A Survey of Task-Oriented Knowledge Graph Reasoning: Status, Applications, and Prospects Paper
🚀Main contribution of this survey : This survey provides a more comprehensive perspective on the research of KGR by categorizing approaches based on primary reasoning tasks, downstream application tasks, and potential challenging reasoning tasks. Besides, we explore advanced techniques, such as large language models (LLMs), and their impact on KGR. This work aims to highlight key research trends and outline promising future directions in the field of KGR.
🙌Key characteristics of this repository : Unlike other outstanding review repositories of the knowledge graph reasoning field, we not only provide a comprehensive review but also strive to offer the official publication abstract page for each paper. This includes not only the official publication version of the paper but also additional resources such as author information , videos , datasets , supplementary materials , and BibTeX citations .
If this repository is useful for you, please kindly cite the corresponding survey paper:
@misc{niu2025kgrsurvey,
author = {Guanglin Niu and Bo Li and Yangguang Lin},
title = {A Survey of Task‐Oriented Knowledge Graph Reasoning: Status, Applications, and Prospects},
year = {2025},
eprint = {arXiv:2506.11012},
archivePrefix= {arXiv},
primaryClass = {cs.AI},
url = {https://arxiv.org/abs/2506.11012}
}
The comprehensive overview framework of our survey is presented as following. The same number (①-⑨) indicates that different approaches share similar ideas, and the keywords corresponding to each number are provided at the bottom of the figure.
The illustration of the six primary KGR tasks
Title
Conference/Journal
Year
Characteristic
Paper
A survey of task-oriented knowledge graph reasoning: status, applications, and prospects
arXiv
2025
Task-oriented KGR
link
Knowledge graph embedding: a survey from the perspective of representation spaces
ACM Computer Survey
2024
Embedding Spaces
link
A survey of knowledge graph reasoning on graph types: Static, dynamic, and multi-modal
IEEE TPAMI
2024
Graph Types
link
Negative sampling in knowledge graph representation learning: a review
arXiv
2024
Negative Sampling
link
Overview of knowledge reasoning for knowledge graph
Neurocomputering
2024
Causal Reasoning
link
A survey on temporal knowledge graph: representation learning and applications
arXiv
2024
Temporal Reasoning
link
A survey on temporal knowledge graph completion: taxonomy, progress, and prospects
arXiv
2023
Temporal Reasoning
link
Generalizing to unseen elements: a survey on knowledge extrapolation for knowledge graphs
IJCAI
2023
Unseen Elements
link
A survey on few-shot knowledge graph completion with structural and commonsense knowledge
arXiv
2023
Commonsense
link
Beyond transduction: a survey on inductive, few shot, and zero shot link prediction in knowledge graphs
arXiv
2023
Few-shot & Inductive
link
A comprehensive overview of knowledge graph completion
Knowledge-Based System
2022
Multi-modal & Hyper-relation
link
Knowledgegraph reasoning with logics and embeddings: survey and perspective
arXiv
2022
Logics and Embeddings
link
⬆️
The illustration of five representative KGE models
Translation or Tensor Decomposition-Based KGE Models
Model
Title
Conference/Journal
Year
Paper
TransE
Translating embeddings for modeling multi-relational data
NIPS
2013
link
TransH
Knowledge graph embedding by translating on hyperplanes
AAAI
2014
link
TransR
Learning entity and relation embeddings for knowledge graph completion
AAAI
2015
link
TransD
Knowledge graph embedding via dynamic mapping matrix
ACL
2015
link
TranSparse
Knowledge graph completion with adaptive sparse transfer matrix
AAAI
2016
link
PairE
PairRE: Knowledge graph embeddings via paired relation vectors
ACL
2021
link
TransA
TransA: An adaptive approach for knowledge graph embedding
arXiv
2015
link
KG2E
Learning to represent knowledge graphs with Gaussian embedding
CIKM
2015
link
ManifoldE
From one point to a manifold: Knowledge graph embedding for precise link prediction
IJCAI
2016
link
TorusE
TorusE: Knowledge graph embedding on a Lie group
AAAI
2018
link
Poincaré
Poincare embeddings for learning hierarchical representations
NIPS
2017
link
MuRP
Multi-relational Poincare graph embeddings
NIPS
2019
link
HAKE
Learning hierarchy-aware knowledge graph embeddings for link prediction
AAAI
2020
link
H2E
Knowledge graph representation via hierarchical hyperbolic neural graph embedding
IEEE Big Data
2021
link
HBE
Hyperbolic hierarchy-aware knowledge graph embedding for link prediction
EMNLP
2021
link
RotatE
RotatE: Knowledge graph embedding by relational rotation in complex space
ICLR
2019
link
QuatE
Quaternion knowledge graph embedding
NIPS
2019
link
DualE
Dual quaternion knowledge graph embeddings
AAAI
2021
link
RESCAL
A three-way model for collective learning on multi-relational data
ICML
2011
link
PITF-BPR
Predicting RDF triples in incomplete knowledge bases with tensor factorization
SAC
2012
link
DistMult
Embedding entities and relations for learning and inference in knowledge bases
ICLR
2015
link
ComplEx
Complex embeddings for simple link prediction
ICML
2016
link
HolE
Holographic embeddings of knowledge graphs
AAAI
2016
link
(Graph) Neural Network-based Models
Model
Title
Conference/Journal
Year
Paper
NTN
Reasoning with neural tensor networks for knowledge base completion
NIPS
2013
link
SME
A semantic matching energy function for learning with multi-relational data
Machine Learning
2014
link
NAM
Probabilistic reasoning via deep learning: Neural association models
arXiv
2016
link
ConvE
Convolutional 2D knowledge graph embeddings
AAAI
2018
link
ConvKB
A novel embedding model for knowledge base completion based on convolutional neural network
NAACL
2018
link
GNN Survey
A comprehensive survey on graph neural networks
IEEE TNNLS
2021
link
R-GCN
Modeling relational data with graph convolutional networks
ESWC
2018
Link
SACN
End-to-end structure-aware convolutional networks for knowledge base completion
AAAI
2019
link
KBGAT
Learning attention-based embeddings for relation prediction in knowledge graphs
ACL
2019
link
KE-GCN
Knowledge embedding based graph convolutional network
The Web Conference
2021
link
Model
Title
Conference/Journal
Year
Paper
KG-BERT
Modeling relational data with graph convolutional networks
ESWC
2018
Link
R-MeN
A relational memory-based embedding model for triple classification and search personalization
ACL
2021
link
CoKE
CoKE: Contextualized knowledge graph embedding
arXiv
2019
link
HittER
HittER: Hierarchical transformers for knowledge graph embeddings
EMNLP
2021
link
GenKGC
From discrimination to generation: Knowledge graph completion with generative transformer
WWW
2022
link
iHT
Pre-training transformers for knowledge graph completion
arXiv
2023
link
SimKGC
SimKGC: Simple contrastive knowledge graph completion with pre-trained language models
ACL
2022
link
StAR
Structure-augmented text representation learning for efficient knowledge graph completion
WWW
2021
link
KoPA
Making large language models perform better in knowledge graph completion
arXiv
2023
link
KICGPT
KICGPT: Large language model with knowledge in context for knowledge graph completion
EMNLP
2023
link
Relphormer
Relphormer: Relational graph transformer for knowledge graph representations
Neurocomputing
2024
link
LGKGR
LGKGR: A knowledge graph reasoning model using LLMs augmented GNNs
Neurocomputing
2025
Link
⬆️
Ontology-Enhanced KGE Models
Model
Title
Conference/Journal
Year
Paper
JOIE
Universal representation learning of knowledge bases by jointly embedding instances and ontological concepts
KDD
2019
Link
Nickel et al.
