Aggregation Algorithm in Text Translation Systems

In order to solve the problem of time-consuming and inaccurate translation in current translation systems, this paper constructs a text translation system based on the K-means clustering algorithm under the aggregation algorithm. This article takes the shared corpus of the Information Retrieval Research Office of Harbin Institute of Technology as an example to compare the translation time and accuracy of different sentence lengths in four different genres. The research results of this article found that the translation system based on K-means algorithm has the best performance, and its translation time is relatively short. The translation accuracy can reach over $\mathbf{9 5 \%}$, far higher than traditional translation systems. This indicates that aggregation algorithms can play an important role in text translation systems.