基于粗糙集理论的中文知识问答的知识谓词分析  

Rough Set Based Knowledge Predicate Analysis of Chinese Knowledge Based Question Answering

作　　者：韩朝 苗夺谦[1,3] 任福继 HAN Zhao;MIAO Duo-qian;REN Fu-ji(College of Electronics and Information Engineering,Tongji Universit;Faculty of Engineering,Tokushima Universit;Key Laboratory of Embedded System and Service Computing,Ministry of Education,Tongji Universit)

机构地区：[1]同济大学电子与信息工程学院,上海201804 [2]德岛大学工学部,德岛7708506 [3]嵌入式系统与服务计算教育部重点实验室(同济大学),上海201804

出　　处：《计算机科学》2018年第6期183-186,共4页Computer Science

基　　金：国家自然科学基金项目(61273304;61673301;61573255);高校学校博士学科点专项基金项目(20130072130004)资助

摘　　要：在基于知识的问答系统中,问句中的知识谓词信息分析结果将会对知识元组的整体匹配效果产生影响。中文短问句中的知识谓词的信息表达方式存在着不确定性,这些不确定性的表达增加了知识谓词分析的难度。从粗糙集理论的角度,提出了一种问句中的知识谓词的分析方法,对问句中的知识谓词的弱相关表达进行约简,使问句中与知识谓词强相关的表达词能更有效地与知识元组中的知识谓词匹配,进而提高系统对知识谓词的整体分析能力。实验结果验证了新方法的有效性。In knowledge based question answering system,the performance of knowledge predicate analysis can affect the overall match result of knowledge triple.The knowledge predicate analysis of Chinese short question is difficult because of the uncertainty of Chinese knowledge predicate representation.Based on the rough set theory,a new definition of knowledge predicate analysis of knowledge based question snswering was given,and a new method was proposed to analyze the knowledge predicate of question.It can reduce the words which are weakly related with the knowledge predicate,and then the words which are more related with knowledge predicate representation will be used to match the knowledge triples to improve the overall performance of system.The experiment results verify the validity of the method.

关 键 词：粗糙集 问答系统 知识问答 信息检索 短文本相似度 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]