Abstract
The application of artificial intelligence in the field of English needs to process a large amount of English text data, but the deviation of English word similarity reduces its overall English translation accuracy and data processing efficiency. Therefore, this paper proposes an accurate estimation of English word similarity based on semantic network, which combines a variety of computing methods to form a compound computing structure based on semantic network. The experimental results show that the error between the Semantic Web-based English word similarity calculation method and manual evaluation is small, and the accuracy of English word similarity calculation is improved to a certain extent. In addition, compared with other English word similarity calculation methods, the English word similarity calculation method based on semantic network is more in line with people’s cognition and understanding of knowledge, has higher reliability, and has certain practical value in the field of English.
Highlights
With the continuous development of the international economy, the cooperation between countries in all aspects is increasing and deepening
The similarity of English words can help AI quickly understand a kind of similar text information, but on the other hand, if there is a large error in the recognition of English word similarity, it will affect the recognition of English words and text by AI [3]. is task is widely used in machine translation [4]
With the development of Internet technology, people can obtain a large amount of information from different languages all over the world, among which English is one of the most widely used languages. e development of artificial intelligence technology has changed the way people learn English or use English and related information, especially in English dictionary query entries and English translation
Summary
With the continuous development of the international economy, the cooperation between countries in all aspects is increasing and deepening. Erefore, English learning and English translation have attracted extensive attention. With the development of artificial intelligence, there are new ways and means of English learning and translation. Nonnative language learners need to understand and learn similar English words when learning English, which needs the help of an English dictionary [5]. With the development of natural language processing technology, many English word semantic resources have been widely used. Based on these semantic dictionaries, many studies on the semantics of English words have put forward the corresponding calculation of English word similarity, which has attracted extensive attention for a time. Skipgram-KR creates similar word training data through backward mapping and the two-word skipping method
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