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Empirical methods for compound splitting

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EmpiricalMethodsforCompoundSplitting

PhilippKoehn

InformationSciencesInstitute

DepartmentofComputerScience

UniversityofSouthernCalifornia

koehn@isi.eduKevinKnight

InformationSciencesInstitute

DepartmentofComputerScience

UniversityofSouthernCalifornia

knight@isi.edu

Abstract

Compoundedwordsareachallengefor

NLPapplicationssuchasmachinetrans-

lation(MT).Weintroducemethodsto

learnsplittingrulesfrommonolingual

andparallelcorpora.Weevaluatethem

againstagoldstandardandmeasure

theirimpactonperformanceofstatisti-

calMTsystems.Resultsshowaccuracy

of99.1%andperformancegainsforMT

of0.039BLEUonaGerman-English

nounphrasetranslationtask.

1Introduction

Compoundingofwordsiscommoninanumberof

languages(German,Dutch,Finnish,Greek,etc.).

Sincewordsmaybejoinedfreely,thisvastlyin-

creasesthevocabularysize,leadingtosparsedata

problems.Thisposeschallengesforanumber

ofNLPapplicationssuchasmachinetranslation,

speechrecognition,textclassification,information

extraction,orinformationretrieval.

Formachinetranslation,thesplittingofanun-

knowncompoundintoitspartsenablesthetransla-

tionofthecompoundbythetranslationofitsparts.

TakethewordAktionsplaninGerman(seeFig-

ure1),whichwascreatedbyjoiningthewordsAk-

tionandPlan.Breakingupthiscompoundwould

assistthetranslationintoEnglishasactionplan.

Compoundsplittingisawelldefinedcompu-

tationallinguisticstask.Onewaytodefinethe

goalofcompoundsplittingistobreakupforeignAktionsplan

Aktionsplanactionplan

Akt ionsplanaction plan

act ion plan

Figure1:SplittingoptionsfortheGermanword

Aktionsplan

words,sothataone-to-onecorrespondencetoEn-

glishcanbeestablished.Notethatwearelooking

foraone-to-onecorrespondencetoEnglishcon-

tentwords:Say,thepreferredtranslationofAk-

tionsplanisplanforaction.Thelackofcorre-

spondencefortheEnglishwordfordoesnotde-

tractfromthedefinitionofthetask:Wewould

stillliketobreakuptheGermancompoundinto

thetwopartsAktionandPlan.Theinsertionof

functionwordsisnotourconcern.

Ultimately,thepurposeofthisworkistoim-

provethequalityofmachinetranslationsystems.

Forinstance,phrase-basedtranslationsystems

[MarcuandWong,2002]mayrecovermoreeas-

ilyfromsplittingregimesthatdonotcreatea

one-to-onetranslationcorrespondence.Onesplit-

tingmethodmaymistakenlybreakuptheword

AktionsplanintothethreewordsAkt,Ion,and

Plan.Butifweconsistentlybreakuptheword

AktionintoAktandIoninourtrainingdata,suchasystemwilllikelylearnthetranslationoftheword

pairAktIonintothesingleEnglishwordaction.

Theseconsiderationsleadustothreedifferent

objectivesandthereforethreedifferentevaluation

metricsforthetaskofcompoundsplitting:

One-to-Onecorrespondence

Translationqualitywithaword-basedtrans-

lationsystem

Translationqualitywithaphrase-basedtrans-

lationsystem

Forthefirstobjective,wecomparetheoutput

ofourmethodstoamanuallycreatedgoldstan-

dard.Forthesecondandthird,weprovidediffer-

entlypreparedtrainingcorporatostatisticalma-

chinetranslationsystems.

2RelatedWork

Whilethelinguisticpropertiesofcompoundsare

widelystudied[Langer,1998],therehasbeenonly

limitedworkonempiricalmethodstosplitup

compoundsforspecificapplications.

Brown[2002]proposesaapproachguidedby

aparallelcorpus.Itislimitedtobreakingcom-

poundsintocognatesandwordsfoundinatransla-

tionlexicon.Thislexiconmayalsobeacquiredby

trainingastatisticalmachinetranslationsystem.

Themethodsleadstoimprovedtextcoverageof

anexamplebasedmachinetranslationsystem,but

noresultsontranslationperformancearereported.

MonzanddeRijke[2001]andHedlundetal.

[2001]successfullyuselexiconbasedapproaches

tocompoundsplittingforinformationretrieval.

Compoundsarebrokenintoeitherthesmallestor

thebiggestwordsthatcanbefoundinagivenlex-

icon.

Larsonetal.[2000]proposeadata-driven

methodthatcombinescompoundsplittingand

wordrecombinationforspeechrecognition.While

itreducesthenumberofout-of-vocabularywords,

itdoesnotimprovespeechrecognitionaccuracy.

MorphologicalanalyzerssuchasMorphix[Fin-

klerandNeumann,1998]usuallyprovideavariety

ofsplittingoptionsandleaveittothesubsequent

applicationtopickthebestchoice.3SplittingOptions

Compoundsarecreatedbyjoiningexistingwords

together.Thus,toenumerateallpossiblesplittings

ofacompound,weconsiderallsplitsintoknown

words.Knownwordsarewordsthatexistina

trainingcorpus,inourcasetheEuropeanparlia-

mentproceedingsconsistingof20millionwords

ofGerman[Koehn,2002].