Factorizing YAGO: Scalable machine learning for linked data
WWW
2012
link
CISS
Embedding two-view knowledge graphs with class inheritance and structural similarity
KDD
2024
link
Wang et al.
An ontology-enhanced knowledge graph embedding method
ICCPR
2024
link
Concept2Box
Concept2Box: Joint geometric embeddings for learning two-view knowledge graphs
ACL
2023
link
CAKE
CAKE: A scalable commonsense-aware framework for multi-view knowledge graph completion
ACL
2022
link
SSE
Semantically smooth knowledge graph embedding
ACL
2015
link
TKRL
Representation learning of knowledge graphs with hierarchical types
IJCAI
2016
link
TransET
TransET: Knowledge graph embedding with entity types
Electronics
2021
link
AutoETER
AutoETER: Automated entity type representation for knowledge graph embedding
EMNLP
2020
link
Model
Title
Conference/Journal
Year
Paper
Path-RNN
Compositional vector space models for knowledge base completion
ACL
2015
link
PTransE
Modeling relation paths for representation learning of knowledge bases
EMNLP
2015
Link
PRN
A path-based relation networks model for knowledge graph completion
Expert Systems with Applications
2021
link
OPTransE
Representation learning with ordered relation paths for knowledge graph completion
EMNLP-IJCNLP
2019
link
TransE&RW
Modeling relation paths for knowledge base completion via joint adversarial training
Knowledge Based Systems
2020
link
HARPA
HARPA: hierarchical attention with relation paths for knowledge graph embedding adversarial learning
Data Mining and Knowledge Discovery
2023
link
RPJE
Rule-guided compositional representation learning on knowledge graphs
AAAI
2020
link
PARL
Attention-aware path-based relation extraction for medical knowledge graph
Smart Computing and Communication
2017
link
Das et al.
Chains of reasoning over entities, relations, and text using recurrent neural networks
EACL
2017
link
Jiang et al.
Attentive path combination for knowledge graph completion
Machine Learning Research
2017
link
CPConvKE
A confidence-aware and path-enhanced convolutional neural network embedding framework on noisy knowledge graph
Neurocomputing
2023
link
PaSKoGE
Path-specific knowledge graph embedding
Knowledge-based Systems
2018
link
Jagvaral et al.
Path-based reasoning approach for knowledge graph completion using CNN-BiLSTM with attention mechanism
Expert Systems with Applications
2020
link
PathCon
Relational message passing for knowledge graph completion
KDD
2021
link
PTrustE
PTrustE: A high-accuracy knowledge graph noise detection method based on path trustworthiness and triple embedding
Knowledge-based Systems
2022
link
TAPR
Modeling relation paths for knowledge graph completion
IEEE TKDE
2021
link
Niu et al.
Joint semantics and data-driven path representation for knowledge graph reasoning
Neurocomputing
2022
link
⬆️
Negative Sampling for KGE
The illustration of six types of negative sampling strategies
Model
Title
Conference/Journal
Year
Paper
Local Closed-World Assumption
Knowledge Vault: A web scale approach to probabilistic knowledge fusion
KDD
2014
link
NS Survey
Negative sampling in knowledge graph representation learning: A review
arXiv
2023
link
Uniform Sampling
Knowledge graph embedding by translating on hyperplanes
AAAI
2014
link
KBGAN
KBGAN: Adversarial learning for knowledge graph embeddings
NAACL
2018
Link
Self-Adv
RotatE: Knowledge graph embedding by relational rotation in complex space
ICLR
2019
link
Batch NS
Pytorch-BigGraph: A large scale graph embedding system
Machine Learning and Systems
2019
link
Bernoulli NS
An interpretable knowledge transfer model for knowledge base completion
ACL
2017
link
Zhang et al.
A novel negative sample generating method for knowledge graph embedding
EWSN
2019
link
SparseNSG
A novel negative sampling based on frequency of relational association entities for knowledge graph embedding
Journal of Web Engineering
2021
link
IGAN
Incorporating GAN for negative sampling in knowledge representation learning
AAAI
2018
link
GraphGAN
GraphGAN: Graph representation learning with generative adversarial nets
AAAI
2018
link
KSGAN
A knowledge selective adversarial network for link prediction in knowledge graph
NLPCC
2019
link
RUGA
Improving knowledge graph completion using soft rules and adversarial learning
Chinese Journal of Electronics
2021
link
LAS
Adversarial knowledge representation learning without external model
IEEE Access
2019
link
ASA
Relation-aware graph attention model with adaptive self-adversarial training
AAAI
2021
link
AN
Knowledge graph embedding based on adaptive negative sampling
ICPSEE
2019
link
EANS
Entity aware negative sampling with auxiliary loss of false negative prediction for knowledge graph embedding
arXiv
2022
link
Truncated NS
Fusing attribute character embeddings with truncated negative sampling for entity alignment
Electronics
2023
link
DNS
Distributional negative sampling for knowledge base completion
arXiv
2019
link
ESNS
Entity similarity-based negative sampling for knowledge graph embedding
PRICAI
2022
Link
RCWC
KGBoost: A classification-based knowledge base completion method with negative sampling
Pattern Recognition Letters
2022
link
Conditional Sampling
Conditional constraints for knowledge graph embeddings
DL4KG
2020
link
LEMON
LEMON: LanguagE MOdel for negative sampling of knowledge graph embeddings
arXiv preprint
2022
Link
NSCaching
NSCaching: Simple and efficient negative sampling for knowledge graph embedding
ICDE
2019
Link
MDNcaching
MDNcaching: A strategy to generate quality negatives for knowledge graph embedding
IEA/AIE
2022
Link
Op-Trans
Op-Trans: An optimization framework for negative sampling and triplet-mapping properties in knowledge graph embedding
Applied Sciences
2023
Link
NS-KGE
Efficient non-sampling knowledge graph embedding
The Web Conference
2021
Link
⬆️
Open-Source Library for KGE
Library
Implementation
Key Features
GitHub Repository
OpenKE
Pytorch, TensorFlow, C++
Efficiently implements fundamental operations such as data loading, negative sampling, and performance evaluation using C++ for high performance.
https://github.com/thunlp/OpenKE
AmpliGraph
TensorFlow
Provides a Keras-style API with improved efficiency over OpenKE.
https://github.com/Accenture/AmpliGraph
torchKGE
Pytorch
Achieves twice the efficiency of OpenKE and five times that of AmpliGraph.
https://github.com/torchkge-team/torchkge
LibKGE
Pytorch
Enables direct configuration of hyperparameters and model settings via configuration files.
https://github.com/uma-pi1/kge
KB2E
C++
One of the earliest KGE libraries and the predecessor of OpenKE.
https://github.com/thunlp/KB2E
scikit-kge
Python
Implements multiple classical KGE models and supports a novel negative sampling strategy.
https://github.com/mnick/scikit-kge
NeuralKG
Pytorch
Integrates KGE techniques with graph neural networks (GNNs) and rule-based reasoning models.
