cs 124/linguist 180 from languages to information · advisor lab research management finish. ......
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CS124/LINGUIST180FromLanguagestoInformation
DanJurafsky
StanfordUniversity
IntroductionandCourseOverview
FromLanguagestoInformation
Automaticallyextractingmeaningandstructurefrom:◦Humanlanguagetextandspeech(news,socialmedia,etc.)◦Socialnetworks◦Genomesequences
Interactingwithhumansvialanguage◦Dialogsystems/Chatbots◦QuestionAnswering◦RecommendationSystems
CommercialWorld
1.Extractinginformationfromlanguage
InformationRetrieval
6,586,013,574 websearcheseveryday(byoneestimate)Text-basedinformationretrievalisthuslikelythemostfrequentlyusedpieceofsoftwareintheworldHowdoesitwork?CanyoubuildanIRengine?ProgrammingAssignment4:Search!
ExtractingSentimentandSocialMeaning
Lotsofmeaningisinconnotation"connotation: an idea or feeling that a word invokes in addition to its literal or primary meaning."
Extractingconnotationisgenerallycalledsentimentanalysis
SentimentAnalysis
ExtractingSocialMeaningfromSpeech
Uncertainty(studentsintutoring)Annoyance◦callerstodialogsystems:DeceptionEmotionIntoxicationFlirtation,Romanticinterest◦ McFarland,Jurafsky,Ranganath
Whatdoyoudoforfun?Dance?Uh,dance,uh,Iliketogo,likecamping.Uh,snowboarding,butI'mnotgood,butI
liketogoanyway.Youlikeboarding.Yeah.Iliketodoanything.LikeI,I'mupforanything.Really?Yeah.Areyouopen-mindedaboutmosteverything?Noteverything,butalotofstuff-Whatisnoteverything[laugh]Idon'tknow.Thinkofsomething,andI'llsayifIdoitornot.[laugh]Okay.[unintelligible].Skydiving.Iwouldn'tdoskydivingIdon'tthink.YeahI'mafraidofheights.F:Yeah,yeah,metoo.M:[laugh]Areyouafraidofheights?F:[laugh]Yeah[laugh]
Whatdoflirtersdo?Womenwhenflirting:◦raisepitchceiling◦laughatthemselves◦say“I”Menwhenflirting:◦raisetheirpitchfloor◦laughattheirdate(teasing?)◦say“you”and“youknow”◦don’tusewordsrelatedtoacademics
Rajesh Ranganath, Dan Jurafsky, and Daniel A. McFarland. 2013. Detecting friendly, flirtatious, awkward, and assertive speech in speed-dates. Computer Speech and Language. 27:1, 89-115
Unlikelywordsformaleflirting
academiainterviewteacherphdadvisorlabresearchmanagementfinish
SentimentinRestaurantReviewsDanJurafsky,VictorChahuneau,BryanR.Routledge,andNoahA.Smith.2014.Narrativeframingofconsumersentimentinonlinerestaurantreviews.FirstMonday19:4
Thebartender...absolutelyhorrible...wewaited10minbeforeweevengotherattention...andthenwehadtowait45- FORTYFIVE!- minutesforourentrees…stalkthewaitresstogetthecheque…shedidn'tmakeeyecontactorevenbreakherstridetowaitforaresponse…
900,000Yelpreviewsonline
A very bad (one-star) review:
Whatisthelanguageofbadreviews?Negativesentimentlanguagehorribleawfulterriblebaddisgusting
Pastnarrativesaboutpeoplewaited,didn’t,washe,she,his,her,manager,customer,waitress,waiter
Frequentmentionsofweand us...we wereignoreduntilwe flaggeddownawaitertogetour waitress…
OthernarrativeswiththislanguageAgenreusing:Pasttense,we/us,negative,peoplenarratives
Textswrittenbypeoplesufferingtrauma◦ JamesPennebaker lab◦ Pasttenseasdistancing◦ Useof“we”:seekingsolaceincommunity
1-starreviewsaretraumanarratives!Thelessonofreviews:It’sallaboutpersonalinteraction
Whataboutpositivereviews?Sex,Drugs,andDessert
• orgasmicpastry• sexyfood• seductivelysearedfois gras
� addictedtopeppershooters� garlicnoodles…mydrugofchoice� thefriesarelikecrack
ComputationalBiology:ComparingSequences
SLIDE STUFF FROM SERAFIMBATZOGLOU
AGGCTATCACCTGACCTCCAGGCCGATGCCCTAGCTATCACGACCGCGGTCGATTTGCCCGAC
-AGGCTATCACCTGACCTCCAGGCCGA--TGCCC---| | | | | | | | | | | | | x | | | | | | | | | | |
TAG-CTATCAC--GACCGC--GGTCGATTTGCCCGACSequencecomparisoniskeyto• Findinggenes• Determiningfunction• UncoveringevolutionaryprocessesThisisalsohowspellcheckerswork!