Whenjoiningwords,fillerlettersmaybein-

sertedatthejoint.ThesearecalledFugenelemente

inGerman.RecalltheexampleofAktionsplan,

wheretheletterswasinsertedbetweenAktionand

Plan.Sincetherearenosimplerulesforwhen

suchlettersmaybeinsertedweallowthembe-

tweenanytwowords.Asfillersweallowsand

eswhensplittingGermanwords,whichcoversal-

mostallcases.Othertransformationsatjointsin-

cludedroppingofletters,suchaswhenSchweigen

andMinutearejoinedintoSchweigeminute,drop-

pingann.Aextensivestudyofsuchtransforma-

合集下载

戴锋基本情况

戴锋基本情况

1

戴锋基本情况

1982年毕业于西安交通大学应用数学系，获理学学士学位

教育背景

1987年毕业于国防科技大学系统工程系，获工学硕士学位

管理科学专业教授，博士研究生导师

德意志银行(Deutsche Bank)金融研究中心CFS(Center for Financial

Studies)特约咨询专家

《中国优选法统筹法及经济数学研究会》理事

《管理科学学报》、《系统工程学报》，国际会议“CCCT”(计算机通讯

和控制技术)，“FSKD”(IEEE模糊系统学会)及“ICNC”(IEEE计算机学会)

的审稿专家 学术背景

出版著作6部，发表学术论文80余篇

现在使用：fengdai@，并将继续使用

电子信箱(E-mail) 曾经使用：fengdai@ 与 fengdai@，但

已经不再使用

Feng DAI’s biography and related information

B.S., Department of Applied Mathematics, Xi’an Jiaotong University

(China), 1982. EDUCATIONAL

BACKGROUND M.S., Department of System Engineering, National University of Defense

Technology (China), 1987.

Professor of economic management and science, Department of

Management Science, Zhengzhou Information Engineering University

(China), Doctoral Advisor

An advisory expert of CFS (Center for Financial Studies) of Deutsche Bank.

俱乐部趋同

俱乐部趋同

AppliedEconomicsLetters,2006,13,569–574

Clubconvergencein

Europeanregions

RitaDeSianoaandMarcellaD’Uvab,*

aDepartmentofEconomicStudies,UniversityofNaples‘Parthenope’,

ViaMedina40,80133Naples,ItalybDepartmentofSocialSciences,UniversityofNaplesL’Orientale,

LargoS.GiovanniMaggiore30,80134Naples,Italy

Thisstudyinvestigatesthe‘clubconvergence’hypothesisapplyingthe

stochasticnotionofconvergencetogroupsofEuropeanregions.Inorder

toavoidthegroupselectionbiasproblem,theinnovativeregressiontree

techniquewasappliedtoselectendogenouslythemostimportantvariables

inachievingthebestidentificationofgroupsonthebaseofpercapita

incomeandproductivespecialization.Testsonstochasticconvergence

ineachgroupevidencesastrongconvergenceamongthewealthiestregions

oftheEuropeanUnionandatrendofweakconvergenceamongthe

remaininggroups,confirmingBaumol’shypothesisofconvergence.

Ferromagnetic bulk glassy alloys

Ferromagnetic bulk glassy alloys

JournalofMagnetismandMagneticMaterials215}216(2000)246}252InvitedpaperFerromagneticbulkglassyalloys

AkihisaInoue󰀁,AkihiroMakino󰀂󰀬*,TakaoMizushima󰀃

󰀁InstituteforMaterialsResearch,TohokuUniversity,Sendai980-8577,Japan󰀂DepartmentofMachineIntelligenceandSystemEngineering,AkitaPrefecturalUniversity,Honjo015-0055,Japan󰀃CentralResearchLaboratory,AlpsElectricCo.,Ltd.,Nagaoka940-8572,Japan

Abstract

Thispaperdealswiththereviewontheformation,thermalstabilityandmagneticpropertiesoftheFe-basedbulkglassyalloysinas-castbulkandmelt-spunribbonforms.Alargesupercooledliquidregionover50KbeforecrystallizationwasobtainedinFe}(Al,Ga)}(P,C,B,Si),Fe}(Cr,Mo,Nb)}(Al,Ga)}(P,C,B)and(Fe,Co,Ni)}Zr}M}B(M"Ti,Hf,V,Nb,Ta,Cr,MoandW)systemsandbulkglassyalloyswereproducedinathicknessrangebelow2mmfortheFe}(Al,Ga)}(P,C,B,Si)systemand6mmfortheFe}Co}(Zr,Nb,Ta)}(Mo,W)-Bsystembycopper-moldcasting.Thering-shapedglassyFe}(Al,Ga)}(P,C,B,Si)alloysexhibitmuchbettersoftmagneticpropertiesascomparedwiththering-shapedalloymadefromthemelt-spunribbonbecauseoftheformationoftheuniquedomainstructure.Thegoodcombinationofhighglass-formingabilityandgoodsoftmagneticpropertiesindicatesthepossibilityoffuturedevelopmentasanewbulkglassymagneticmaterial.󰀁2000ElsevierScienceB.V.Allrightsreserved.Keywords:Ferromagneticbulkglassyalloy;Rapidsolidi"cation;Widesupercooledliquidregion;Softmagneticproperty

成盐反应

成盐反应

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1. Query 19 reactions in

Reaxys 2014-11-18 01h:54m:50s (EST)

Search as: Product, As drawn, No salts, No mixtures

色氨酸甲酯盐酸盐的制备

在冰浴下,增加了100毫升圆底烧瓶与60毫升的甲醇,然后慢慢加4毫升SOCl2 恒压滴液漏斗(干燥管顶部),和氢氧化钠溶液吸收废气。

搅拌1小时后,8mmol的色氨酸(3 d)补充道,在室温下搅拌30分钟,然后回流在66°c 6 h。

反应是由薄层色谱跟踪,直到原料消失,2%茚三酮在乙醇溶液为显色剂。

溶剂蒸发了获得色氨酸甲酯盐酸盐。收益率:100%。

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