https://github.com/zjukg/NeuralKG
PyKEEN
Pytorch
Offers 37 datasets, 40 KGE models, 15 loss functions, 6 regularization mechanisms, and 3 negative sampling strategies.
https://github.com/pykeen/pykeen
Pykg2vec
Pytorch, TensorFlow
Supports automated hyperparameter tuning, exports KG embeddings in TSV or RDF formats, and provides visualization for performance evaluation.
https://github.com/Sujit-O/pykg2vec
μKG
Pytorch, TensorFlow
Supports multi-process execution and GPU-accelerated computation, making it well-suited for large-scale KGs.
https://github.com/nju-websoft/muKG
DGL-KE
Pytorch, MXNet
Optimized for execution on CPU and GPU clusters, offering high scalability for large-scale KGs.
https://github.com/awslabs/dgl-ke
GraphVite
Pytorch
Provides efficient large-scale embedding learning, supports visualization of graph data, and enables multi-processing and GPU parallelization.
https://github.com/DeepGraphLearning/graphvite
PBG
Pytorch
Designed for distributed training, capable of handling KGs with billions of entities and trillions of edges.
https://github.com/facebookresearch/PyTorch-BigGraph
⬆️
Logic Rule-based KGR Model
Model
Title
Conference/Journal
Year
Paper
FOIL
Learning logical definitions from relations
Machine Learning
1990
link
MDIE
Inverse entailment and progol
New Generation Computing
1995
link
Inspire
Best-effort inductive logic programming via fine-grained cost-based hypothesis generation
Machine Learning
2018
link
Neural-Num-LP
Differentiable learning of numerical rules in knowledge graphs
ICLR
2020
link
AMIE+
Fast rule mining in ontological knowledge bases with AMIE+
VLDB Journal
2015
link
ScaLeKB
ScaLeKB: Scalable learning and inference over large knowledge bases
VLDB Journal
2016
link
RDF2rules
RDF2Rules: Learning rules from RDF knowledge bases by mining frequent predicate cycles
arXiv
2015
link
SWARM
SWARM: An approach for mining semantic association rules from semantic web data
PRICAI
2016
link
Rudik
Rudik: Rule discovery in knowledge bases
PVLDB
2018
link
RuLES
Rule learning from knowledge graphs guided by embedding models
ESWC
2018
link
Evoda
Rule learning over knowledge graphs with genetic logic programming
ICDE
2022
link
NeuralLP
Differentiable learning of logical rules for knowledge base reasoning
NeurIPS
2017
link
DRUM
DRUM: End-to-end differentiable rule mining on knowledge graphs
NeurIPS
2019
link
RLvLR
An embedding-based approach to rule learning in knowledge graphs
IEEE TKDE
2019
link
RNNLogic
RNNLogic: learning logic rules for reasoning on knowledge graphs
ICLR
2021
link
RARL
Relatedness and TBox-driven rule learning in large knowledge bases
AAAI
2020
link
Ruleformer
Ruleformer: context-aware rule mining over knowledge graph
COLING
2022
link
Ott et al.
Rule-based knowledge graph completion with canonical models
CIKM
2023
link
Model
Title
Conference/Journal
Year
Paper
KALE
Jointly embedding knowledge graphs and logical rules
EMNLP
2016
link
RUGE
Knowledge graph embedding with iterative guidance from soft rules
AAAI
2018
link
RulE
RulE: Knowledge graph reasoning with rule embedding
Findings of ACL
2024
link
RPJE
Rule-guided compositional representation learning on knowledge graphs
AAAI
2020
link
IterE
Iteratively learning embeddings and rules for knowledge graph reasoning
WWW
2019
link
UniKER
UniKER: A unified framework for combining embedding and definite Horn rule reasoning for knowledge graph inference
EMNLP
2021
link
EngineKG
Perform like an engine: A closed-loop neural-symbolic learning framework for knowledge graph inference
COLING
2022
link
Taxonomy of static single-step KGR approaches
⬆️
Model
Title
Conference/Journal
Year
Paper
PRA
Relational retrieval using a combination of path-constrained random walks
Machine Learning 2010
link
Lao et al. 1
Random walk inference and learning in a large scale knowledge base
EMNLP
2011
link
Lao et al. 2
Reading the web with learned syntactic-semantic inference rules
EMNLP
2012
link
Gardner et al.
Improving learning and inference in a large knowledge-base using latent syntactic cues
EMNLP
2013
link
CPRA
Knowledge base completion via coupled path ranking
ACL
2016
link
C-PR
Context-aware path ranking for knowledge base completion
IJCAI
2017
link
A*Net
A*Net: a scalable path-based reasoning approach for knowledge graphs
NeurIPS
2024
link
SFE
Efficient and expressive knowledge base completion using subgraph feature extraction
EMNLP
2015
link
PathCon
Relational message passing for knowledge graph completion
KDD
2021
link
Reinforcement Learning-based Model
Model
Title
Conference/Journal
Year
Paper
DeepPath
DeepPath: a reinforcement learning method for knowledge graph reasoning
EMNLP
2017
link
MINERVA
Go for a walk and arrive at the answer: Reasoning over paths in knowledge bases using reinforcement learning
ICLR
2018
link
DIVA
Variational knowledge graph reasoning
NAACL
2018
link
MultiHopKG
Multi-hop knowledge graph reasoning with reward shaping
EMNLP
2018
link
M-Walk
M-Walk: Learning to walk over graphs using monte carlo tree search
NeurIPS
2018
link
RARL
Rule-aware reinforcement learning for knowledge graph reasoning
ACL-IJCNLP
2021
link
AttnPath
Incorporating graph attention mechanism into knowledge graph reasoning based on deep reinforcement learning
EMNLP-IJCNLP
2019
link
DIVINE
DIVINE: A generative adversarial imitation learning framework for knowledge graph reasoning
EMNLP-IJCNLP
2019
link
LLM-based Multi-Step KGR Model
Model
Title
Conference/Journal
Year
Paper
KG&LLM Survey
Unifying large language models and knowledge graphs: A roadmap
IEEE TKDE
2024
link
StructGPT
StructGPT: A general framework for large language model to reason over structured data
EMNLP
2023
link
KSL
Knowledge solver: Teaching LLMs to search for domain knowledge from knowledge graphs
arXiv
2023
link
KD-CoT
Knowledge-driven CoT: Exploring faithful reasoning in LLMs for knowledge-intensive question answering
arXiv
2023
link
ToG
Think-on-Graph: Deep and responsible reasoning of large language model on knowledge graph
ICLR
2024
link
KnowledgeNavigator
KnowledgeNavigator: Leveraging large language models for enhanced reasoning over knowledge graph
Complex Intell. Syst.
2024
link
Nguyen et al.
Direct evaluation of chain-of-thought in multi-hop reasoning with knowledge graphs
Findings of ACL
2024
link
KG-Agent
KG-Agent: An efficient autonomous agent framework for complex reasoning over knowledge graph
arXiv
2024
link
AgentTuning
AgentTuning: Enabling generalized agent abilities for LLMs
Findings of ACL
2024
link
Glam
Glam: Fine-tuning large language models for domain knowledge graph alignment via neighborhood partitioning and generative subgraph encoding
AAAI Symposium
2024
link
Taxonomy of static multi-step KGR approaches
⬆️
The illustration of the dynamic KGR task
Model
Title
Conference/Journal
Year
Paper
DKGE
Efficiently embedding dynamic knowledge graphs
Knowl.-Based Syst.
