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KGML

INTRODUCTION

Predicting relations in Knowledge Graph by Multi-Label Deep Neural Network.

EXECUTION

Training

python train_kgml.py [option] [dataset]

Dataset

FB15k, WN18 or WD40k.

Option

Option Description
-d1 Hyperparameter dim1. Integer. Default value is 100.
-d2 Hyperparameter dim2. Integer. Default value is 100.
-a Hyperparameter alpha. Float in [0,1]. Default value is 1.0.

Example

python train_kgml.py WD40k
python train_kgml.py -d1 50 -d2 50 -a 0.5 FB15k

Test

python test_kgml.py [model] [dataset]

Example

python test_kgml.py kgml_WD40k.h5 WD40k

DATA

FB15k and WN18 are the same as the ones used in the paper "Translating Embeddings for Modeling Multi-relational Data (2013).".
https://everest.hds.utc.fr/doku.php?id=en:transe They are available at data.zip in https://github.com/thunlp/KB2E.

Experiment Environment

  • tensorflow 1.4.1
  • Keras 2.1.2
  • CUDA 8.0.61
  • Cudnn 6.0.20

kgml's People

Contributors

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Watchers

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Forkers

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