Vocabulary learning entry selection method, device, electronic equipment and storage medium

Abstract

The invention provides a vocabulary learning entry selection method, device, electronic equipment and storage medium, through the data mining of the corpus, the entry and entry word frequency data are obtained, and then the entries are combined into word families and further calculated Word frequency data for word families. According to the word frequency data of word families, high-frequency words are given priority to learning in stages, which can grasp the focus of learning; deep mining of the relationship between words with word families and etymology, the memory of entries will become more profound, the combination of the two Good teaching and memory effects can be achieved.

Description

technical field [0001] The invention relates to the field of education, in particular to a vocabulary learning entry selection method, device, electronic equipment and computer-readable storage medium. Background technique [0002] With the development of society, foreign languages ​​are becoming more and more important in our life and work. Therefore, more and more people are learning languages ​​(such as English), and they often need to memorize a large number of words in the learning process. Memorizing words is very boring. At the same time, due to the similarity between many words, this also brings difficulty to memory for learners. [0003] Most of the existing vocabulary learning methods recommend words that need to be learned, and the learners memorize them by themselves. This kind of learning method does not have a systematic learning framework, which not only has low learning efficiency, but also leads to poor memory. Contents of the invention [0004] In view o...

AI Technical Summary

Problems solved by technology

[0003] Most of the existing vocabulary learning methods recommend words that need to be learned, and the learners memorize them by themselves. This kind of learning method does not have a systematic learning framework, which not only has low learning efficiency, but also leads to poor memory

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