This document describes a system for creating and publishing resumes using semantic web technologies. The system allows users to semantically tag skills and work experience, receives content-based and collaborative recommendations on additional tags, and publishes resumes with RDFa annotations so they can be crawled and understood by semantic agents. Future work includes linking to external data sources like DBpedia and improving methods for ranking nodes in the semantic graph.

1. A Semantic Web enabled System for Résumé Composition and Publication Roberto Mirizzi1, Tommaso Di Noia1, Eugenio Di Sciascio1, Michelantonio Trizio2 2D.O.O.M., Matera, Italy 1Politecnico di Bari, Bari, Italy 1

2. Outlineof the talk Writing a Résumé: elicithidden information Motivation: the needforSemantics in Information Management Proposed System: SemanticTagging Content-basedRecommendation Collaborative FilteringRecommendation RDFaannotation Conclusion and future work 2

3. Writing a Résumé (I) 3

4. Writing a Résumé (II) A lotof information ishidden 4 Internet Systems Consultant, Custom Information Systems, Raleigh, NC January 2007 to December 2009 Responsible for full software development life cycle (SDLC) management of custom applications developed for corporate clients Managed project requirements, milestones and created detailed functional specifications Developed applications using HTML, ASP, Javascript, VBscript, Visual Basic.net 2008, JAVA, Perl, MySQL, PL/SQL HTML, ASP, Javascript Web Development two-yearsexperience Project Manager PL/SQL Oracle VBscript, Javascript, Perl Scriptingprogramminglanguages Java, VisualBasic.net 2008 Object-orientedprogramminglanguages MySQL, PL/SQL Database Management System

5. Motivation WeneedSemanticsbecause: ithelpstoelicithiddenknowledge itallowsanefficientretrievalof a resource 5 I.M.P.A.K.T.reloaded

6. Proposed System http://sisinflab.poliba.it/impakt-reloaded 6

7. Proposed System: SemanticTagging 7 The userstartstotype in some characters or a keyworddescribinghisprofile The system returns a drop-downlistofitemscontaining the characterskeyed in

8. Content-basedrecommendation 8 The userselectsfrom the drop-downlist the keywordthat best suitshisprofile The system generates a tagscloudwithkeywordsrelatedto the choosenone Eachsuggestedconcepthasitsowndescription

10. Knowledgeelicitation 11 The userdrags&drops a tag in histag bag area (e.g. ZendFramework) The system populates the area withall the implicit information relatedto the choosentag

11. Annotating the Work Experience 12 The userannotateshisworkingexperiencebydragging&dropping the tags in the relatedtagsarea Bythis way itispossibleto link eachcompetenceto a specific work experience. Thisallowstoexactlyknowhowmanyyearsofexperiencea candidate has on a givenlanguage The occupation and typeof business are automaticallytaggedaccordingtowhat the usertypes in

12. Previewing and Saving 13 The Résuméisdisplayedforpreviewintoaniframe The europass style isachievedthroughan appropriate CSS The user can printhis CV or saveitfor a local copy but more can bedone …

14. VCARD

15. DOAC

16. IMPAKT

17. …The CV can bepubliclyexposed on the Web, readytobecrawled. ThankstoRDFaannotationanySemanticAgents, after the parsingof the Résuméforextracting RDF triples, couldautomaticallyretrievedetailedinformation about the candidate.

18. Future work (I) 15 exploit the Social Currentontology Linked Data

19. Thank You 16 Q&A

20. Future work (II) 17 Anyway extracting relevant information from DBpedia is much more difficult and complex. The risk is to obtain a lot of useless tags. It is fundamental to find some new measure for ranking the nodes of the RDF-graph.

21. Future work (III) 18 SYSTEM ARCHITECTURE Linked Data graphexploration Ranknodesexploitingexternal information Storeresultsaspairsofnodestogetherwiththeirsimilarity Start typing a tag Query the system forrelevanttags (eg. Dbpediaresources) Show the semantictagcloud Usetagsfordocumentsemanticannotation or forRDFa-enableddocuments Offline classification Online search DBpedia 1 4 RDFaenableddocuments 2 1 SPARQL 3 1 GRAPH EXPLORER TAGS 1 ExternalInformation Sources 3 2 2 3 Source 1 2 WEB INTERFACE STORAGE Source 2 RANKER 3 … 4 Source N I.M.P.A.K.T.revolution and much more iscoming…