#alpsp17www.alpsp.org/Conference

Parallel – Picke Room IAI – Two publishing case studiesDavid Smith (Chair & speaker) - IETMarcel Karnstedt-Hulpus - Springer Nature

Youwon’tbelievehoweasyitistobuildanAI!

RetoolinganA&Idatabaseforthe21st Century.

AbouttheIET• TheIETisoneoftheworld’slargestengineeringinstitutionswithover168,000membersin150countries.Itisalsothemostmultidisciplinary– toreflecttheincreasinglydiversenatureofengineeringinthe21stcentury.

• TheIETisworkingtoengineerabetterworldbyinspiring,informingandinfluencingourmembers,engineersandtechnicians,andallthosewhoaretouchedby,ortouch,theworkofengineers.

INSPEC:ABluffersGuide• AhighlycuratedA&IdatabasecoveringEngineering,ComputingandPhysics(etc etc)

• Forover40Years• >17millionabstracts• SoMuchMetadataWOW!• SeveralhundredyearsworthofHumanExpertisekeepsaverycloseeyeonthemetadataquality

Soitwasamanualsystem…

Andhere’showitworked…

Weneededtochangethis…• TheTechwasE.O.L• TheManualmethodswererestrictive&expensive(butVHighQuality)

• Wehadreachedanupperlimitoncoverageandvolume

• Therewereclearopportunitiestorethinkwhatweweredoingandwhy…

• RebootingINSPECproductioncouldopenupnewbusinessavenues– ifwegotitright.

Goals…• Delivercostsavings(ROIargumentused).• Movethehumaneffortfurtherupthevaluechain• Beabletoextendcoveragecapabilities• Beabletoextendvolumecapabilities• ReconfigurethedatainINSPECtoallownewwaysofasking

questionsofit.• BuildanewIETIPasset• FocusonautomationwithhumanQA(‘GroundTruthing’)

Sothisiswhatwehavebuilt…(Simpleversion)

Acquisition

• IngestXML/PDF/OCR

Normalisation

•RendertostandardINSPECSchemaforonwardprocessing

MetadataApplication

•TheAIliveshere…

ProductGeneration

•Setupofabstractstovariousoutputcontainers

Output

•VariousXMLoutputsasneeded

Humans Machine Machine&HumanQA Machine Machine/HumanQA

Ohyeah…We’vealsobuiltanINSPECKnowledgeGraphCoveringallofINSPEC

Let’sfocusontheAI• Whatdoesitdo?• Howdoesitwork?• Isitanygood?

Whatdoesitdo?• Itreadstext.• ItexpectsthattexttocontainengineeringcontentcommensuratewithINSPECcoverage

• ItthenappliesthefullgamutofINSPECmetadatatothetext…Uncontrolledindexing/Controlledterms/Classifications/Numericalindexing/Chemicalindexing/Astronomicalobjectindexing/Treatmentcodes

84

Howdoesitwork?• Wedon’treallyknow.Weturneditonafewmonthsagoandremovedhumansfromthedecisionprocess.Itstartedtolearnatageometricrateuntilitbecameselfaware.Wetriedtoturnitoff,butitalreadyhadphishedourAWScreditcarddetails.Itkeepsaskinguswhere‘Wintermute’is.Helpusplease…

Howdoesitwork?

JustKidding!

Howdoesitwork?• Itusesamixtureof

– Heuristics– NaturalLanguageProcessors– Statisticalanalysistools– AndaselectionofAIalgorithms.

• Webuiltadetaileddomainmodel&Ontologyforittouse

• It’sbeentrainedviadirectedlearningofagoldencorpus(circa600KdocumentsacrossINSPEC)

Howdoesitwork?• AndaselectionofAIalgorithms…

– Welookedatadaboost (goseewikipedia…)– Alsoword2vec(likewise)– AndTensorflow – thedeeplearningalgo fromGoogle.Interestingresults…ItdidsomeratheroddthingsTBHsoweabandonedthatapproach.

IsitAnyGood?• Arathercomplexquestiontoanswerinmanyways…

• Whenitstartstogetgood(anditis)ittestspreviouslyheldassumptionsaboutwhatqualityactuallyis…

• We’velearnedourselvesquiteabitaboutwhatwethinkisgoodandWHYasaresultofteachingamachinetounderstandengineeringtexts.

IsitAnyGood?ShowMeTheNumbers!

ControlledTermsFScoreresults ClassificationsFScoreresultsINSPECClassificationsarecomplexmetaconcepts

Remember– FscoreisafunctionofBOTHPrecisionandrecall…

IsitAnyGood?• WecangetVERYhighnumbersindeedonindividualconceptandtermmatching(90%+)butmuchofthemetadataweaddisaboutwhereagivenitemshouldbelonginourvariousmeta-classificationapproaches.

• WealsohavetofigureoutawaytolookacrosstheentiretyoftheINSPECdatawhenthemachineislearning.Animprovementinoneareacanleadtooddresultselsewhere.

IsitAnyGood?• Ohyes.It’sverygoodindeed.SeniorINSPECAlumniofmanyyearsarefrequentlystunnedbywhatitcando.

• It’slive.It’sdeliveringsavingstousnowandit’sallowingustogotakealookatwhat’soverthehorizonfortheIET…

Visualisation

Thanks!

Q’s(attheend)