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Knowledge Graphs

106 papers with code · Knowledge Base

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OpenKE: An Open Toolkit for Knowledge Embedding

EMNLP 2018 thunlp/OpenKE

We release an open toolkit for knowledge embedding (OpenKE), which provides a unified framework and various fundamental models to embed knowledge graphs into a continuous low-dimensional space.

INFORMATION RETRIEVAL KNOWLEDGE GRAPHS QUESTION ANSWERING REPRESENTATION LEARNING

Knowledge Graph Completion via Complex Tensor Factorization

22 Feb 2017Accenture/AmpliGraph

In statistical relational learning, knowledge graph completion deals with automatically understanding the structure of large knowledge graphs---labeled directed graphs---and predicting missing relationships---labeled edges.

KNOWLEDGE GRAPH COMPLETION LINK PREDICTION RELATIONAL REASONING

Holographic Embeddings of Knowledge Graphs

16 Oct 2015Accenture/AmpliGraph

Learning embeddings of entities and relations is an efficient and versatile method to perform machine learning on relational data such as knowledge graphs.

KNOWLEDGE GRAPHS LINK PREDICTION RELATIONAL REASONING

Modeling Relational Data with Graph Convolutional Networks

17 Mar 2017tkipf/gae

We demonstrate the effectiveness of R-GCNs as a stand-alone model for entity classification.

GRAPH CLASSIFICATION INFORMATION RETRIEVAL KNOWLEDGE BASE COMPLETION KNOWLEDGE GRAPHS LINK PREDICTION

ERNIE: Enhanced Language Representation with Informative Entities

ACL 2019 thunlp/ERNIE

Neural language representation models such as BERT pre-trained on large-scale corpora can well capture rich semantic patterns from plain text, and be fine-tuned to consistently improve the performance of various NLP tasks.

ENTITY TYPING KNOWLEDGE GRAPHS NATURAL LANGUAGE INFERENCE SENTIMENT ANALYSIS

Zero-shot Recognition via Semantic Embeddings and Knowledge Graphs

CVPR 2018 JudyYe/zero-shot-gcn

Given a learned knowledge graph (KG), our approach takes as input semantic embeddings for each node (representing visual category).

GRAPH NEURAL NETWORK KNOWLEDGE GRAPHS ZERO-SHOT LEARNING

Convolutional 2D Knowledge Graph Embeddings

5 Jul 2017TimDettmers/ConvE

In this work, we introduce ConvE, a multi-layer convolutional network model for link prediction, and report state-of-the-art results for several established datasets.

KNOWLEDGE GRAPH EMBEDDINGS KNOWLEDGE GRAPHS LINK PREDICTION

Learning Deep Generative Models of Graphs

ICLR 2018 JiaxuanYou/graph-generation

Graphs are fundamental data structures which concisely capture the relational structure in many important real-world domains, such as knowledge graphs, physical and social interactions, language, and chemistry.

GRAPH GENERATION KNOWLEDGE GRAPHS

Explainable Knowledge Graph-based Recommendation via Deep Reinforcement Learning

22 Jun 2019DeepGraphLearning/RecommenderSystems

Recently, a variety of methods have been developed for this problem, which generally try to learn effective representations of users and items and then match items to users according to their representations.

KNOWLEDGE GRAPHS POLICY GRADIENT METHODS RECOMMENDATION SYSTEMS