Computer Science ›› 2018, Vol. 45 ›› Issue (6): 183-186.doi: 10.11896/j.issn.1002-137X.2018.06.032

• Artificial Intelligence • Previous Articles     Next Articles

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

HAN Zhao1,3, MIAO Duo-qian1,2, REN Fu-ji2,3   

  1. College of Electronics and Information Engineering,Tongji University,Shanghai 201804,China1;
    Key Laboratory of Embedded System and Service Computing,Ministry of Education,Tongji University,Shanghai 201804,China2;
    Faculty of Engineering,Tokushima University,Tokushima 7708506,Japan3
  • Received:2017-12-18 Online:2018-06-15 Published:2018-07-24

Abstract: 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 predi-cate,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.

Key words: Information retrieval, Knowledge based question answering, Question answering system, Rough set, Short text similarity

CLC Number: 

  • TP391
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