Ontology driven Annotation

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  • 1. Ontology driven Annotation

2. What is Semantic web? 3. The Semantic Web visionA web of data that can be processed directly and indirectly bymachines 4. What do we need?Annotated documents with Ontology with metadata aboutcanonical references toentitiesmentioned entities 5. Wikipedia Annotation 6. About WikipediaLarge knowledge base with 3.9Marticle pages in English 7. Automatic Annotation Spotting DisambiguationHeading into the LosAngeles Lakers Tuesdaynight tilt with the GoldenState Warriors, KobeBryant needed 25 pointsto pass Michael Jordan forthe second-most pointsscored by a player for asingle NBA franchise. Hegot 30. We now have adefinitive answer; finally,the debate can end. 8. Existing Wikipedia AnnotatorsWikify DBPedia Spotlight Wikipedia Miner Zemanta ExtractivOpencalaisWikifier 9. Sample from Wikipedia Miner 10. Trie based Spotter 11. Academic and Technical Ontology, Annotators 12. 1212 Motivating VisionNext-Generation Search will beInformation Extraction + Ontology + InferenceObject 1 Albert Einstein was a German-born theoretical physicist h German Scientists Taught at US Universities? Object 3New Jersey is a state in the Northeastern region Object 2Einstein was a guest lecturer at the Institute for Advanced Study in New Jersey 13. Academic and TechnicalOntology 14. AQL script for Techpedia Project Titlecreate view ProjectName asextract regex /Project Title/ with flags CASE_INSENSITIVE on D.text as titlefrom DetaggedDoc D;create view ProjectTitle asselect RightContextTok(P.title,10) as ProjectTitlefrom ProjectName P;output view ProjectTitle; 15. AQL script for course prerequisitecreate view PrerequisiteWord asextract regex /(Prerequisitesns*)(.*)/on D.textreturn group 1 as prereqWord andgroup 2 as prereqfrom DetaggedDoc D;create view prereq asextractP.prereq as match,regex /n/ on P.prereq as boundaryfrom PrerequisiteWord P;create view CoursePrerequisite asextract split using P.boundaryretain left split point on P.matchas CoursePrerequisitefrom prereq Plimit 1;output view CoursePrerequisite; 16. AQL script for Professor Namecreate view ProfessorName as(select CombineSpans(F.fname, L.lname) as Pnamefrom FirstName F, LastName Lwhere FollowsTok(F.fname, L.lname,0,0)consolidate on F.fname using ContainedWithinorder by GetText(F.fname)limit 1)union all(select CombineSpans(F.Nameinitial, L.lname) as Pnamefrom FNameInitial F, LastName Lwhere FollowsTok(F.Nameinitial, L.lname,0,0)consolidate on F.Nameinitial using ContainedWithinorder by GetText(F.Nameinitial)limit 1);16 17. Input Page 18. Output view for Project TitleOutput View ProjectTitle:[Document.text[17-73]:: DESIGN & ANALYSIS OF PRESSUREVES...(1 fields)]ProjectTitle: :DESIGN & ANALYSIS OF PRESSURE VESSEL College :U[Document.text[276-349]::Design and Analysis ofElectrical...(1 fields)]ProjectTitle: :Design and Analysis of Electrical OverheadTraveling Crane College[Document.text[566-623]::Blungers: For Slip and GlazePrep...(1 fields)]ProjectTitle: :Blungers: For Slip and Glaze Preparation College :[Document.text[833-880]::DESIGN OF STEAM CONDENSERn Col...(1 fields)]ProjectTitle: :DESIGN OF STEAM CONDENSER 19. Output view for College NameOutput View CollegeName:[Document.text[68-113]:: U.V.PATEL COLLEGE OFENGINEERING...(1 fields)]CollegeName: : U.V.PATEL COLLEGE OF ENGINEERING Guide[Document.text[349-394]::U.V.PATEL COLLEGE OFENGINEERING...(1 fields)]CollegeName: : U.V.PATEL COLLEGE OF ENGINEERING Guide[Document.text[621-666]::U.V.PATEL COLLEGE OFENGINEERING...(1 fields)]CollegeName: : U.V.PATEL COLLEGE OF ENGINEERING Guide[Document.text[873-918]::U.V.PATEL COLLEGE OFENGINEERING...(1 fields)]CollegeName: : U.V.PATEL COLLEGE OF ENGINEERING 20. Output view for Guide NameOutput View GuideName:[Document.text[116-150]:MR. Bhavesh PatelnTeamMembers(1 fields)]Guide: MR. Bhavesh Patel Team Members [Document.text[397-418]:Mr. Bhavesh P. Patel(1 fields)] Guide: Mr. Bhavesh P. Patel [Document.text[669-680]: PROF. V.B.(1 fields)] Guide: PROF. V.B. [Document.text[921-941]: A.R. ISRANIn Team(1 fields)] Guide: A.R. ISRANI 21. Output view for Team MembersOutput View TeamMembers:[Document.text[153-219]:Jimit Vyas & Mahavir SolankinAbs...(1 fields)]members: Jimit Vyas & Mahavir Solanki Abstract : The significance read[Document.text[437-471]:Vishal A. Patel,Bhavik H. Khamar,(1fields)]members: Vishal A. Patel,Bhavik H. Khamar,[Document.text[704-758]:PATEL JAYRAM ,PATEL KETUL ,PATELTUS...(1 fields)]members: PATEL JAYRAM ,PATEL KETUL ,PATEL TUSHAR Abstract :[Document.text[952-1007]:HARSHAD PATEL,NITIN NAHAR,SANDEEPPA...(1 fields)]members: HARSHAD PATEL,NITIN NAHAR,SANDEEP PARMAR 22. Input CSE Course Page 23. Output view for Course DetailsCourseId: CS 717CourseName: Statistical Relational LearningCoursePrerequisite: N/ACourseHomepage: Not AvailableCourseContent:* What is Relational Learning? Need for RL.* Discussion on thethree elements of relational models: (a) logic for representingtypes, relations and complexdependencies between them, (b)uncertainty, and (c) learning and inferencing* Basics of 0-order and First order logic - includes types of clauses, syntaxand semantics, ....CourseReferences: 1.011 Inductive Logic Programming:Techniques and Applications, N. Lavrac and S. Dzeroski. EllisProfessorName: G.Ramakrishnan 24. Thank You 25. What is annotation? Short description of page/document Explicit v/s Implicit Metadata and not content Type of Annotation Concise description Abbreviation Opinion Web URL annotation like wiki linksearch by Dmitriev, Pavel A. and Eiron, Nadav and Fontoura, Marcus and Shekita, Eugene In Proceedings of the 15th internatio 26. Flow of annotations in searchUsing Annotations in Enterprise Search by Dmitriev, Pavel A. and Eiron, Nadav and Fontoura, Marcus andShekita, Eugene In Proceedings of the 15th international conference on World Wide Web 2006 27. Definition of OntologyA formal, explicit specification of a shared conceptualizationGruber (1993)must be machine understandable not private to some individual, but accepted by a groupan abstract model of some phenomenon in the world formed by identifying thtypes of concepts and constraints must be clearly defined2727 28. Processes to create a DomainOntologyOntology acquisitionAutomatic extraction of ontological knowledge from base vocabularyand domain specific text sourcesMerging into one ontologyRefinement and ExtensionEvaluation and Assessment 28 28