Aditya Gaurav Bhalotia Soumen Chakrabarti Arvind Hulgeri Charuta Nakhe Parag S Sudarshan Computer Science and Engg Dept IIT Bombay badityasoumenaruparagsudarsha cseiitbacin bhalotiaeecsberkeley edu charutapsplcoin Abstract The BANKS system ID: 4289 Download Pdf
Aditya Gaurav Bhalotia Soumen Chakrabarti Arvind Hulgeri Charuta Nakhe Parag S Sudarshan Computer Science and Engg Dept IIT Bombay badityasoumenaruparagsudarsha cseiitbacin bhalotiaeecsberkeleyedu charutapsplcoin Abstract The BANKS system enables ke
Kostas Stefanidis. *. Chinese University of Hong Kong. Joint work with M. Drosou and E. Pitoura. University of Ioannina. *Work done while with the University of Ioannina. Introduction. Keyword-based search .
Information. Database. A database is a collection of data arranged for ease and speed of search and retrieval (The American Heritage Dictionary of English Language, 2000). . The . quality of being "... arranged for ease and speed of search and retrieval" is what distinguishes a database from a computer network..
Seminar: Transaction Processing (Bachelor). SS 2009. Dennis . Stratmann. Outline. Goal and Overview. Examine Three Approaches to CC on RD:. 1. Predicate-Oriented Concurrency Control. 2. Relational Update Transactions.
Marina . Drosou. Computer Science Department . University of . Ioannina. , Greece. Joint work with . Kostas . Stefanidis. *. and . Evaggelia. . Pitoura. http://dmod.cs.uoi.gr. * Now at the Chinese University of Hong Kong.
Marina . Drosou. Computer Science Department . University of . Ioannina. , Greece. Joint work with . Kostas . Stefanidis. *. and . Evaggelia. . Pitoura. http://dmod.cs.uoi.gr. * Now at the Chinese University of Hong Kong.
ucsdedu Yannis Papakonstantinou University of California San Diego yanniscsucsdedu Abstract DISCOVER operates on relational databases and facilitates information discovery on them by al lowing its user to issue keyword queries without any knowledge o
An . entity. is anything about which the organization wishes to store data. At your college or university, one entity would be the student.. STUDENTS. Student ID. Last Name. First Name. Phone Number.
Lecture 11 * Fall 2019 * Kesden. Socrative. https://api.socrative.com/rc/Nfu6Lp. Today’s Goals. A brief introduction to relational databases. A brief introduction to the SQL language used by relational databases.
Cse 344 May 7 th – Exam Review Examination Stations Exam Wednesday 9:30-10:20 One sheet of notes, front and back Practice solutions out after class Good luck! Exam Length Production v. Verification
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Aditya Gaurav Bhalotia Soumen Chakrabarti Arvind Hulgeri Charuta Nakhe Parag S Sudarshan Computer Science and Engg Dept IIT Bombay badityasoumenaruparagsudarsha cseiitbacin bhalotiaeecsberkeley edu charutapsplcoin Abstract The BANKS system
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BANKS:BrowsingandKeywordSearchinginRelationalDatabasesB.AdityaGauravBhalotiaSoumenChakrabartiArvindHulgeriCharutaNakheParagS.SudarshanComputerScienceandEngg.Dept.,I.I.T.Bombaybaditya,soumen,aru,parag,sudarsha@cse.iitb.ac.inbhalotia@eecs.berkeley.educharuta@pspl.co.inAbstractTheBANKSsystemenableskeyword-basedsearchondatabases,togetherwithdataandschemabrowsing.BANKSenablesusersto PartlysupportedbyanIBMFacultyFellowshipgrantand Mining Surprising Patterns UsingTemporal Description Length ChakrabartiSD98...Paper Tuple PaperIdPaperName ByronDChakrabartiSD9 8 Writes Tuple SunitaSChakrabartiSD98Writes