2022
link
PuTransE
Non-parametric estimation of multiple embeddings for link prediction on dynamic knowledge graphs
AAAI
2017
link
Liu et al.
Heuristic-driven, type-specific embedding in parallel spaces for enhancing knowledge graph reasoning
ICASSP
2024
link
ABIE
Anchors-based incremental embedding for growing knowledge graphs
TKDE
2023
link
CKGE
Towards continual knowledge graph embedding via incremental distillation
AAAI
2024
link
LKGE
Lifelong embedding learning and transfer for growing knowledge graphs
AAAI
2023
link
AIR
AIR: Adaptive incremental embedding updating for dynamic knowledge graphs
DASFAA
2023
link
TIE
TIE: A framework for embedding-based incremental temporal knowledge graph completion
SIGIR
2021
link
RotatH
Incremental update of knowledge graph embedding by rotating on hyperplanes
ICWS
2021
link
MMRotatH
Knowledge graph incremental embedding for unseen modalities
Knowl. Inf. Syst.
2023
link
DKGE
Efficiently embedding dynamic knowledge graphs
Knowl.-Based Syst.
2022
link
Navi
Dynamic knowledge graph embeddings via local embedding reconstructions
ESWC (Satellite)
2022
link
UOKE
Online updates of knowledge graph embedding
Complex Networks X
2021
link
KGCR
Temporal knowledge graph incremental construction model for recommendation
APWeb-WAIM
2020
link
⬆️
Time Embedding-based Models
Model
Title
Conference/Journal
Year
Paper
TA-TransE
Learning sequence encoders for temporal knowledge graph completion
EMNLP
2018
link
HyTE
HyTE: Hyperplane-based temporally aware knowledge graph embedding
EMNLP
2018
link
TTransE
Deriving validity time in knowledge graph
WWW
2018
link
TERO
TeRo: A time-aware knowledge graph embedding via temporal rotation
COLING
2020
link
TDistMult
Embedding models for episodic knowledge graphs
JWS
2019
link
TComplEx
Tensor decompositions for temporal knowledge base completion
ICLR
2020
link
SimplE
Diachronic embedding for temporal knowledge graph completion
AAAI
2020
link
ATiSE
Temporal KGC based on time series gaussian embedding
ISWC
2020
link
TARGAT
TARGAT: A time-aware relational graph attention model
IEEE/ACM TASLP
2023
link
LCGE
Logic and commonsense-guided TKGC
AAAI
2023
link
Evolution Learning-based Models
Model
Title
Conference/Journal
Year
Paper
Know-Evolve
Know-evolve: deep temporal reasoning for dynamic knowledge graphs
ICML
2017
link
RE-NET
Recurrent event network: autoregressive structure inference over temporal knowledge graphs
EMNLP
2020
link
EvolveRGCN
EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs
AAAI
2020
link
CyGNet
Learning from history: modeling temporal knowledge graphs with sequential copy-generation networks
AAAI
2021
link
CluSTeR
Search from history and reason for future: two-stage reasoning on temporal knowledge graphs
ACL
2021
link
Model
Title
Conference/Journal
Year
Paper
StreamLearner
Learning temporal rules from knowledge graph streams
AAAI Spring Symposium
2019
link
Tlogic
Tlogic: temporal logical rules for explainable link forecasting on temporal knowledge graphs
AAAI
2022
link
TILP
TILP: differentiable learning of temporal logical rules on knowledge graphs
ICLR
2023
link
TEILP
TEILP: time prediction over knowledge graphs via logical reasoning
AAAI
2024
link
NeuSTIP
NeuSTIP: a neuro-symbolic model for link and time prediction in temporal knowledge graphs
EMNLP
2023
link
Multi-step Temporal KGR Model
Model
Title
Conference/Journal
Year
Paper
xERTE
Explainable subgraph reasoning for forecasting on temporal knowledge graphs
ICLR
2021
link
CluSTeR
Search from history and reason for future: two-stage reasoning on temporal knowledge graphs
ACL
2021
link
TPath
Multi-hop reasoning over paths in temporal knowledge graphs using reinforcement learning
Applied Soft Computing
2021
link
T-GAP
Learning to walk across time for interpretable temporal knowledge graph completion
KDD
2021
link
RTTI
Reinforcement learning with time intervals for temporal knowledge graph reasoning
Information Systems
2024
link
TITer
TimeTraveler: Reinforcement learning for temporal knowledge graph forecasting
EMNLP
2021
link
LLM-based Temporal KGR Model
Model
Title
Conference/Journal
Year
Paper
PPT
Pre-trained language model with prompts for temporal knowledge graph completion
Findings of ACL
2023
link
ECOLA
ECOLA: Enhancing temporal knowledge embeddings with contextualized language representations
Findings of ACL
2023
link
SToKE
Learning joint structural and temporal contextualized knowledge embeddings for temporal knowledge graph completion
Findings of ACL
2023
link
NeoX
Temporal knowledge graph forecasting without knowledge using in-context learning
EMNLP
2023
link
CSProm-KG
Dipping PLMs Sauce: Bridging structure and text for effective knowledge graph completion via conditional soft prompting
Findings of ACL
2023
link
zrLLM
zrLLM: Zero-shot relational learning on temporal knowledge graphs with large language models
NAACL
2024
link
Taxonomy of dynamic KGR approaches
⬆️
Multi-Modal Embedding-based Model
Model
Title
Conference/Journal
Year
Paper
Wang et al.
