Year-end Sale % OFF 
Abstract
Realizing accurate recognition of Chinese and English information is a major difficulty in English feature recognition. Based on this difficulty, this paper studies the English feature recognition model based on deep belief network classification algorithm and Big Data analysis. First, the basic framework based on deep belief network classification algorithm and Big Data analysis is proposed. Combined with the Big Data analysis training model, the English feature information is processed. Through the recognition of different English text features, the recognition and matching of English features are realized. Then the errors of deep belief network classification algorithm and Big Data analysis are evaluated. Second, this paper describes the quantitative evaluation of deep belief network classification algorithm and Big Data analysis in this system. In the evaluation, the language feature evaluation method is used to improve the evaluation function. At the same time, the deep belief network classification algorithm and Big Data analysis are used to self-study the model, and the English feature recognition method with strong applicability is established. Finally, the effectiveness of the recognition system is verified by the experiment.
Highlights
Xiaoling LiuIt can be seen that most of the current English feature recognition systems do not involve the evaluation model based on deep belief neural network classification algorithm and Big Data analysis [11]
E core content of English feature recognition is to evaluate the accuracy and efficiency of recognition, which is of great value to promote the intelligent development of English text and English characteristics [3]
This paper proposes an English feature recognition method based on belief neural network classification algorithm and Big Data analysis. is paper studies the English text and English feature recognition system based on deep belief network classification algorithm and Big Data analysis, which is mainly divided into 4 parts
Summary
It can be seen that most of the current English feature recognition systems do not involve the evaluation model based on deep belief neural network classification algorithm and Big Data analysis [11]. China has done a lot of basic research on English characteristics, there are few achievements in the specific quantitative dynamic recognition of English features Based on this background, this paper proposes an English feature recognition method based on belief neural network classification algorithm and Big Data analysis. Compared with the existing research results (English feature recognition methods are only limited to the recognition of grammar, vocabulary, and other textual characteristics), the innovation of this article is to propose a deep belief network classification algorithm and Big Data analysis based on English text and English feature recognition system. The English feature recognition model uses feature difference factors to quantitatively describe the degree of data matching between each comparison column and the reference column and the amount of difference in standard data, and complete the prioritization of English feature classification standards with quantitative indicators, which is better than the existing one. e research results can further improve the recognition efficiency of English features
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
