DESIGN OF AN AUTOMATED KNOWLEDGE INTEGRATION SYSTEM FOR ENGLISH TRANSLATION CORPUS BASED ON DATA MINING ALGORITHMS

Yanhua Ma
School of English Language, Zhejiang Yuexiu University, Shaoxing, Zhejiang, China, 312000

Abstract:

Machine interpretation (MT) is a subfield of normal language handling that attempts to utilize PCs to decipher regular dialects. Start to finish neural machine interpretation (NMT) has turned into the new standard strategy in genuine machine interpretation frameworks lately. In this article, we first give an extensive outline of NMT approaches prior to zeroing in on designs, interpreting, and information expansion strategies. Then, at that point, we gather a rundown of significant locales and apparatuses for scientists. At last, we'll discuss some potential future review bearings. In spite of ongoing advances in neural machine interpretation, incorporating various covering, subjective earlier information sources stays a troublesome assignment. We suggest that back regularization be utilized to give an expansive structure to joining earlier data into neural machine interpretation in this paper. Earlier information sources are addressed as highlights in a log-straight model that coordinates the neural interpretation model's learning cycle. Explores different avenues regarding Chinese-to-English interpretation show that our strategy yields huge increases.