Knowledge graph and text jointly embedding
EMNLP
2014
link
DKRL
Representation learning of knowledge graphs with entity descriptions
AAAI
2016
link
TEKE
Text-enhanced representation learning for knowledge graph
IJCAI
2016
link
KG-BERT
Modeling relational data with graph convolutional networks
ESWC
2018
Link
SimKGC
SimKGC: Simple contrastive knowledge graph completion with pre-trained language models
ACL
2022
link
StAR
Structure-augmented text representation learning for efficient knowledge graph completion
WWW
2021
link
IKRL
Image-embodied knowledge representation learning
IJCAI
2017
link
TransAE
Multimodal data enhanced representation learning for knowledge graphs
IJCNN
2019
link
RSME
Is visual context really helpful for knowledge graph? A representation learning perspective
ACM MM
2021
link
OTKGE
OTKGE: multi-modal knowledge graph embeddings via optimal transport
NeurIPS
2024
link
HRGAT
Hyper-node relational graph attention network for multi-modal knowledge graph completion
ACM TOMM
2023
link
MKBE
Embedding multimodal relational data for knowledge base completion
EMNLP
2018
link
MMKGR
MMKGR: multi-hop multi-modal knowledge graph reasoning
ICDE
2022
link
NativE
NativE: Multi-modal knowledge graph completion in the wild
SIGIR
2024
link
TransFusion
TransFusion: Multi-modal fusion for video tag inference via translation-based knowledge embedding
ACM MM
2021
link
MoSE
MoSE: modality split and ensemble for multimodal knowledge graph completion
EMNLP
2022
link
IMF
IMF: interactive multimodal fusion model for link prediction
WWW
2023
link
MMRNS
Relation-enhanced negative sampling for multimodal knowledge graph completion
ACM MM
2022
link
MANS
Modality-aware negative sampling for multi-modal knowledge graph embedding
IJCNN
2023
link
DHNS
Diffusion-based Hierarchical Negative Sampling for Multimodal Knowledge Graph Completion
arXiv
2025
link
Model
Title
Conference/Journal
Year
Paper
VL-BERT
VL-BERT: pre-training of generic visual-linguistic representations
ICLR
2019
link
Visualbert
Visualbert: A simple and performant baseline for vision and language
arXiv
2019
link
Unicoder-VL
Unicoder-VL: A universal encoder for vision and language by cross-modal pre-training
AAAI
2020
link
UNITER
UNITER: universal image-text representation learning
SpringerLink
2020
link
LXMERT
LXMERT: learning cross-modality encoder representations from transformers
EMNLP-IJCNLP
2019
link
ViLBERT
ViLBERT: pretraining task-agnostic visiolinguistic representations for vision-and-language tasks
NeurIPS
2019
link
MKGformer
Hybrid transformer with multi-level fusion for multimodal knowledge graph completion
SIGIR
2022
link
VISTA
VISTA: visual-textual knowledge graph representation learning
EMNLP Findings
2023
link
SGMPT
Structure guided multi-modal pre-trained transformer for knowledge graph reasoning
arXiv
2023
link
MMKRL
MMKRL: a robust embedding approach for multi-modal knowledge graph representation learning
Applied Intelligence
2022
link
KoPA
Mixture of modality knowledge experts for robust multi-modal knowledge graph completion
arXiv
2024
link
Taxonomy of multi-modal KGR approaches
⬆️
The illustration of few-shot KGR in the 3-shot setting
Metric Learning-based Model
Model
Title
Conference/Journal
Year
Paper
GMatching
One-shot relational learning for knowledge graphs
EMNLP
2018
link
FSRL
Few-shot knowledge graph completion
AAAI
2020
link
FAAN
Adaptive attentional network for few-shot knowledge graph completion
EMNLP
2020
link
TransAM
Exploring entity interactions for few-shot relation learning (student abstract)
AAAI
2022
link
FRL-KGC
Few-shot knowledge graph completion model based on relation learning
Applied Sciences
2023
link
HMNet
HMNet: hybrid matching network for few-shot link prediction
DASFAA
2021
link
Metap
Metap: meta pattern learning for one-shot knowledge graph completion
SIGIR
2021
link
Meta-Learning-based Model
Model
Title
Conference/Journal
Year
Paper
MetaR
Meta relational learning for few-shot link prediction in knowledge graphs
EMNLP-IJCNLP
2019
link
GANA
Relational learning with gated and attentive neighbor aggregator for few-shot knowledge graph completion
SIGIR
2021
link
Meta-iKG
Subgraph-aware few-shot inductive link prediction via meta-learning
IEEE TKDE
2022
link
SMetaR
Simple and effective meta relational learning for few-shot knowledge graph completion
Optimization and Engineering
2024
link
HiRe
Hierarchical relational learning for few-shot knowledge graph completion
arXiv
2022
link
MTRN
Task-related network based on meta-learning for few-shot knowledge graph completion
Applied Intelligence
2024
link
Auxiliary Information-Enhanced Model
Model
Title
Conference/Journal
Year
Paper
TCVAE
Tackling long-tailed relations and uncommon entities in knowledge graph completion
EMNLP-IJCNLP
2019
link
ZSGAN
Generative adversarial zero-shot relational learning for knowledge graphs
AAAI
2020
link
HAPZSL
HAPZSL: a hybrid attention prototype network for knowledge graph zero-shot relational learning
Neurocomputing
2022
link
OntoZSL
OntoZSL: ontology-enhanced zero-shot learning
WWW
2021
link
DOZSL
Disentangled ontology embedding for zero-shot learning
IJCAI
2018
link
DMoG
Decoupling mixture-of-graphs: unseen relational learning for knowledge graph completion by fusing ontology and textual experts
COLING
2022
link
P-INT
P-INT: a path-based interaction model for few-shot knowledge graph completion
EMNLP Findings
2021
link
EPIRL
Enhancing path information with reinforcement learning for few-shot knowledge graph completion
ICPADS
2023
link
⬆️
Multi-Step Few-Shot KGR Model
Model
Title
Conference/Journal
Year
Paper
Meta-KGR
Adapting meta knowledge graph information for multi-hop reasoning over few-shot relations
EMNLP-IJCNLP
2019
link
FIRE
Few-shot multi-hop relation reasoning over knowledge bases
EMNLP
2020
link
ADK-KG
Adapting distilled knowledge for few-shot relation reasoning over knowledge graphs
SDM
2022
link
THML
When hardness makes a difference: multi-hop knowledge graph reasoning over few-shot relations
CIKM
2021
link
Temporal Few-Shot KGR Model
Model
Title
Conference/Journal
Year
Paper
FTMO
Few-shot temporal knowledge graph completion based on meta-optimization
Complex Intell. Syst.
2023
link
TFSC
Few-shot link prediction for temporal knowledge graphs based on time-aware translation and attention mechanism
Neural Networks
2023
link
TR-Match
Temporal-relational matching network for few-shot temporal knowledge graph completion
DASFAA 2023
2023
link
FTMF
FTMF: few-shot temporal knowledge graph completion based on meta-optimization and fault-tolerant mechanism
