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thunlp · Oct 22, 2017 · 00bbad5 · 00bbad5
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 The implementation of TransE [1], TransH [2], TransR [3], TransD [4] for knowledge representation learning (KRL). The overall framework is based on TensorFlow. We use C++ to implement some underlying operations such as data preprocessing and negative sampling. For each specific model, it is implemented by TensorFlow with Python interfaces so that there is a convenient platform to run models on GPUs. 
 
+These codes will be gradually integrated into the new framework [[OpenKE]](https://github.com/thunlp/openke).
 
 # Customizing Your Own Model