面向高考语文阅读理解的篇章标题选择研究  

Discourse Title Selection for Chinese Reading Comprehension of College Entrance Examination

作　　者：关勇 吕国英[1] 李茹[1,2,3] 郭少茹 谭红叶 GUAN Yong;LV Guoying;LI Ru;GUO Shaoru;TAN Hongyel(School of Computer and Information Technology,Shanxi University,Taiyuan,Shanxi 030006,China;Key Laboratory of Ministry of Education for Computation Intelligence and Chinese Information Processing,Shanxi University,Taiyuan,Shanxi 030006,China;Collaborative Innovation Center of Big Data Mining and Intelligent Technology in Shanxi,Taiyuan,Shanxi 030006,China)

机构地区：[1]山西大学计算机与信息技术学院,山西太原030006 [2]山西大学计算智能与中文信息处理教育部重点实验室,山西太原030006 [3]山西省大数据挖掘与智能技术协同创新中心,山西太原030006

出　　处：《中文信息学报》2018年第6期28-35,43,共9页Journal of Chinese Information Processing

基　　金：国家863计划(2015AA015407);国家自然科学基金(61772324;61673248)

摘　　要：高考语文阅读理解篇章标题选择题要求机器根据对篇章内容的理解,从多个候选项中选取能够准确恰当的概括表达篇章内容的选项。标题往往是高度凝练且能准确表达文意、结构鲜明的词串。因此,如何对篇章内容进行归纳概括、对标题结构进行梳理和分析是解答篇章标题选择题的关键。针对该问题,提出了标题与篇章要点相关性分析模型。该模型通过分析标题与篇章要点的相关性,构建了基于标题和篇章要点的相关度矩阵。在此基础上融入标题结构特征,选取与篇章最相关的标题。在全国近10年高考真题和测试题上进行实验,验证了该方法的有效性。Discourse title selection for reading comprehension in the college entrance examination on Chinese is to se- lect the best option by summarizing and analyzing the articles. The title usually captures the meaning of the article accurately in a distinctive structure. Summarizing information about the article and analyzing the title structure is the key to solve the problem. This paper proposes a correlation analysis model based on title and discourse key-points to solve the problem. This model constructs a correlation matrix of title and the discourse key-points, selecting the best answer is jointly with the title structure features. The experiment on the national college entrance examination ques- tions of recent 10 years verifies the validity of the method.

关 键 词：高考语文 阅读理解 标题选择 神经网络 标题结构 相关度矩阵 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]