SWOC - Semantic Wonder Cloud: Exploratory Search in DBpedia - SWIM 2010


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Inspired by the Google Wonder Wheel, we present Semantic Wonder Cloud (SWOC): a tool that helps users in knowledge exploration within the DBpedia dataset by adopting a hybrid approach. We describe both the architecture and the user interface. The system exploits not only pure semantic connections in the underlying RDF graph but it mixes the meaning of such information with external non-semantic knowledge sources, such as web search engines and tagging systems. Semantic Wonder Cloud allows the user to explore the relations between resources of knowledge domain via a simple and intuitive graphical interface.
The system is available at http://sisinflab.poliba.it/semantic-wonder-cloud/index/

SWIM 2010 - 2nd International Workshop on Semantic Web Information Management

The paper won the "Best Workshop Paper Award" at 10th International Conference on Web Engineering, ICWE 2010, held in Vienna, July 05-09, 2010.

Presented by Roberto Mirizzi (http://sisinflab.poliba.it/mirizzi -
roberto.mirizzi -at- gmail.com)

Vienna (Austria), July 05, 2010

Published in: Technology, Education
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SWOC - Semantic Wonder Cloud: Exploratory Search in DBpedia - SWIM 2010

  1. 1. Semantic Wonder Cloud: exploratory search in DBpedia<br />Roberto Mirizzi1, Azzurra Ragone1,2, <br />Tommaso Di Noia1, Eugenio Di Sciascio1<br />1Politecnico di Bari<br />Via Orabona, 4<br />70125 Bari (ITALY)<br />2Universityof Trento<br />Via Sommarive, 14<br />38100 Trento (ITALY)<br />
  2. 2. Outline<br /><ul><li>Exploratory search
  3. 3. SWOC (Semantic Wonder Cloud): the interface
  4. 4. Background technologies
  5. 5. SWOC: how it works
  6. 6. Ranking in Linked Data (DBpedia)
  7. 7. Conclusion and Future work</li></li></ul><li>WhatisExploratorySearch?<br />[Gary Marchionini. ExploratorySearch: FromFindingtounderstanding. Communicationsof the ACM, 49(4): 41-46, 2006]<br />
  8. 8. Inspiration: Google Wonder Wheel<br />ExploratorySearch in Google…<br />…nice, butthereis no “semantics” in it. <br />You can notdiscovernewknowledgeexploiting the meaningof a term (keyword/tag/query)<br />
  9. 9. SWOC: SemanticWonderCloud<br />http://sisinflab.poliba.it/semantic-wonder-cloud/index/<br />
  10. 10. Whatisbehind SWOC? (I)<br />
  11. 11. Whatisbehind SWOC? (II)<br />
  12. 12. What is behind SWOC? (III)<br />…<br />…<br />Knowledge_representation<br />Data_management<br />Internet_architecture<br />…<br />XML-based_standards<br />Distribute_computing_architecture<br />Semantic_Web<br />Web_services<br />Semantic_Web_Services<br />OWL-S<br />Triplestores<br />Folksonomy<br />…<br />Web_service_specifications<br />Internet_search<br />Enterprise_application_integration<br />Microformtas<br />…<br />…<br />Legend<br />skos:subject<br />skos:broader<br />Category<br />Article<br />
  13. 13. The functionalarchitecture<br />Back-end<br />Google<br />Bing<br />SPARQL<br />Ext. Info Sources<br />Yahoo!<br />Graph Explorer<br />Context Analyzer<br />Delicious<br />Ranker<br />DBpedia Lookup Service<br />Storage<br />XML documents<br />SQL2XML Converter<br />Graph Generator<br />Resource Selector<br />Interface<br />
  14. 14. DBpedia-Ranker: ranking<br />Graph-based ranking<br />?r1<br />?r2<br />isSimilar<br />hasValue<br />v<br />Externalsources-based ranking<br />
  15. 15. DBpedia-Ranker: contextanalysis<br />The samesimilaritymeasureisused in the contextanalysis<br />C<br />?c1<br />Algorithm:<br />If(v>THRESHOLD) then<br /> r1belongsto the context;<br />add r1to the graphexplorationqueue<br />Else<br /> r1doesnotbelongto the context;<br />exclude r1fromgraphexploration<br />EndIf<br />?c2<br />belongsTo<br />?r1<br />?c…<br />?cN<br />hasValue<br />Example:<br />C = {ProgrammingLanguages, Databases, Software}<br />DoesDennis Ritchiebelongsto the givencontext?<br />v<br />
  16. 16. Evaluation (I)<br />http://sisinflab.poliba.it/evaluation<br />
  17. 17. Evaluation (II)<br />http://sisinflab.poliba.it/evaluation/data<br />
  18. 18. Conclusion<br /><ul><li>SWOC: a tool for exploratory search
  19. 19. Ranking algorithm for RDF graphs</li></ul>Future work<br /><ul><li>Integrate resultsfromsearchengines in SWOC
  20. 20. Test ouralgorithmswithdifferentdomains
  21. 21. Extract more fine grainedcontexts
  22. 22. Enrich the extractedcontextusingalsorelevantproperties
  23. 23. Integrateourapproachwithrealexistingsystems
  24. 24. Use the core system toautomaticallyextractrelevanttags (concepts) from a document (or from a collectionofdocuments) exploitingtoolsfornamedentitiesextraction</li></li></ul><li>Q&A<br />Semantic Wonder Cloud: exploratory search in DBpedia (SWIM 2010)<br />Thanksforyourattention!<br />Seeyoulater at the demo sessionand on Fridaywith…<br />Ranking the Linked Data: the case of DBpedia (ICWE 2010)<br />Roberto Mirizzi, AzzurraRagone, Tommaso Di Noia, Eugenio Di Sciascio<br />mirizzi@deemail.poliba.it, ragone@disi.unitn.it, {ragone,dinoia,disciascio}@poliba.it<br />