacks on Knowledge Graphs

16 Apr 2021

Knowledge graphs have become increasingly popular supplemental information because they represented structural relations between entities.

INFERENCE ATTACK KNOWLEDGE GRAPH COMPLETION KNOWLEDGE GRAPH EMBEDDING LINK PREDICTION TRIPLE CLASSIFICATION

Node Co-occurrence based Graph Neural Networks for Knowledge Graph Link Prediction

15 Apr 2021

We introduce a novel embedding model, named NoKE, which aims to integrate co-occurrence among entities and relations into graph neural networks to improve knowledge graph completion (i. e., link prediction).

KNOWLEDGE GRAPH COMPLETION LINK PREDICTION

Dynamic Graph Neural Networks for Sequential Recommendation

15 Apr 2021

We propose a new method named \emph{Dynamic Graph Neural Network for Sequential Recommendation} (DGSR), which connects the sequence of different users through a dynamic graph structure, exploring the interactive behavior of users and items with time and order information.

LINK PREDICTION