Application of Data Mining Methods in Internet of Things Technology for the Translation Systems in Traditional Ethnic Books

Abstract

In order to translate the ethnic classics, based on the research on the Internet of things, machine learning, and translation technology of ethnic classics, the log-linear model is combined with the national corpus scale and the grammatical structure characteristics, and the phrase statistical machine translation is used to establish a discontinuous phrase extraction model. Then, the translation technology is studied from the three aspects of model definition, training, and decoding. Finally, the algorithm is compared with the traditional phrase extraction algorithm to verify its effectiveness. The results show that the extraction number of discontinuous phrase extraction model is significantly higher than that of traditional phrase extraction model, and the model can extract more phrases, handle larger and more complex text, and score higher in translation fluency. From the evaluation indexes scores of Bilingual Evaluation Understudy (B.L.E.U.) and National Institute of Standards and Technology (N.I.S.T.), it can be found that the B.L.E.U. and N.I.S.T. values of the traditional phrase extraction algorithm are lower than those of the discontinuous phrase extraction model algorithm. The discontinuous phrase extraction algorithm can not only extract the regular continuous phrase, but also obtain the discontinuous text, and the translation effect is better. In conclusion, the combination of Internet of things and machine learning can be used in the translation of ethnic classics to achieve high-quality translation of discontinuous phrases, which is of guiding significance for the study of machine translation.

Keywords

• Internet of Things
• traditional national classic
• Corpora
• translation
• data mining