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1、杭州电子科技大学硕士学位论文ABSTRACTSinceSinamicrobloggingplatformstarteditsservicein2009,theusers’countofmicroblogkeepsincreasingatahighspeedannually.Attractedbythenewcharactersofmicroblog,peopleuseitcontinuouslyandwidely.Withuniquestructureofusernetworkandhugeinfluencepow
2、er,microbloghasbecomeanewforceofinformationdisseminating.Nowadays,thewholeusersinmicrobloggingplatformgeneratemillionsofpostseveryday,whichleadstothefactthatpeoplecanhardlyobtainusefulinformationfrommillionsofmicroblogposts.Therefore,itismeaningfultoproposeana
3、utomaticmethodforautomaticallydetectingthemostcomprehensiveandlatestemergingtopics.Withsuchamethodcanwemaintainthesocietymorestabilityandharmonious.Thispaperstudiesthekeytechnologiesofdetectingbursttopicsfrommicroblogstreams,includingthefollowtwoparts.Firstly,
4、basedonthebloomcharactersofemergingtopic,amodelcalledBurstKeywordsExtractingModelwasproposed.AfterdefiningadatastructurenamedMicroblogStreamSegment,theextractingmodelutilizes3kindsoftechnologiessuchasslidingwindow,divideandconquerandweightingtechnologies,toext
5、ractburstkeywordsfrommicroblogmessagestream.Experimentresultshaveshownthattheproposedburstkeywordsextractingmethodcanmorecomprehensivelyandaccuratelyextractburstkeywordsofeachtimeintervals.Besides,withtheburstkeywordsextractedfrommicroblogstream,weproposedanot
6、hermodelnamedBurstTopicsDetectingModel.Firstofall,thismodeltakesadvantageoftheInformationRetrievaltechnologiestoconstructthemutualinformationmatrixofkeywordset.Then,thedetectingmodelclustersburstkeywordsetbyiterativelyexpandinganewtopic’skeywordset.Finally,the
7、subsetoftopicalkeywordsareregardastheresultsofclusteringprocedurearethebursttopics.Theexperimentprovedthatthismethodcancomprehensivelyandaccuratelydetectbursttopicsofeachtimeperiod.Inconclusion,basedontheburstcharacterofemergingtopicsinmicroblog,weproposedanew
8、methodtoextractbursttopicalkeywordsandabursttopicdetectingmethodformicrobloggingplatform.Thesetwotechnologiescanhelpuserstotimelyandcomprehensivelygetthelatestbursttopicsinmicroblo