World Wide Web
2023
link
MetaRT
Few-shot link prediction with meta-learning for temporal knowledge graphs
J. Comput. Des. Eng.
2023
link
MetaTKGR
Learning to sample and aggregate: few-shot reasoning over temporal knowledge graphs
NeurIPS
2022
link
FITCARL
Improving few-shot inductive learning on temporal knowledge graphs using confidence-augmented reinforcement learning
Machine Learning and Knowledge Discovery in Databases
2023
link
Taxonomy of few-shot KGR approaches
⬆️
The illustration of inductive KGR
Model
Title
Conference/Journal
Year
Paper
GraphSAGE
Inductive representation learning on large graphs
NeurIPS
2017
link
RuleNet
Missing-edge aware knowledge graph inductive inference through dual graph learning and traversing
Expert Systems with Applications
2023
link
CBGNN
Cycle representation learning for inductive relation prediction
ICML
2022
link
RED-GNN
Knowledge graph reasoning with relational digraph
ACM Web Conference
2022
link
VN
VN network: embedding newly emerging entities with virtual neighbors
CIKM
2020
link
ARGCN
Inductive knowledge graph reasoning for multi-batch emerging entities
CIKM
2022
link
ELPE
Explainable link prediction for emerging entities in knowledge graphs
ISWC
2020
link
Model
Title
Conference/Journal
Year
Paper
MEAN
Knowledge transfer for out-of-knowledge-base entities: a graph neural network approach
IJCAI
2017
link
NBFNet
Neural Bellman-Ford networks: a general graph neural network framework for link prediction
NeurIPS
2024
link
GraIL
Inductive relation prediction by subgraph reasoning
ICML
2020
link
PathCon
Relational message passing for knowledge graph completion
KDD
2021
link
SNRI
Subgraph neighboring relations infomax for inductive link prediction on knowledge graphs
IJCAI
2022
link
REPORT
Inductive relation prediction from relational paths and context with hierarchical transformers
ICASSP
2023
link
LogCo
Inductive relation prediction with logical reasoning using contrastive representations
EMNLP
2022
link
RPC-IR
Learning first-order rules with relational path contrast for inductive relation reasoning
arXiv
2021
link
TACT
Topology-aware correlations between relations for inductive link prediction in knowledge graphs
AAAI
2021
link
NRTG
Entity representation by neighboring relations topology for inductive relation prediction
PRICAI
2022
link
CoMPILE
Communicative message passing for inductive relation reasoning
AAAI
2021
link
LCILP
Locality-aware subgraphs for inductive link prediction in knowledge graphs
Pattern Recognition Letters
2023
link
ReCoLe
Relation-dependent contrastive learning with cluster sampling for inductive relation prediction
Neurocomputing
2024
link
DEKG-ILP
Disconnected emerging knowledge graph oriented inductive link prediction
ICDE
2023
link
CG-AGG
Exploring relational semantics for inductive knowledge graph completion
AAAI
2022
link
FCLEntity-Att
Attention-based aggregation graph networks for knowledge graph information transfer
PAKDD
2020
link
SAGNN
Open-world relationship prediction
ICTAI
2020
link
LAN
Logic attention based neighborhood aggregation for inductive knowledge graph embedding
AAAI
2019
link
SLAN
SLAN: similarity-aware aggregation network for embedding out-of-knowledge-graph entities
Neurocomputing
2022
link
ARP
Attention-based relation prediction of knowledge graph by incorporating graph and context features
WISE
2022
link
TransNS
Open knowledge graph representation learning based on neighbors and semantic affinity
Journal of Computer Research and Development
2019
link
⬆️
Multimodal-Enhanced Model
Model
Title
Conference/Journal
Year
Paper
CatE
Ontological concept structure aware knowledge transfer for inductive knowledge graph embedding
IJCNN
2021
link
DKRL
Representation learning of knowledge graphs with entity descriptions
AAAI
2016
link
OWE
An open-world extension to knowledge graph completion models
AAAI
2019
link
WOWE
Weighted aggregator for the open-world knowledge graph completion
CCIS
2020
link
Caps-OWKG
Caps-OWKG: a capsule network model for open-world knowledge graph
Int. J. Mach. Learn. & Cyber.
2021
link
OWE-MRC
Extracting short entity descriptions for open-world extension to knowledge graph completion models
Advances in Knowledge Science and Engineering
2021
link
OWE-RST
Relation specific transformations for open world knowledge graph completion
TextGraphs @ ACL
2020
link
EmReCo
Embeddings based on relation-specific constraints for open world knowledge graph completion
Applied Intelligence
2023
link
ConMask
Open-world knowledge graph completion
AAAI
2018
link
SDT
SDT: an integrated model for open-world knowledge graph reasoning
Expert Systems with Applications
2020
link
Bi-Link
Bi-Link: bridging inductive link predictions from text via contrastive learning of transformers and prompts
arXiv
2022
link
RAILD
RAILD: towards leveraging relation features for inductive link prediction in knowledge graphs
IJCKG
2023
link
DMoG
Decoupling mixture-of-graphs: unseen relational learning for knowledge graph completion by fusing ontology and textual experts
COLING
2022
link
BERTRL
Inductive relation prediction by BERT
AAAI
2022
link
InductivE
Inductive learning on commonsense knowledge graph completion
IJCNN
2021
link
FITCARL
Improving few-shot inductive learning on temporal knowledge graphs using confidence-augmented reinforcement learning
Machine Learning and Knowledge Discovery in Databases
2023
link
TITer
TimeTraveler: Reinforcement learning for temporal knowledge graph forecasting
EMNLP
2021
link
MetaTKGR
Learning to sample and aggregate: few-shot reasoning over temporal knowledge graphs
NeurIPS
2022
link
FILT
Few-shot inductive learning on temporal knowledge graphs using concept-aware information
AKBC
2022
link
Taxonomy of inductive KGR approaches
⬆️
Datasets for Static KGR Tasks
Dataset
#Entities
#Relations
#Training Triples
#Valid Triples
#Test Triples
Paper Link
Countries
271
2
1,110
24
24
link
Kinship
104
25
8,544
1,068
1,074
link
FB13
75,043
13
316,232
11,816
47,464
link
FB122
9,738
122
91,638
9,595
11,243
link
FB15K
14,951
1,345
483,142
50,000
59,071
link
FB15K237
14,505
237
272,115
17,535
20,466
link
FB20K
19,923
1,452
378,072
89,040
90,143
link
FB5M
5,385,322
1,192
19,193,556
50,000
50,000
link
WN11
38,588
11
110,361
5,212
21,035
link
WN18
40,943
18
141,442
5,000
5,000
link
WN18RR
40,559
11
86,835
2,924
2,924
link
YAGO3-10
123,143
37
1,079,040
4,978
4,982
link
YAGO37
123,189
37
420,623
50,000
50,000
link
NELL-995
75,492
200
126,176
5,000
5,000
link
Datasets for Dynamic KGR Tasks
Dataset
#Entities
#Relations
Temporal
#Training
#Valid
#Test
Paper Link
GDELT
7,691
240
Timestemp
1,033,270
238,765
305,241
link
ICEWS14
6,738
235
Timestemp
118,766
14,859
14,756
link
ICEWS05-15
10,488
251
Timestemp
386,962
46,092
46,275
link
Wikidata12k
12,554
24
Time Interval
2,735,685
341,961
341,961
link
YAGO11k
10,623
10
Time Interval
161,540
19,523
20,026
link
YAGO15k
15,403
34
Time Interval
110,441
13,815
13,800
link
Datasets for Multi-modal KGR Tasks
Dataset
#Entities
#Relations
Modality
#Training
#Valid
#Test
Paper Link
FB-IMG-TXT
11,757
1,231
Image+Text
285,850
34,863
29,580
link
FB15K237-IMG
14,541
237
Image
272,115
17,535
20,466
link
WN9-IMG-TXT
6,555
9
Image+Text
11,741
1,319
1,337
link
WN18-IMG
40,943
18
Image
141,442
5,000
5,000
link
MKG-Wikipedia
15,000
169
Image
34,196
4,274
4,276
link
MKG-YAGO
15,000
28
Image
21,310
2,663
2,665
link
TIVA
11,858
16
Video
20,071
2,000
2,000
link
Datasets for Few-shot KGR Tasks
Dataset
#Entities
#Relations
#Triples
#Training/Valid/Test Splits
Paper Link
NELL-One
68,545
358
181,109
51/5/1
link
Wiki-One
4,868,244
822
5,859,240
133/16/34
link
FB15K-One
14,541
231
281,624
75/11/33
link
Datasets for Inductive KGR Tasks
Dataset
Version
Training/Test Set
#Entities
#Relations
#Triples
Paper Link
FB15K237
v1
Train
2,000
183
5,226
link
Test
1,500
146
2,404
v2
Train
3,000
203
12,085
Test
2,000
176
5,092
v3
Train
4,000
218
22,394
Test
3,000
187
9,137
v4
Train
5,000
222
33,916
Test
3,500
204
14,554
WN18RR
v1
Train
2,746
9
6,678
link
Test
922
9
1,991
v2
Train
6,954
10
18,968
Test
2,923
10
4,863
v3
Train
12,078
11
32,150
Test
5,084
11
7,470
v4
Train
3,861
9
9,842
Test
7,208
9
15,157
NELL-995
v1
Train
10,915
14
5,540
link
Test
225
14
1,034
v2
Train
2,564
88
10,109
Test
4,937
79
5,521
v3
Train
4,647
142
20,117
Test
4,921
122
9,668
v4
Train
2,092
77
9,289
Test
3,294
61
8,520
Dataset
#Entities
#Relations
#Training Triples
#Test Triples
Paper Link
DBPedia50k
24,624
351
32,388
6,459
link
Wikidata5M
4,579,609
822
20,496,514
6,894
link
⬆️
Illustrative examples of the KGR technique applied to QA systems
Model
Title
Conference/Journal
Year
Paper
KBQA Survey
A survey: complex knowledge base question answering
IEEE ICICSE
2022
link
KEQA
Knowledge graph embedding based question answering
ACM WSDM
2019
link
TRL-KEQA
Question answering over knowledge base embeddings with triples representation learning
Neural Information Processing
2021
link
TransE-QA
Knowledge base question answering system based on knowledge graph representation learning
ACM ICIAI
2020
link
CAPKGQA
Complex question answering over incomplete knowledge graph as n-ary link prediction
IEEE IJCNN
2022
link
EmbedKGQA
Improving multi-hop question answering over knowledge graphs using knowledge base embeddings
ACL
2020
link
PKEEQA
Path-enhanced multi-relational question answering with knowledge graph embeddings
arXiv
2021
link
PA-KGQA
Path-aware multi-hop question answering over knowledge graph embedding
IEEE ICTAI
2022
link
HamQA
Hierarchy-aware multi-hop question answering over knowledge graphs
ACM Web Conference
2023
link
BRGNN
Query path generation via bidirectional reasoning for multihop question answering from knowledge bases
IEEE TCDS
2023
link
GRRN
Implicit relation inference with deep path extraction for commonsense question answering
Neural Processing Letters
2022
link
Li et al.