Tuple ...Sunita SarawagiSunitaSAuthor Tuple A uthorIdAuthorName . .. Byron DomByronDAuthor Tuple Figure1:AFragmentoftheDBLPDatabaseBANKS,includingrelevancescorecomputation,isde-scribedinmoredetailinSection2.BANKSprovidesarichinterfacetobrowsedata,withautomaticgenerationofhyperlinks.Thebrows-ingcomponentofBANKSisdescribedinmorede-tailinSection3.TheBANKSsystemisdevelopedinJavausingservletsandJDBC,andcanberunonanydatabase,withoutanyprogramming.Wearealsode-velopingaversionofBANKSthathandlesXMLdata.ThegreatestvalueofBANKSliesinalmostzero-eortWebpublishingofrelationaldatawhichwouldotherwiseremaininvisibletotheWeb[2].Forexam-ple,BANKSmaybeusedtopublishorganizationaldata,bibliographicdata,andelectroniccatalogs.AdemooftheBANKSsystemisaccessibleovertheWebattheURL:http://www.cse.iitb.ac.in/banks/2KeywordsearchConsiderafragmentofabibliographicdatabaseshowninFigure1.Thisdatabasecontainspapertitles,theirauthorsandcitationsextractedfromtheDBLPreposi-tory.Aswecansee,duetonormalization,informationaboutasinglepaperisdistributedacrossseventuplesrelatedthroughforeignkeyreferences.Auserlookingforthispapermayusequerieslikesunitatemporalorsoumensunita.TheBANKSsystemmodelsthedatabaseasadi-rectedgraph,witheachtupleinthedatabasecorre-spondingtoanodeinthegraph.Eachforeign-keyprimary-keylinkismodeledasadirectededgebetweenthecorrespondingtuples.(Thiscanbeeasilyextendedtoothertypeofconnections.)AkeywordqueryinBANKSconsistsof1searchterms,...,t.Therststepistolocatethesetofnodesmatchingsearchterms;anodematchesasearchtermifitcontainsthesearchtermaspartofanat-tributevalueormetadata(suchascolumn,tableorviewnames).Letdenotethesetofnodesmatch- Figure2:Resultofquerysoumensunita;anodemaymatchmorethanonesearchterm,sothesmayoverlap.Intuitively,ananswertoaqueryisasubgraphconnectingsomesetofnodesthatcoverthekeywords,i.e.,eachkeywordmustmatchoneofthenodesin.Justbylookingatasubgraphitmaynotbeapparentwhatinformationitconveys.Wewishtoalsoidentifyacentralnodeinthesubgraph,thatconnectsallthekeywordnodes,andstronglyreectstherelationshipamongstthem.Ananswertoaqueryisthereforemodeledasarooteddirectedtreecontainingatleastonenodefromeach;edgesaredirectedawayfromtheroot.Themotivationfordirectionalityisoutlinedlaterinthissection.NotethatthetreemayalsocontainnodesnotinanyandisthereforeaSteinertree.Fig-ure2showsasampleresultofaquerycontainingthekeywordssoumenandsunitaexecutedonthebiblio-graphicdatabase.Indentationisusedtodepictthetreestructure,andnodescontainingkeywordsaredis-tinguishedbytheircolor.2.1AnswerRelevanceIngeneral,theimportanceofalinkdependsuponthetypeofthelink,i.e.,whatrelationsitconnectsandonitssemantics;forexample,inabibliographicdatabase,thelinkbetweenthePapertableandtheWritestableisseenasastrongerlinkthanthelinkbetweenthePapertableandtheCitestable.ThelinkbetweenPaperandCitestablescancorrespondinglybegivenahigherweight.Theweightofatreeisproportionaltothetotalofitsedgeweights,andtherelevanceofatreeisinverselyrelatedtoitsweight.TheexampleinFigure1illustratesthatsomelinkspointtowardtherootofthetree,insteadofawayfromtherootasrequiredbyourmodel.Forinstance,theWritesrelationhasforeignkeystothePaperandAu-thorrelations,whereaswerequirepathsfromPaper Author,traversingaforeignkeyedgeintheop-positedirection.However,wecannotsimplyregardtheedgesasundirected.Ignoringdirectionalitywouldcauseproblemsbecauseofhubsthatareconnectedtoalargenumbersofnodes.Forexample,inauni-versitydatabaseadepartmentwithalargenumberoffacultyandstudentswouldactasahub.Asaresult,manynodeswouldbewithinashortdistanceofmanyothernodes,reducingtheeectivenessoftree-weightbasedscoringmechanism.Tosolvetheproblem,wecreateforeachedge(u,vbackwardedgev,u);intheexamplefromFigure1,thebackwardedgesensurethatthereisadirectedtreerootedatthepaper,withapathtoeachleaf.Wesettheweightof(v,u)totheweightof(u,v)multipliedbyafunctionofthenumberoflinkstofromthenodesofthesametypeas.Experimentswithdierentfunctionsindicatedthatthefunctionlog(1+),whereisthenumberofinlinks,providedgoodresults[3].