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作 者:郭娜[1] 赵向军 GUO Na;ZHAO Xiang-jun(Jiangsu Normal University Department of Informationization Construction and Management,Xuzhou 221116,China;Nanjing Xiaozhuang University,Nanjing 210007,China)
机构地区:[1]江苏师范大学信息化建设与管理处,江苏徐州221116 [2]南京晓庄学院,江苏南京210017
出 处:《南京晓庄学院学报》2022年第6期119-124,共6页Journal of Nanjing Xiaozhuang University
摘 要:本文基于Matlab平台,借助分词、词频统计和词汇聚类等文本处理技术处理文本库,获得符合学生学习规律的词汇序表,在充分考虑学生的认知特点和接受度的基础上,划分词汇序表,确定各学段的必学词汇表.依据各学段的必学词汇表,设计半自动化的语文教材选文推荐方法,为编者推荐与各学段词汇表匹配度较高的一系列选文,以提高教材选编的效率,促进教材编排的科学性.Based on Matlab,the paper generates an ordered vocabulary through a series of operations including word segmentation,word-frequency statistics and word-clustering.On the basis of fully considering the cognitive characteristics and acceptance of students,the obtained vocabulary can be divided into several small vocabularies,and each of them corresponds to one grade.Then,we propose a semi-automatic recommendation method to recommend a series of articles with high matching degree to each small vocabulary.The experimental results show that this method can effectively improve the efficiency of Chinese textbook selection and editing,as well as,promote the scientificity of Chinese textbook arrangement.
分 类 号:TP311.13[自动化与计算机技术—计算机软件与理论]
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