Method for mining students' online English learning intention based on user portrait and big data

To overcome the problems of low recall, low accuracy, and long time in traditional methods, a new method for mining students' online English learning intention based on user portrait and big data is proposed. With the support of big data technology, the maximum mean difference algorithm is used to determine the distance between student online English learning data sample points, and the K-means algorithm is used to implement student online English learning data collection. The collected data is used to construct user personas, and the attention mechanism is used to extract students' online English learning characteristics. A student's online English learning willingness mining model based on extreme learning machine network is established to obtain relevant mining results. Experimental tests have shown that the recall rate of the proposed method is always above 97.3%, the maximum mining accuracy is 98.1%, and the average mining time is 79.15 ms.