(Iftherewasalreadyanedgefrom,wesettheedgeweighttotheloweroftheoriginaledgeweightandtheweightcomputedabove.)BANKSincorporatesanotherinterestingfeature,namelynodeweights,inspiredbyprestigerankingssuchasPageRankinGoogle[4].Withthisfeature,nodesthathavemultiplepointerstothemgetahighernodeweight(highernodeweightcorrespondstohigherprestige).E.g.,inabibliographydatabasecontainingcitationinformation,iftheusergivesaqueryQueryOptimizationourtechniquewouldgivehigherprestigetothepaperswithmorecitations.Asanotherexam-ple,inaTPCDdatabasestoringinformationaboutparts,suppliers,customersandorders,theordersin-formationcontainsreferencestoparts,suppliersandcustomers.Asaresult,ifaquerymatchestwoparts(orsuppliers,orcustomers)theonewithmoreorderswouldgetahigherprestige.Inthecurrentimplementationwesetthenodeweighttoafunctionofthein-degreeofthenode.Weexperimentedwithdierentfunctions,andgotgoodresultswiththefunctionlog(1+),whereisthein-degree.Ouruseoflogarithmsinedgeandnodeweightsissimilartotermweightingschemesininfor-mationretrieval.Nodeweightsandtreeweightsarecombinedtogetanoverallrelevancescore.Weexperimentedwithad-ditiveandmultiplicativecombinations,andfoundthatbothworkedwellwhentherelativeweightsforthetwoscoreswereappropriatelychosen.Detailsofthesearchalgorithmandtherelevancecomputation,alongwithapreliminaryperformancestudycanbefoundin[3].Althoughafewothersystemsimplementkeywordsearchondatabases(e.g.,[5,1,6])BANKSdiersfromallpriorworkinseveralways:notably,inthetech-niquesforedgeweightcomputationandprestigebasedranking,andtheuseofanin-memorygraphstructureforveryecientsearchwhilekeepingthebulkofthedatadiskresident.TheconnectionsofBANKStore-latedworkaredescribedinmoredetailin[3].2.2ExtensionsTheBANKSsystemsupportsiterativerenementofIfmultiplenodesmatchakeyword,theusercanselectoneormorenodesasbeingrelevantandignoreothers;asanexample,twoauthorsintheDBLPdatabasematchthekeywordsudarshan,andtheusercanchooseoneofthemandexecuteaquerymatchingitwithotherkeywords.Userscanrequestmoreanswerssimilartooneofthedisplayedanswers;similaritycanbedenedonthebasisoftheanswertreestructure.Otherrenementstotunenodeandedgeweightsarealsounderdevelopment.Insteadofdisplayingtreesconsistingofexplicittu-ples,systemdeveloperscanspecifyanswerformatsbasedonthetypeoftherootoftheanswertrees.Forinstance,onecanspecifyauthor,conference/journalandyearbedisplayedwhenevertherootnodeisfrompaperrelation.Wearecurrentlyworkingonimple-mentinganswerformatting,andonsupportingnega-tionanddisjunctioninqueries.3BrowsingTheBANKSsystemprovidesarichinterfacetobrowsedatastoredinarelationaldatabase.Thesystemau-tomaticallygeneratesbrowsableviewsofdatabasere-lationsandqueryresults;nocontentprogrammingoruserinterventionisrequired.Everydisplayedforeignkeyattributevaluebecomesahyperlinktothereferencedtuple.Inaddition,pri-marykeycolumnscanbebrowsedbackwards,tondreferencingtuples,organizedbyreferencingrelations(userscanselectaspecicreferencingrelation).Eachtabledisplayedcomeswithavarietyoftoolsforinteractingwithdata.Columnscanbeprojectedaway(dropped),andselectionscanbeimposedonanycolumn.Forforeignkeycolumns,clickingonjoinresultsinthereferencedtablebeingjoinedin,anditscolumnsalsodisplayed.Thiseliminatestheneedforexplicitlywritingjoinqueriesforthenormalcaseofforeignkeyjoin.Thejoinfeaturecanalsobeusedintheotherdirection,fromaprimarykeytoareferencingforeignkey.Resultscanbegroupedbyacolumn;thisresultsinonlythedistinctvaluesforthatcolumnbeingdisplayed.Theusercanclickonanyofthevaluestoseethetuplesassociatedwiththatvalue.Tuplesinthedisplayedtablecanbesortedbyaspeciedcolumn. Figure3:BrowsingExamples:(a)Samplebrowsingsession(b)PiechartControlsfortheseoperationscanbeaccessedbyclickingonthecolumnnamesinthetableheader.Inaddition,displayeddataispaginated,andschemabrowsingissupported.Figure3(a)showstheresultofbrowsingthethe-sisdatabasestartingwiththestudentrelation,usingapop-upmenuontherollnumberattributetoeectajoinwiththethesisrelationanddroppingseveralcolumns.Thejoinismadepossiblesincethethesislationhasaforeign-keyattributereferencingthedentrelation.Asamplepop-upmenuisshownforthefemailattributewhichreferencesthefacultytable.Hyperlinksinthedisplayeddataareautomaticallygeneratedbythesystem.EachhyperlinkcorrespondstoanSQLquerythatisexecutedwhenauserclicksonthelinks.Thus,allthepagesinthesystemaregen-eratedontheybyexecutingcorrespondingqueriesagainsttheunderlyingrelationaldatabase.Nopre-computationisrequired.BANKStemplatesprovideseveralpredenedwaysofdisplayingdata.Templateinstancesarecustomized,storedinthedatabase,andgivenahyperlinkname,whichisusedtoaccessthetemplate.TheBANKSsystemcurrentlyprovidesfourtypesoftemplates:Cross-tabs(similartoOLAPcross-tabs),withdrill-downfacilities.Thegroup-bytemplateprovidesahierarchicalviewofdata,byspecifyingasequenceofgroupingattributes.Folder-treeviews,whichprovideanotherhierar-chicalviewofdata.Thegraphicalinterfacetemplatepermitsinforma-tiontobedisplayedinbarchartlinechartpiechartformat.HyperlinksareprovidedonthegraphicaldataviaHTMLimagemaps,toallowdrilldownonthedata.Figure3(b)showsanex-amplepiechartgeneratedbyBANKS.Anotherinterestingfeatureoftemplatesisthattheycanbecomposedtogetherinahyperlinked,visualmanner.SeveralexampletemplatesareavailableontheBANKSwebsite.4ConclusionsTosummarize,wehavedevelopedanintegratedsys-temforkeywordsearchingandbrowsingofdatabases.Thesystemhasmanyusefulfeatureswhichallowca-sualuserstoaccessdatabaseinformationinanintu-itivemanner.BANKSenablesalmosteortlessWebpublishingofrelationalandXMLdatathatwouldoth-erwiseremain(atleastpartially)invisibletotheWeb.WehavealsodevelopedaprototypeversionofBANKSthatworksonXMLdata,supportingkey-wordsearchingandscalablebrowsingoflargeXMLdatasets.WeareworkingonintegratingXMLsearch/browsingwiththerestoftheBANKSsystem.References[1]SanjayAgrawal,SurajitChaudhuri,andGautamDas.DBXplorer:Asystemforkeyword-basedsearchoverrelationaldatabases.InProcs.ICDEFeb.2002.[2]PeterBailey,NickCraswell,andDavidHawking.DarkmatterontheWeb.InPosterProceedings,9thWorld-WideWebConference,2000.[3]GauravBhalotia,ArvindHulgeri,CharutaNakhe,SoumenChakrabarti,andS.Sudarshan.Key-wordsearchingandbrowsingindatabasesusingBANKS.InProcs.ICDE,Feb.2002.[4]SergeyBrinandLawrencePage.Theanatomyofalarge-scalehypertextualWebsearchengine.Com-puterNetworksandISDNSystems,30(17),1998.[5]ShaulDar,GadiEntin,ShaiGeva,andEranPal-mon.DTLsDataSpot:Databaseexplorationus-ingplainlanguage.InProcs.VLDB,1998.[6]VagelisHristidisandYannisPapakonstanti-nou.DISCOVER:Keywordsearchinrelationaldatabases.InProcs.VLDB,Aug.2002.
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