In order to understand the latest research progress of TransE based representation learning methods in real time, this paper classified TransE based representation learning methods into four types: the method based on complex relationship, the method based on relationship path, the method based on image information, and the method based on other aspects. Then, this paper analyzed the design ideas, advantages and disadvantages of each method. At the same time, it compared and summarized the common data sets and evaluation indexes of the TransE based representation learning method, as well as the performance of various TransE based representation learning algorithms in the experiment. From the research results, PaSKoGE, NTransGH, TCE and TransD method perform the best in link prediction and triple classification tasks, which are worth promoting and further expanding, and can be further improved in path specific embedding, two-layer neural network, triple context and dynamic mapping matrix construction.

[2021-03-05] Printed Article /doc/2020.02.0028/v2