Translational relation embeddings for multi-hop knowledge base question answering
Web Semantics
2022
link
DSSAGN
Knowledge graph multi-hop question answering based on dependent syntactic semantic augmented graph networks
Electronics
2024
link
Jiao et al.
A relation embedding assistance networks for multi-hop question answering
ACM TALIP
2024
link
Zhou et al.
Marie and BERT – a knowledge graph embedding based question answering system for chemistry
ACS Omega
2023
link
CF-KGQA
Causality-aware enhanced model for multi-hop question answering over knowledge graphs
Knowledge-Based Systems
2022
link
TwiRGCN
TwiRGCN: Temporally Weighted Graph Convolution for Question Answering over Temporal Knowledge Graphs
EACL
2023
link
CRONKGQA
Question answering over temporal knowledge graphs
ACL-IJCNLP
2021
link
TempoQR
TempoQR: Temporal question reasoning over knowledge graphs
AAAI
2021
link
CTRN
An improving reasoning network for complex question answering over temporal knowledge graphs
Applied Intelligence
2022
link
EXAQT
Complex temporal question answering on knowledge graphs
ACM CIKM
2021
link
GATQR
Temporal knowledge graph question answering models enhanced with GAT
IEEE BigData
2023
link
Prog-TQA
Self-improvement programming for temporal knowledge graph question answering
LREC-COLING
2024
link
GenTKGQA
Two-stage generative question answering on temporal knowledge graph using large language models
ACL Findings
2024
link
⬆️
Model
Title
Conference/Journal
Year
Paper
KGCN
Knowledge graph convolutional networks for recommender systems
WWW
2019
link
KGNCF-RRN
Neural collaborative recommendation with knowledge graph
IEEE ICKG
2020
link
KGECF
Knowledge graph embedding based collaborative filtering
IEEE Access
2020
link
Survey
A review of explainable recommender systems utilizing knowledge graphs and reinforcement learning
IEEE Access
2024
link
PGPR
Reinforcement knowledge graph reasoning for explainable recommendation
SIGIR
2019
link
CogER
Cognition-aware knowledge graph reasoning for explainable recommendation
WSDM
2023
link
Hsu et al.
Explainable mutual fund recommendation system developed based on knowledge graph embeddings
Applied Intelligence
2022
link
Lee et al.
GCN-based explainable recommendation using a knowledge graph and a language model
IEEE BigData
2023
link
Markchom et al.
Explainable meta-path based recommender systems
ACM TORS
2023
link
Fu et al.
Fairness-aware explainable recommendation over knowledge graphs
SIGIR
2020
link
KRRL
Knowledge-aware reasoning with self-supervised reinforcement learning for explainable recommendation in MOOCs
Neural Computing and Applications
2024
link
Ryotaro et al.
An explainable recommendation framework based on an improved knowledge graph attention network with massive volumes of side information
Knowledge-Based Systems
2022
link
RippleNet
RippleNet: propagating user preferences on the knowledge graph for recommender systems
CIKM
2018
link
AKUPM
AKUPM: attention-enhanced knowledge-aware user preference model for recommendation
KDD
2019
link
RCoLM
Unifying task-oriented knowledge graph learning and recommendation
IEEE Access
2019
link
KGAT
KGAT: knowledge graph attention network for recommendation
KDD
2019
link
IntentGC
IntentGC: a scalable graph convolution framework fusing heterogeneous information for recommendation
KDD
2019
link
AKGE
Hierarchical attentive knowledge graph embedding for personalized recommendation
Electronic Commerce Research and Applications
2021
link
KPRN
Explainable reasoning over knowledge graphs for recommendation
AAAI
2019
link
⬆️
Visual Question Answering
Model
Title
Conference/Journal
Year
Paper
FVQA
FVQA: fact-based visual question answering
IEEE TPAMI
2018
link
Wang et al.
Explicit knowledge-based reasoning for visual question answering
IJCAI
2017
link
Graphhopper
Graphhopper: multi-hop scene graph reasoning for visual question answering
ISWC
2021
link
Hypergraph Transformer
Hypergraph transformer: weakly-supervised multi-hop reasoning for knowledge-based visual question answering
ACL
2022
link
CMRL
Cross-modality multiple relations learning for knowledge-based visual question answering
ACM TOMM
2024
link
KRISP
KRISP: Integrating implicit and symbolic knowledge for open-domain knowledge-based VQA
CVPR
2021
link
LLM+(KBret+SGret)
Find the gap: knowledge base reasoning for visual question answering
arXiv
2024
link
Model
Title
Conference/Journal
Year
Paper
KCR
Knowledge-aware cross-modal text-image retrieval for remote sensing images
IEEE TGRS
2022
link
MMRG
Multi-modal relational graph for cross-modal video moment retrieval
CVPR
2021
link
IRGR
Multiple instance relation graph reasoning for cross-modal hash retrieval
Knowledge-Based Systems
2022
link
Model
Title
Conference/Journal
Year
Paper
GB-Net
Bridging knowledge graphs to generate scene graphs
ECCV
2020
link
HiKER-SGG
HiKER-SGG: Hierarchical knowledge enhanced robust scene graph generation
CVPR
2024
link
CGR
Configurable graph reasoning for visual relationship detection
TNNLS
2022
link
COACHER
Zero-shot scene graph relation prediction through commonsense knowledge integration
ECML PKDD
2021
link
⬆️
Model
Title
Conference/Journal
Year
Paper
Zhu et al.
Multimodal reasoning based on knowledge graph embedding for specific diseases
Bioinformatics
2022
link
Chai et al.
Diagnosis method of thyroid disease combining knowledge graph and deep learning
IEEE Access
2020
link
SSI-DDI
SSI-DDI: substructure-substructure interactions for drug-drug interaction prediction
Brief. Bioinform.
2021
link
KGNN
KGNN: knowledge graph neural network for drug-drug interaction prediction
IJCAI
2020
link
SMR
SMR: medical knowledge graph embedding for safe medicine recommendation
Big Data Res.
2021
link
PharmKG
PharmKG: a dedicated knowledge graph benchmark for biomedical data mining
Brief. Bioinform.
2021
link
KG-Predict
KG-Predict: a knowledge graph computational framework for drug repurposing
J. Biomed. Inform.
2022
link
Model
Title
Conference/Journal
Year
Paper
OpenBG
Construction and applications of billion-scale pre-trained multimodal business knowledge graph
ICDE
2023
link
Zhang et al.
Knowledge graph embedding in e-commerce applications: attentive reasoning, explanations, and transferable rules
Int. Joint Conf. on Knowledge Graphs
2021
link
Yang et al.
Inferring substitutable and complementary products with knowledge-aware path reasoning based on dynamic policy network
Knowledge-Based Syst.
2022
link
Mitropoulou et al.
Anomaly detection in cloud computing using knowledge graph embedding and machine learning mechanisms
J. Grid Comput.
2024
link
Kosasih et al.
Towards knowledge graph reasoning for supply chain risk management using graph neural networks
Int. J. Prod. Res.
2022
link
Yang et al.
Research on enterprise risk knowledge graph based on multi-source data fusion
Neural Comput. Appl.
2022
link
Zhang et al.
Billion-scale pre-trained e-commerce product knowledge graph model
ICDE
2021
link
Model
Title
Conference/Journal
Year
Paper
Sikos
Cybersecurity knowledge graphs
Knowl. Inf. Syst.
2023
link
Ezekia Gilliard et al.
Cybersecurity knowledge graph enabled attack chain detection for cyber-physical systems
Computers and Electrical Engineering
2023
link
Hu et al.
Knowledge graph reasoning for cyber attack detection
IET Commun.
2024
link
Model
Title
Conference/Journal
Year
Paper
Liang et al.
Graph path fusion and reinforcement reasoning for recommendation in MOOCs
Educ. Inf. Technol.
2023
link
Zhou et al.
Mining tourist preferences and decision support via tourism-oriented knowledge graph
Inf. Process. Manag.
2024
link
Gao et al.
Hierarchical knowledge graph learning enabled socioeconomic indicator prediction in location-based social network
The Web Conference (WWW)
2023
link
Zeng et al.
Combining knowledge graph into metro passenger flow prediction: a split-attention relational graph convolutional network
Expert Syst. Appl.
2023
link
Liu et al.
Multi-source knowledge graph reasoning for ocean oil spill detection from satellite SAR images
Int. J. Appl. Earth Obs. Geoinf.
2023
link
⬆️
Challenge and Opportunity
Model
Title
Conference/Journal
Year
Paper
HoGRN
HoGRN: explainable sparse knowledge graph completion via high-order graph reasoning network
IEEE Trans. on Knowledge and Data Engineering
2024
link
Jia et al.
Application of graph neural network and feature information enhancement in relation inference of sparse knowledge graph
Journal of Electronic Science and Technology
2023
link
KRACL
KRACL: contrastive learning with graph context modeling for sparse knowledge graph completion
The Web Conference (WWW)
2023
link
BERT-ConvE
Effective use of BERT in graph embeddings for sparse knowledge graph completion
ACM/SIGAPP Symposium on Applied Computing (SAC)
2022
link
DacKGR
Dynamic anticipation and completion for multi-hop reasoning over sparse knowledge graph
EMNLP
2020
link
RuMER-RL
RuMER-RL: a hybrid framework for sparse knowledge graph explainable reasoning
Information Sciences
2024
link
WAR
Walk-and-relate: a random-walk-based algorithm for representation learning on sparse knowledge graphs
arXiv preprint
2022
link
Model
Title
Conference/Journal
Year
Paper
BEUrRE
Probabilistic box embeddings for uncertain knowledge graph reasoning
NAACL-HLT
2021
link
SUKE
SUKE: embedding model for prediction in uncertain knowledge graph
IEEE Access
2021
link
MUKGE
Embedding uncertain knowledge graphs
AAAI
2019
link
UKRM
Uncertain knowledge graph completion with rule mining
Web Information Systems and Applications
2024
link
TensorLog
Tensorlog: a differentiable deductive database
arXiv preprint
2016
link
Model
Title
Conference/Journal
Year
Paper
CKG-ED
Contrastive knowledge graph error detection
CIKM
2022
link
CAGED
What is normal, what is strange, and what is missing in a knowledge graph: unified characterization via inductive summarization
WWW
2020
link
HEAR
Knowledge graph error detection with hierarchical path structure
CIKM
2023
link
Model
Title
Conference/Journal
Year
Paper
Survey
Logical rule-based knowledge graph reasoning: a comprehensive survey
Mathematics
2023
link
Power-Link
Path-based explanation for knowledge graph completion
KDD
2024
link
IterE
Iteratively learning embeddings and rules for knowledge graph reasoning
WWW
2019
link
EngineKG
Perform like an engine: A closed-loop neural-symbolic learning framework for knowledge graph inference
COLING
2022
link
StreamLearner
Learning temporal rules from knowledge graph streams
AAAI Spring Symposium
2019
link
Tlogic
Tlogic: temporal logical rules for explainable link forecasting on temporal knowledge graphs
AAAI
2022
link
LCGE
Logic and commonsense-guided TKGC
AAAI
2023
link
TILP
TILP: differentiable learning of temporal logical rules on knowledge graphs
ICLR
2023
link
Xu et al.
A human-centric evaluation platform for explainable knowledge graph completion
EACL (System Demonstrations)
2024
link
RLF-KG
Advancing Abductive Reasoning in Knowledge Graphs through Complex Logical Hypothesis Generation
ACL (Volume 1: Long Papers)
2024
lihk
Model
Title
Conference/Journal
Year
Paper
KG-GPT
KG-GPT: a general framework for reasoning on knowledge graphs using large language models
Findings of EMNLP
2023
link
MPIKGC
Multi-perspective improvement of knowledge graph completion with large language models
LREC-COLING
2024
lihk
LARK
Complex logical reasoning over knowledge graphs using large language models
arXiv
2023
link
Chatrule
Chatrule: mining logical rules with large language models for knowledge graph reasoning
arXiv
2023
link
LLM-DA
Large language models-guided dynamic adaptation for temporal knowledge graph reasoning
arXiv
2024
link
Xia et al.
Chain-of-history reasoning for temporal knowledge graph forecasting
Findings of ACL
2024
link
Luo et al.
Chain of history: learning and forecasting with LLMs for temporal knowledge graph completion
arXiv
2024
link
Nguyen et al.
Direct evaluation of chain-of-thought in multi-hop reasoning with knowledge graphs
Findings of ACL
2024
link
GenTKG
GenTKG: Generative Forecasting on Temporal Knowledge Graph with Large Language Models
Findings of NAACL
2024
link
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