Knowledge Graph Embedding
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| TREND | DATASET | BEST METHOD | PAPER TITLE | PAPER | CODE | COMPARE |
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Greatest papers with code
GraphVite: A High-Performance CPU-GPU Hybrid System for Node Embedding
In this paper, we propose GraphVite, a high-performance CPU-GPU hybrid system for training node embeddings, by co-optimizing the algorithm and the system.
SOTA for Node Classification on YouTube
DIMENSIONALITY REDUCTION KNOWLEDGE GRAPH EMBEDDING LINK PREDICTION NETWORK EMBEDDING NODE CLASSIFICATION
DeepPath: A Reinforcement Learning Method for Knowledge Graph Reasoning
We study the problem of learning to reason in large scale knowledge graphs (KGs).
KNOWLEDGE GRAPH EMBEDDING KNOWLEDGE GRAPH EMBEDDINGS KNOWLEDGE GRAPHS
KBGAN: Adversarial Learning for Knowledge Graph Embeddings
This framework is independent of the concrete form of generator and discriminator, and therefore can utilize a wide variety of knowledge graph embedding models as its building blocks.
KNOWLEDGE BASE COMPLETION KNOWLEDGE GRAPH EMBEDDING KNOWLEDGE GRAPH EMBEDDINGS KNOWLEDGE GRAPHS LINK PREDICTION
Multi-Task Feature Learning for Knowledge Graph Enhanced Recommendation
• hwwang55/MKR
• 
Collaborative filtering often suffers from sparsity and cold start problems in real recommendation scenarios, therefore, researchers and engineers usually use side information to address the issues and improve the performance of recommender systems.
COLLABORATIVE FILTERING KNOWLEDGE GRAPH EMBEDDING KNOWLEDGE GRAPHS MULTI-TASK LEARNING
Pykg2vec: A Python Library for Knowledge Graph Embedding
• Sujit-O/pykg2vec
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Python library for knowledge graph embedding and representation learning.
Answering Visual-Relational Queries in Web-Extracted Knowledge Graphs
A visual-relational knowledge graph (KG) is a multi-relational graph whose entities are associated with images.
IMAGE RETRIEVAL KNOWLEDGE GRAPH EMBEDDING KNOWLEDGE GRAPH EMBEDDINGS KNOWLEDGE GRAPHS ZERO-SHOT LEARNING
HyTE: Hyperplane-based Temporally aware Knowledge Graph Embedding
EMNLP 2018
• malllabiisc/HyTE
•
Knowledge Graph (KG) embedding has emerged as an active area of research resulting in the development of several KG embedding methods.
INFORMATION RETRIEVAL KNOWLEDGE GRAPH EMBEDDING KNOWLEDGE GRAPHS QUESTION ANSWERING
Multi-view Knowledge Graph Embedding for Entity Alignment
• THU-KEG/Entity_Alignment_Papers
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Furthermore, we design some cross-KG inference methods to enhance the alignment between two KGs.
Differentiating Concepts and Instances for Knowledge Graph Embedding
Most conventional knowledge embedding methods encode both entities (concepts and instances) and relations as vectors in a low dimensional semantic space equally, ignoring the difference between concepts and instances.
Improving Knowledge Graph Embedding Using Simple Constraints
We examine non-negativity constraints on entity representations and approximate entailment constraints on relation representations.