We'lllearn:editdistancealgorithms(Quiz1)
SocialNetworks
Thenetworkformedbyyourfriendsorotherrelationsofflineoronline◦Canwecomputepropertiesofthesenetworks?◦Extractinformationfromthem?
Highschooldating
PeterS.Bearman,JamesMoodyandKatherineStovel Chainsofaffection:ThestructureofadolescentromanticandsexualnetworksAmericanJournalofSociology 11044-91(2004)ImagedrawnbyMarkNewman
Whatisthestructureofsocialrelations?Imagineagraphofhighschool
• peoplearenodes• linksareromanticrelationships
Whatwilltheshapeofthisgraphbe?Adenselyconnectedgraph?Aline?Acycle?
2.Interactingwithhumansvialanguage
QuestionAnswering:IBM’sWatson
RecommendationEngines
PersonalAssistants
Whyislanguageinterpretationhard?
Ambiguity
Resolvingambiguityishard
AmbiguityFindatleast6meaningsofthissentence:
I made her duck
AmbiguityFindatleast6meaningsofthissentence:
I made her duckIcookedwaterfowlforherbenefit(toeat)IcookedwaterfowlbelongingtoherIcreatedthe(plaster?)waterfowlsheownsIcausedhertoquicklylowerherheadorbodyIrecognizedthetrueidentityofherspywaterfowlIwavedmymagicwandandturnedherintoundifferentiatedwaterfowl
AmbiguityisPervasive
IcausedhertoquicklylowerherheadorbodyPartofspeech:“duck”canbeaNounorVerb
Icookedwaterfowlbelongingtoher.Partofspeech:“her”ispossive pronoun(“ofher”)“her”isdativepronoun(“forher”)
Imadethe(plaster)duckstatuesheownsWordMeaning:“make”canmean“create”or“cook”
AmbiguityisPervasive
Grammar:make canbe:Transitive:(verbhasanoundirectobject)
Icooked[waterfowlbelongingtoher]Ditransitive:(verbhas2nounobjects)
Imade[her](into)[undifferentiatedwaterfowl]Action-transitive(verbhasadirectobject+verb)Icaused[her][tomoveherbody]
AmbiguityisPervasive:Phonetics!!!!!ImateorduckI’meightorduckEyemaid;herduckAyemate,herduckImaidherduckI’maidherduckImateherduckI’mateherduckI’mateorduckImateorduck
Moredifficulties:Non-standardlanguage
Great job @justinbieber! Were SOO PROUD of what youve accomplished! U taught us 2 #neversaynever& you yourself should never give up either♥
Andneologisms:unfriendretweetbromance
Makingprogressonthisproblem…
Thetaskisdifficult!Whattoolsdoweneed?◦Knowledgeaboutlanguageandtheworld◦Awaytocombineknowledgesources
Howwegenerallydothis:◦probabilisticmodelsbuiltfromlanguagedataP(“maison”® “house”)highP(“L’avocat général”® “thegeneralavocado”)low
ModelsandToolsRegularExpressionsEditdistanceandalignmentWordembeddings◦vector/neuralmodelsofmeaning
Languagemodels(wordprediction)MachineLearningclassifiers◦NaïveBayes◦LogisticRegression 33
Networkalgorithms◦PageRank
Recommendationalgorithms◦Collaborativefiltering
Linguistictools◦Sentimentlexicons
CourselogisticsinbriefInstructor:DanJurafskyTAs:WillHamilton(headTA)
Time:TuTh 3:00-4:20,420-040cs124.stanford.edu
JeffPykeKellyShenStephanieTangLucyWangRobVoigt
RobinJiaRafaelMusaKateParkCharissa Plattner
JanetteChengTimDozatAshkon FarhangiGasparGarcia
EvidenceBasedPedagogy!
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http://www.knewton.com/flipped-classroom/
Whytheflippedclassroom(1)Masterylearning:LearnuntilyoumasterBenjaminBloom,1968
Bloom'smasterylearningPersonalized,goal-drivenpractice,drivenbyfeedback1. Watch(andre-watch)lecturesatyourownpaceand
learnwhenit'sbestforyou2. Videoshaveembeddedminiquizzes.Ifyougetitwrong,
itgivesyoufeedbackaboutwhyyoumisunderstood.3. Youhave2chancesateachweeklyTuesdayQuizzes,so
youcangobacktothelectureandretakethem.4. Withprogrammingassignmentsyoucanseeyour
performanceonthetrainingsettoseewhatyou'redoingwrong!
