计算机科学
人工智能
构造(python库)
互联网
排名(信息检索)
文字2vec
自然语言处理
情报检索
多媒体
万维网
嵌入
程序设计语言
作者
Panpan Li,Yuwen Ning,Hongjuan Fang
标识
DOI:10.1177/0020720920983528
摘要
With the gradual advancement of education reform, English learning has become more and more important, and efficient and fast English learning has become a concern of people. In this study, an online translation platform based on artificial intelligence was selected for exploration. Use SQLite software database server as text data source. When the user performs English translation, the query word will be input into the translation platform, and at the same time, the artificial intelligence Google API translation technology will translate the text. Based on the collected actual user service usage records, build edge computing solutions and analyze user data input records. Use word2vec to construct the feature vector of the word, and use LSTM to construct the word ranking of the text. The word ranking method is used to predict the user's service usage, select the corresponding edge server, and combine the relevant probability model to preload the service. Combined with the edge algorithm compression data processing technology of the Internet of Things, the data is synchronized and tracked. After the data is compressed, the translated text is displayed on the application interface in the form of voice and words. The research results show that the use of edge computing of the Internet of Things increases the preservation rate of historical query records of intelligent translation by 30%, and the intelligent translation platform predicts that the matching degree of users' translation queries is 90%. The use of edge algorithm compression technology of the Internet of Things can greatly save the network traffic and bandwidth of the server. The optimized query algorithm can improve query efficiency, save query time, and increase users' enthusiasm for learning English.
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