LimitedDomainKnowledgeQuestionAnsweringSystemBasedonBI-LSTM-CRF

doi:10.3969/j.issn.1006-2475.2018.07.011

Abstract

Abstract: Withthedevelopmentofopenfieldquestion-answeringsystemandtheurgentneedoftheintegrationofmechanicalindustryandartificialintelligence,itisnecessarytoestablishaknowledgebasequestionansweringsystemformachineryfield.Basedonmechanicalindustrydataandnaturallanguageprocessingtechniques,anetworkmodelbasedonconditionalrandomfieldandlongandshorttermmemoryneuralnetworkisproposedtoimprovetheinformationextractionperformanceandtoestablishaknowledgebasequestion-answeringsysteminmachineryindustry.Throughthecomparativeanalysisofexperimentaldata,themodelhasachievedgoodresults.

Key words: CRF, LSTM, informationextraction, questionanswering

CLC Number:

TP391.1

CHENGShu-dong,HUYing. LimitedDomainKnowledgeQuestionAnsweringSystemBasedonBI-LSTM-CRF[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2018.07.011.

References

［1］宋凯,肖川.全液压热矫直机的结构特点及应用［J］.山西冶金,2016,39(3):91-92.
［2］张凯,宋锦春,李松,等.基于分类学习粒子群优化算法的液压矫直机控制［J］.机械工程学报,2017,53(18):202-208.
［3］乔磊,李存华,仲兆满,等.基于规则的人物信息抽取算法的研究［J］.南京师大学报(自然科学版),2012,35(4):134-139.
［4］郑轶.基于条件随机场的人物信息抽取［J］.计算技术与自动化,2015,34(4):132-136.
［5］王宗尧,刘金岭,崔俊峰,等.基于CRF模型的短文本信息流话题提取［J］.淮阴工学院学报,2016,25(5):6-9.
［6］翟菊叶,陈春燕,张钰,等.基于CRF与规则相结合的中文电子病历命名实体识别研究［J］.包头医学院学报,2017,33(11):124-125.
［7］〖KG-*4〗YaoXuchen,VanDurmeB.Informationextractionoverstructureddata:Questionansweringwithfreebase［C］//MeetingoftheAssociationforComputationalLinguistics.2014:956-966.
［8］BordesA,ChopraS,WestonJ.Questionansweringwithsubgraphembeddings［J］.ComputerScience,2014:arXiv:1406.3676.
［9］BordesA,WestonJ,UsunierN.Openquestionansweringwithweaklysupervisedembeddingmodels［C］//ProceedingsoftheEuropeanConferenceonMachineLearningandKnowledgeDiscoveryinDatabases.2014:165-180.
［10］LiDong,WeiFuru,ZhouMing,etal.Questionansweringoverfreebasewithmulti-columnconvolutionalneuralnetworks［C］//Proceedingsofthe53rdAnnualMeetingoftheAssociationforComputationalLinguistics&the7thInternationalJointConferenceonNaturalLanguageProcessing.2015:260-269.
［11］YihWen-tau,ChangMing-Wei,HeXiaodong,etal.Semanticparsingviastagedquerygraphgeneration:Questionansweringwithknowledgebase［C］//Proceedingsofthe53rdAnnualMeetingoftheAssociationforComputationalLinguisticsandthe7thInternationalJointConferenceonNaturalLanguageProcessing.2015:1321-1331.
［12］周博通,孙承杰,林磊,等.基于LSTM的大规模知识库自动问答［J］.北京大学学报(自然科学版),2018,54(2):286-292.
［13］LaffertyJ,MccallumA,PereiraF.Conditionalrandomfields:Probabilisticmodelsforsegmentingandlabelingsequencedata［C］//Proceedingsofthe18thInternationalConferenceonMachineLearning.2001:282-289.
［14］HochreiterS,SchmidhuberJ.Longshort-termmemory［J］.NeuralComputation,1997,9(8):1735-1780.
［15］HintonGE.Learningdistributedrepresentationsofconcepts［C］//Proceedingsofthe8thAnnualConferenceoftheCognitiveScienceSociety.1986:46-61.
［16］DiekemaAR,YilmazelO,LiddyED.Evaluationofrestricteddomainquestion-answeringsystems［C］//ProceedingsoftheACLWorkshoponQuestionAnsweringinRestrictedDomain.2004.
［17］杨煜,张炜.TensorFlow平台上基于LSTM神经网络的人体动作分类［J］.智能计算机与应用,2017,7(5):41-45.

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