Construction of large scale English teaching corpus and e-learning system based on Apache Hadoop algorithm

Abstract

Currently, the contradiction between traditional English teaching and the need for dynamic learning is becoming increasingly prominent. Therefore, the organic integration of new teaching aids with traditional English teaching is conducive to achieving a new concept design and innovation in English teaching. On this basis, a large-scale English teaching corpus was established by combining MapReduce with Apache Hadoop algorithm. At the same time, information theory and methods based on the MapReduce computing model are proposed and applied to the parallelism analysis of big data, effectively solving practical problems that are difficult to expand certain datasets. Secondly, this article will design a new algorithm, Salsa20, based on the construction characteristics of Apache Hadoop. By utilizing the parallel characteristics of this algorithm, we can parallelize the Apache Hadoop algorithm, improve the system's data processing ability, ensure the security of data in MapReduce operation mode, and ensure its efficient data processing ability. In addition, the comprehensive and systematic use of large-scale corpora to establish an English teaching system based on them can effectively improve some of the problems that arise in English teaching, greatly enhance the teaching effectiveness of English courses.