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1、TamingRecurrentNeuralNetworksforBetterSummarizationAPRIL16,2017Thisisablogpostaboutourlatestpaper,GetToThePoint:SummarizationwithPointer-GeneratorNetworks,toappearatACL2017.Codewillbereleasedshortly.Theinternetagehasbroughtunfathomablymassiveamountsofinform
2、ationtothefingertipsofbillions–ifonlywehadtimetoreadit.Thoughourliveshavebeentransformedbyreadyaccesstolimitlessdata,wealsofindourselvesensnaredbyinformationoverload.Forthisreason,automatictextsummarization–thetaskofautomaticallycondensingapieceoftexttoasho
3、rterversion–isbecomingincreasinglyvital.TwotypesofsummarizationTherearebroadlytwoapproachestoautomatictextsummarization:extractiveandabstractive.Extractiveapproachesselectpassagesfromthesourcetext,thenarrangethemtoformasummary.Youmightthinkoftheseapproaches
4、aslikeahighlighter.Abstractiveapproachesusenaturallanguagegenerationtechniquestowritenovelsentences.Bythesameanalogy,theseapproachesarelikeapen.Thegreatmajorityofexistingapproachestoautomaticsummarizationareextractive–mostlybecauseitismucheasiertoselecttext
5、thanitistogeneratetextfromscratch.Forexample,ifyourextractiveapproachinvolvesselectingandrearrangingwholesentencesfromthesourcetext,youareguaranteedtoproduceasummarythatisgrammatical,fairlyreadable,andrelatedtothesourcetext.Thesesystems(severalareavailableo
6、nline)canbereasonablysuccessfulwhenappliedtomid-lengthfactualtextsuchasnewsarticlesandtechnicaldocuments.Ontheotherhand,theextractiveapproachistoorestrictivetoproducehuman-likesummaries–especiallyoflonger,morecomplextext.ImaginetryingtowriteaWikipedia-style
7、plotsynopsisofanovel–say,GreatExpectations–solelybyselectingandrearrangingsentencesfromthebook.Thiswouldbeimpossible.Foronething,GreatExpectationsiswritteninthefirstpersonwhereasasynopsisshouldbeinthethirdperson.Moreimportantly,condensingwholechaptersofacti
8、ondowntoasentencelikePipvisitsMissHavishamandfallsinlovewithheradopteddaughterEstellarequirespowerfulparaphrasingthatispossibleonlyinanabstractiveframework.Inshort:abstractivesummarizationmaybedi icult