An Improved TransE Algorithm

Haoyu Chang, Xin Luo, Youqun Shi, Xin-Xin Li, Tao Yang
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Abstract

This paper proposes the TransE-CBA (TransE Based On Improved Bernoulli And Adam) model, an improved TransE model. We used an improved Bernoulli distribution sampling method to improve the accuracy of negative samples, and used the Adam algorithm to update the gradient to improve the performance of the algorithm. Experiment result shows that, on the FB13 and WN18 datasets, the TransE-CBA model has a lower average ranking score (MeanRank) than TransE as a whole, and the proportion of the top ten triples (HITS@10) Higher, better sorting effect.
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一种改进的TransE算法
本文提出了TransE- cba (TransE Based On Improved Bernoulli And Adam)模型,这是TransE模型的改进。我们使用改进的伯努利分布采样方法来提高负样本的准确性,并使用Adam算法来更新梯度以提高算法的性能。实验结果表明,在FB13和WN18数据集上,TransE- cba模型的平均排序分数(MeanRank)低于TransE整体,且前十位三元组的比例(HITS@10)更高,排序效果更好。
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