一种基于结构化语料库的概念语义网络自动生成算法-豆柴文库

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一种基于结构化语料库的概念语义网络自动生成算法
基于结构化语料库的概念语义网络自动生成算法
Abstract:
Withtherapiddevelopmentofnaturallanguageprocessingandartificialintelligence,thegenerationofconceptsemanticnetworksplaysacrucialroleinvariousapplicationssuchasknowledgerepresentation,questionanswering,andinformationretrieval.Inthispaper,weproposeanovelalgorithmforgeneratingconceptsemanticnetworksbasedonstructuredcorpora.Thealgorithmcombinesnaturallanguageprocessingtechniqueswithgraphtheorytoautomaticallyextractconceptrelationshipsfromlarge-scaletextdataandconstructasemanticnetwork.Experimentalresultsdemonstratetheeffectivenessandefficiencyoftheproposedalgorithm.
Keywords:conceptsemanticnetwork,structuredcorpus,naturallanguageprocessing,graphtheory
1.Introduction
Conceptsemanticnetworks,alsoknownasconceptmaps,representtherelationshipsbetweenvariousconceptsinadomain.Thesenetworksprovideastructuredrepresentationofknowledgeandenablereasoningandinferenceinvariousapplications.Thegenerationofconceptsemanticnetworksfromunstructuredtextdataisachallengingtaskduetothecomplexityandambiguityofnaturallanguage.Traditionalapproachesrelyonmanualconstructionorspecificlinguisticrules,whicharetime-consumingandlimitedinscalability.
Withtheavailabilityoflarge-scalestructuredcorpora,suchasWikipediaandonlineknowledgebases,thereisanopportunitytoleveragetheseresourcesforautomaticconceptsemanticnetworkgeneration.Thegoalistoextractconceptrelationshipsfromthetextdataandconstructanetworkthatcapturesthesemanticassociationsbetweenconcepts.Inthispaper,weproposeanalgorithmthatcombinesnaturallanguageprocessingtechniqueswithgraphtheorytoachievethisgoal.
2.AlgorithmOverview
Ouralgorithmconsistsofseveralkeysteps:textpreprocessing,conceptextraction,conceptrelationshipextraction,andnetworkconstruction.Inthefollowingsections,wedescribeeachstepindetail.
2.1TextPreprocessing
Thefirststepistopreprocesstheinputtextdatatoremovenoiseandirrelevantinformation.Thisincludestokenization,stopwordremoval,andstemming.Tokenizationbreaksthetextintoindividualwordsorphr