Whythevideoshaveembeddedquizzes:“summative”vs“formative”assessment
Summativeassessment◦Finalexams:goalisgrading
Formativeassessment◦Alongtheway:goalisforyou tofindoutwhatyoudon’tknowsoyoucanlearn
Whytheflippedclassroom(2)
Attentionspan:everyonespacesoutduringlonglectures◦Middendorf andKalish,1995,Johnstone andPercival1976,Burns1985
“theclassstarted1:00.Thestudentsittinginfrontofmetookcopiousnotesuntil1:20.Thenhejustnoddedoff…motionless,witheyesshutforaboutaminuteandahalf,penstillpoised.Thenheawokeandcontinuedhisrapidnote-takingasifhehadn’tmissedabeat.”Studentrememberedonlythefirst15-20minutes
Whytheflippedclassroom(3)Activelearning:Beinchargeofyourlearning◦Obviouslymostimportant:programmingassignments◦Activelearning(“constructivism”),learningbydoing
Collaborativelearning:Learnfromeachother◦Useclasstimeforgroupactivities,workedproblems◦“Smallgroupactivelearning”
cs124:Semi-flippedclassroomLecturesonvideo:Iexpectyouto:◦Watchvideolectures(and/orandreadtextbookchapters)◦Onaverageabout90minutesofvideocontenteachweek◦ Somepeoplewatchitspeededup
Somelectureslive:◦ 8lecturesand1groupsessionarerequired(onfinalexam,novideos)◦ Iwillalsore-lecture(double-cover)afewofthevideos◦ somepeopleliketheengagementofin-classlectures
In-classgroupsessions(“activelearning”)◦ Optionalbutrecommended
LogisticsMoreSpecificallyOnlineVideoLectureswithembeddedquizzes(beforeclass)WeeklyonlineReviewQuizzes(Tueoffollowingweek)RoughlyweeklyPythonhomeworks (Frioffollowingweek)FinalExam(TuesdayMarch203:30-6:30)Classsessions:Allencouraged;8 livelecturesrequired◦Fulllectures◦Mini-lectures◦Groupworkedproblems
TheOpenPlatform:EdX!
https://lagunita.stanford.edu/abouthttp://edx.readthedocs.io/projects/edx-guide-for-students/en/latest/index.htmlhttps://open.edx.org/about-open-edx
LearningGoals
Attheendofthiscourse,youwillbeableto:
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Learninggoals
Writeefficientregularexpressionstosolveanykindoftext-basedextractiontask
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Learninggoals
Applytheeditdistancealgorithmtoallsortsoftextsequenceproblems
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Learninggoals
Buildasupervisedclassifiertosolveproblemslikesentimentclassification
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Learninggoals
Buildasearchengine
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Learninggoals
Buildarecommendationengine
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Learninggoals
Buildacomputationalmodelofwordmeaning(usinglexiconsandembeddings)
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Learninggoals
Buildachatbot
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Learninggoals
UnderstandandimplementPageRank
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Thisclassistheundergradintroto:
Win2018:cs224NNaturalLanguageProcessingw/DeepLearningWin2018:cs246MiningMassiveDataSetsSpr 2018:cs222UNaturalLanguageUnderstandingAut 2018:cs224WAnalysisofNetworks
Spr 2019:cs276InformationRetrievalandWebSearch
TBD:cs224SSpokenLanguageProcessing
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Syllabus
http://web.stanford.edu/class/cs124
Comingupnextclass(Thursday)
Unixforpoetsgrepsort
PA1:SpamLord!
Writeregularexpressionstospreadevilthroughoutthegalaxy!Byextractingemailaddressesandphonenumbersfromtheweb!jur a fs ky at st anford dot e d u
GoesliveFriday!
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ActionItemsBeforeThursday!1)Readthesyllabuswebpageatcs124.stanford.edu
2)SignupforpiazzaandedX◦ ForedX,you'llneedtofirstsigninwithyourSUnet IDat suclass.stanford.edu,andthenclickontheEdX buttonatthetopofthecs124.stanford.eduwebpage
3)Watchthefirsthalfofthisweek’svideos(“BasicTextProcessing”)beforeclass!
4)Downloadthisfiletoyourlaptop
http://cs124.stanford.edu/nyt_200811.txt.gz58