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ID:36573321
大小:2.81 MB
页数:92页
时间:2019-05-12
《文本过滤关键技术研究》由会员上传分享,免费在线阅读,更多相关内容在学术论文-天天文库。
1、复旦大学博士学位论文文本过滤关键技术研究姓名:夏迎炬申请学位级别:博士专业:计算机软件与理论指导教师:吴立德20030418塑茎一——AbstractMoreandmoreinformations01.1rezsarenowavailableinmachine—readableformduetotherapiddevelopmentofcommunicationnetworksandinexpensivemassivestorage.Foraspecialuser,theinformafionneededisrelative
2、lysmall.Sincemostofthedataaremassiveinscaleanddiverseinsubjectareas,theymaketheinformationacquisitionbottleneckmoresevere,thusgreatlychallengetheprocessingsystemsinspeed,precisionandrobustness.Inordertofindusefulinformationembeddedinelectronicform.emcientandeffecti
3、vetechniquesforlargescalerealtextprocessinghavebecomeoneofthemosturgentdemands.Tllisdissertationfocusesonthekeytechniquesofadaptivetextfiltering.Wehavedesignedanddevelopedanexperimentplatform.BasedonthatwetookpartintheFilteringtrackofTextREtrievalConference(TRECl0a
4、ndTRECll)andobtainedverygoodresults.InTREell,WeareselectedforthefirstofonlythreespeakingslotsonFilteringtrack.Wealsohavedevelopedseveralsystems,including‘‘Chinesetextfilteringsystem'’and“Web—BasedTrendSearchSystem”.VectorSpaceModel(VSM)isusedtorepresenttext,Therear
5、etwoprincipleproblemsaboutVSM:termselectionandtermweighting.Words,concepts,andterminologiesareselectedasterms.whiletermweightsarecalculated、衍thstatisticalinformationandheuristicrules.WehaveappliedtheWordNettofilteringsystem,usedthesemanticinformationandtrieddisambi
6、guation.WehavedevelopedtheinterfaceofHowNetandappliedittoChinesefilteringsystembyusingitsconceptioninformation.Thismethodhasenhancedthesystem’sperformancewhilelowerthedimensionofvectorgreatly.MachineLearninginadaptivetextfilteringincludesprofilelearningandthreshold
7、learning.Wemakeresearchonthresholdlearning.InTRECIO,wepresentedanovelthreshold—adjustingalgorithm.珊salgorithmadjuststhethresholdfastandefficientlyusingasmallnumberofsamples.InTRECII,wepresentedanovelmethodthatusesawinnowclassifierbuildingfromthesewordstoassistthete
8、xtfilteringsystem.Thismethodcanenhancethesystem’sperformancegreatly.Keywords:AdaptiveTextFiltering,TextFeatureExtraction,VectorSpaceModelMachineL
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