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Knowledge Base Completion

16 papers with code · Knowledge Base
Subtask of Knowledge Base

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Greatest papers with code

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.

KNOWLEDGE BASE COMPLETION KNOWLEDGE GRAPHS LINK PREDICTION

Combining Two And Three-Way Embeddings Models for Link Prediction in Knowledge Bases

2 Jun 2015glorotxa/SME

This paper tackles the problem of endogenous link prediction for Knowledge Base completion.

KNOWLEDGE BASE COMPLETION LINK PREDICTION

KBGAN: Adversarial Learning for Knowledge Graph Embeddings

HLT 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

KBLRN : End-to-End Learning of Knowledge Base Representations with Latent, Relational, and Numerical Features

14 Sep 2017nle-ml/mmkb

We present KBLRN, a framework for end-to-end learning of knowledge base representations from latent, relational, and numerical features.

KNOWLEDGE BASE COMPLETION REPRESENTATION LEARNING

Canonical Tensor Decomposition for Knowledge Base Completion

ICML 2018 facebookresearch/kbc

The problem of Knowledge Base Completion can be framed as a 3rd-order binary tensor completion problem.

KNOWLEDGE BASE COMPLETION LINK PREDICTION

An overview of embedding models of entities and relationships for knowledge base completion

23 Mar 2017datquocnguyen/STransE

Knowledge bases (KBs) of real-world facts about entities and their relationships are useful resources for a variety of natural language processing tasks.

KNOWLEDGE BASE COMPLETION LINK PREDICTION

STransE: a novel embedding model of entities and relationships in knowledge bases

HLT 2016 datquocnguyen/STransE

Knowledge bases of real-world facts about entities and their relationships are useful resources for a variety of natural language processing tasks.

KNOWLEDGE BASE COMPLETION LINK PREDICTION

Embedding Multimodal Relational Data for Knowledge Base Completion

EMNLP 2018 pouyapez/multim-kb-embeddings

In this paper, we propose multimodal knowledge base embeddings (MKBE) that use different neural encoders for this variety of observed data, and combine them with existing relational models to learn embeddings of the entities and multimodal data.

KNOWLEDGE BASE COMPLETION LINK PREDICTION

End-to-end Structure-Aware Convolutional Networks for Knowledge Base Completion

11 Nov 2018JD-AI-Research-Silicon-Valley/SACN

The recent graph convolutional network (GCN) provides another way of learning graph node embedding by successfully utilizing graph connectivity structure.

KNOWLEDGE BASE COMPLETION KNOWLEDGE GRAPH EMBEDDING KNOWLEDGE GRAPHS LINK PREDICTION