摘要
传统的英语教学中,资源利用率不高,调度能力不强。为了解决这些问题,文中提出了一种基于关联语义规则的英语文本摘要改进算法。挖掘了英语文本短语和句子之间的相关特征,实现了英语摘要中关键词的语义关联分析和特征提取,其核心是基于信息论获得了英语摘要的关联规则判别。然后将文本相似度特征作为两个语义关联规则向量的最大差异分量,结合语义相似度信息,最终实现英语文本摘要的精确提取。仿真结果表明,该方法能够准确地提取出文本摘要,在提取过程中具有较好的收敛性和精确性。
In traditional English teaching,the resource utilization rate is not high,and the scheduling ability is not strong.In order to solve these problems,an improved English text summary algorithm based on association semantic rules is proposed here.The relevant features between English text phrases and sentences are mined,and the semantic association analysis and feature extraction of keywords in English abstracts are realized.Its core is to obtain the association rules of English abstracts based on information theory.Then the text similarity feature is used as the largest difference component of the two semantic association rule vectors,combined with the semantic similarity information,and finally the accurate extraction of English text summaries is achieved.Simulation results show that the method can accurately extract text summaries,and there are good convergence and accuracy in the extraction process.
作者
帕提曼·吐尔逊
任艳
PATIMAN Tuerxun;REN Yan(Language and Culture Institute,Xinjiang Medical University,Urumqi 830011,China;Information Management Institute,Xinjiang University of Finance and Economics,Urumqi 830012,China)
出处
《信息技术》
2020年第12期82-85,共4页
Information Technology
关键词
英语文本
抽象提取
语义特征
英语教学
相似度
English text
abstract extraction
semantic features
English teaching
similarity
