A method for generating distractor items of English near-form words combined with parts of speech

Abstract

The invention relates to a method for generating distractors of English similar word forms by being combined with word class. The method includes steps of selecting a source word from a word bank as a source word character string, utilizing other words as target word character strings, traversing all words in the word bank, and solving similarity between the source word character string and the target character strings according to uniformized integration similarity algorithm; controlling the threshold value of the similarity within 0.6-1.0, and taking the words within the range of the threshold value as optional words; subjecting the optional words and the source word output in the last step to similarity calculation combined with the word class, and controlling the threshold value a of the similarity within 0.6-1.0, thereby obtaining the distractors of the source word; finishing once processing course. By introducing the LCS (longest common subsequence) algorithm to uniformized integration, blindness in calculating similarity of the English words by singly depending on one similarity algorithm is changed, reliability and accuracy in generation of the distractors of the English similar word forms are improved, and the problem that words with same meaning but in different word classes repeatedly appear is solved.

Description

technical field [0001] The invention relates to a natural language processing method, in particular to a method for generating interference items of English near-form words combined with parts of speech. Background technique [0002] In the process of learning English, we often encounter some confusing words. Confusing words mainly include synonyms and near-form words, among which near-form words are words with similar word forms. For example: the adjective sensitive means "sensitive", while the adjective sensible means "reasonable". Although sensitive and sensible share a common root and have the same part of speech, these two words are not synonyms, but synonyms. In the design of English test questions or other English learning resources, near-form words often appear as distracting items for correct word options, so as to increase the difficulty of selection and improve learners' mastery of words. [0003] The traditional near-word interference generation algorithm main...

AI Technical Summary

Problems solved by technology

[0003] The traditional near-word interference generation algorithm mainly uses the edit distance algorithm to calculate word similarity, but the edit distance algorithm itself has some defects, resulting in insufficient accuracy and rationality in generating near-form words, and the similarity of interference items is low. unreasonable question

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