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Loditaly2014 new


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Loditaly2014 new

  1. 1. Semantic Technologies for Linked Open Data at the STLab Aldo Gangemi*, Andrea Nuzzolese, Valentina Presutti*, Diego Reforgiato, Alberto Salvati*, Eva Blomqvist, Enrico Daga*, Francesco Draicchio, Paolo Ciancarini°, Sergio Consoli, Silvio Peroni°, Daria Spampinato* CNR Semantic Technology Lab, ISTC-CNR, Rome/Catania ; * ; °
  2. 2. People • STLab@ISTC Aldo Gangemi Valentina Presutti Daria Spampinato Andrea Nuzzolese Diego Reforgiato Stefania Capotosti Sergio Consoli Alessio Iabichella • • STLab@SI Alberto Salvati Gianluca Troiani tes ocia iBo) Ass i (Un Lab T ) arin • S ianc niBo C U olo im ( gle) a ss o P i aN (Go a alvin amit M M) Ciar ing) p IB assi nkö zo ( M lioz ity) n. L i s G iver st (U lfio n A qvi n.) nU U Blom a (Ope pen O Eva ou ( Dag iBo) am co (Un Enri o Ad r io icch sand NR) ra les C D A cci ( sco u ance ntin A Fr STLab (Semantic Technology Lab) è un laboratorio dell’ISTC sco ance Fr (Istituto di Scienze e Tecnologie Cognitive) del CNR, con sedi a Roma e Catania, attivo anche a Bologna e Parigi 2
  3. 3. Outline • The Linked Open Data (LOD) of CNR ! • The Semantic Scout ! • Machine reading for the Semantic Web ! • Knowledge pattern discovery and usage 3
  4. 4. Linked Open Data in Public Administrations A practical experience: and the Semantic Scout Joint work by STLab and the Information Systems unit of CNR Thanks to Alberto Salvati, Enrico Daga, Gianluca Troiani, Andrea Pompili, Angelo Olivieri Past collaboration with Claudio Baldassarre (UN-FAO) and Alfio Gliozzo (now IBM-Watson) 4
  5. 5. Objective and results • Objectives • Publishing CNR data as LOD • Matching the research demand to the research supply in the largest research institution (CNR) in Italy ! • Results • • The CNR ontology network and data available as LOD • Semantic interoperability between heterogeneous data sources • The Semantic Scout - • Expert finding based on competence • Monitoring funding and evolution of different research areas and units • Browsing and reporting capabilities 5
  6. 6. 6
  7. 7. 6
  8. 8. 6
  9. 9. Methods for data conversion, extraction, inference, integration, linking, publishing, and searching 7
  10. 10. Semantic scout Semantic search 8
  11. 11. Semantic scout Browsing 8
  12. 12. Semantic scout Relation explorer 8
  13. 13. Semantic scout Exporting exploration results 8
  14. 14. Semantic scout Automated reporting 8
  15. 15. Machine reading for the Semantic Web
  16. 16. Apache Stanbol • A set of reusable components for semantic content management • To extend traditional content management systems with semantic services accessible as HTTP REST services • Stanbol is the main software result of the EU IP IKS ! • Our contribution: the Knowledge Representation and Reasoning layer of Stanbol • Services used to define and manipulate semantic data models in CMS, i.e., Ontology Network Manager component • Services able to retrieve additional semantic information about content, i.e., Reaoners and Rules components 10
  17. 17. Stanbol in a nutshell NER and linking to LOD datasets 11
  18. 18. FRED E R l fu ST • The Black Hand might not have decided to barbarously assassinate Franz Ferdinand after he arrived in Sarajevo on June 28th, 1914 semantic roles tense co-reference events qualities negation modality dates NER sample RDFa annotation type induction WSD taxonomy inductio The <span xmlns:dbo="" xmlns:dbr="" about="dbr:Black_Hand_(Serbia)" typeof=”dbo:Agent">Black Hand</span> might not have decided to barbarously assassinate <span xmlns:schemaorg="" xmlns:dbr=" resource/" about="dbr:Archduke_Franz_Ferdinand_of_Austria" typeof=”schemaorg:Person”>Franz Ferdinand</ 12 span> after he arrived in <span xmlns:schemaorg="" xmlns:dbr=" resource/" about="dbr:Sarajevo” typeof=”schemaorg:City”>Sarajevo</span> on June 28th, 1914 12
  19. 19. Tìpalo • Motivation • It is difficult to automatically generate enterprise taxonomies from data available as plain documents ! • Objective • To enable automatic generate taxonomies by exploiting the richness of natural language text 13
  20. 20. Typing DBpedia entities with Tìpalo “Pakito is the alias of french electronic dance music artist Julien Ranouil” (cf. Typing NER RE ST fu l Alignment to Dolce Taxonomy induction WSD Alignment to WordNet supersenses 14
  21. 21. Sentilo • Sentilo is a new method of Sentic Computing • i.e., Semantic Sentiment Analysis, which is a new research area ! • Motivations • Sentiment Analysis does not take into account semantic features when computing opinion scores • Semantics can give a lot of information for Sentiment Analysis methods ! • Objectives • • To provide Sentiment Analysis methods with Semantic information To identify more easily and also using semantic information the opinion 15
  22. 22. ul f T S Sentilo E R “Robert is happy because Silvio Berlusconi finally was condemned by judges” Sentiment scores Opinions Sub topics Topic Opinion holder 16
  23. 23. Knowledge pattern discovery
  24. 24. Bottom-up: schema extraction 18
  25. 25. Encyclopedic Knowledge Patterns • 184 Encyclopaedic Knowledge Patterns (EKPs) were discovered by identifying invariances in the structure of Wikipedia page links ! • EKPs are represented as OWL2 ontologies ! • They capture concepts that are typically used by Wikipedia users for describing things of a certain type 19
  26. 26. An EKP for OfficeHolder 20
  27. 27. An EKP for OfficeHolder Formal represenation 20
  28. 28. An EKP for OfficeHolder Access to data 20
  29. 29. An EKP for OfficeHolder Textual grounding From 20
  30. 30. Aemoo • Aemoo exploits EKPs for • Entity summarisation and Exploratory search • Distinguishing between core and peculiar knowledge ! • The data sources are Wikipedia, DBpedia, Twitter, and GoogleNews ! • Aemoo is a KP-aware application • Benefits from KPs for addressing knowledge interaction tasks • Uses KPs as the basic unit of mean for representing, exchanging, as well as reasoning with knolwedge 21
  31. 31. Aemoo UI 22
  32. 32. Conclusions • We have provided a practical overview about how to build Linked Open Data ! • We have provided case studies and scenarios for exploiting Linked Data ! • We have shown Linked Data-compliant algorithms and tools 23
  33. 33. Thank you! 24