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Knowledge Graph Embedding

24 papers with code · Graphs

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GraphVite: A High-Performance CPU-GPU Hybrid System for Node Embedding

2 Mar 2019DeepGraphLearning/graphvite

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.

DIMENSIONALITY REDUCTION KNOWLEDGE GRAPH EMBEDDING LINK PREDICTION NETWORK EMBEDDING NODE CLASSIFICATION

KBGAN: Adversarial Learning for Knowledge Graph Embeddings

NAACL 2018 cai-lw/KBGAN

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

23 Jan 2019hwwang55/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.

KNOWLEDGE GRAPH EMBEDDING KNOWLEDGE GRAPHS MULTI-TASK LEARNING RECOMMENDATION SYSTEMS

Pykg2vec: A Python Library for Knowledge Graph Embedding

4 Jun 2019Sujit-O/pykg2vec

Python library for knowledge graph embedding and representation learning.

KNOWLEDGE GRAPH EMBEDDING

Answering Visual-Relational Queries in Web-Extracted Knowledge Graphs

7 Sep 2017nle-ml/mmkb

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

Multi-view Knowledge Graph Embedding for Entity Alignment

6 Jun 2019THU-KEG/Entity_Alignment_Papers

Furthermore, we design some cross-KG inference methods to enhance the alignment between two KGs.

ENTITY ALIGNMENT KNOWLEDGE GRAPH EMBEDDING KNOWLEDGE GRAPHS

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

Differentiating Concepts and Instances for Knowledge Graph Embedding

EMNLP 2018 davidlvxin/TransC

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.

KNOWLEDGE GRAPH EMBEDDING KNOWLEDGE GRAPHS LINK PREDICTION

Quaternion Knowledge Graph Embeddings

NeurIPS 2019 cheungdaven/QuatE

In this work, we move beyond the traditional complex-valued representations, introducing more expressive hypercomplex representations to model entities and relations for knowledge graph embeddings.

KNOWLEDGE GRAPH COMPLETION KNOWLEDGE GRAPH EMBEDDING KNOWLEDGE GRAPH EMBEDDINGS LINK PREDICTION