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Digital Enterprise Research Institute                                          www.deri.ie




             A Multidimensional Semantic Space
            for Data Model Independent Queries
                       over RDF Data
                 André Freitas, João Gabriel Oliveira, Edward Curry
                                   Seán O’Riain




 Copyright 2009 Digital Enterprise Research Institute. All rights reserved.
Outline
Digital Enterprise Research Institute   www.deri.ie




        Problem Space & Motivation
        Description of the Approach
        Evaluation
        Conclusion & Future Work
Linked Data
Digital Enterprise Research Institute                  www.deri.ie



         Uses the Web infrastructure and standards to
          expose and interlink datasets.

         Linked Data vision:
             The         Web as a single Dataspace.
             Web           of interlinked datasets.
Linked Data: Adoption
Digital Enterprise Research Institute   www.deri.ie
Queries over Linked Data
Digital Enterprise Research Institute                                       www.deri.ie




         Linked Data brings a           fundamental challenge for data
          consumption:
               How to query heterogeneous and distributed datasets?
               At Web scale it is unfeasible for end-users to be aware of the
                location and structure of datasets.


         Demand for new query mechanisms for Linked Data (data
          model independency).
Query/Search Spectrum
Digital Enterprise Research Institute                              www.deri.ie




                                        Adapted from Kauffman et al (2009)
Fundamental Problem
Digital Enterprise Research Institute                                       www.deri.ie


                                        From which university did the wife of
                                        Barack Obama graduate?




            Popescu (2003): Semantic tractability problem.
Semantic Matching Problem
Digital Enterprise Research Institute                             www.deri.ie



       From which university did the wife of Barack Obama graduate?
Semantic Matching Problem
Digital Enterprise Research Institute                             www.deri.ie



       From which university did the wife of Barack Obama graduate?




      Entity identification
Semantic Matching Problem
Digital Enterprise Research Institute                             www.deri.ie



       From which university did the wife of Barack Obama graduate?




      Entity search
Semantic Matching Problem
Digital Enterprise Research Institute                             www.deri.ie



       From which university did the wife of Barack Obama graduate?




          Approximate
        semantic matching
Semantic Matching Problem
Digital Enterprise Research Institute                             www.deri.ie



       From which university did the wife of Barack Obama graduate?




          Approximate
        semantic matching
Semantic Matching Problem
Digital Enterprise Research Institute                             www.deri.ie



       From which university did the wife of Barack Obama graduate?




          Approximate
        semantic matching
Semantic Matching Problem
Digital Enterprise Research Institute                             www.deri.ie



       From which university did the wife of Barack Obama graduate?




       Structural matching
Semantic Matching Problem
Digital Enterprise Research Institute                             www.deri.ie



       From which university did the wife of Barack Obama graduate?


                                        T- Space
Strategy
Digital Enterprise Research Institute                 www.deri.ie




        Best-effort query model (ranked results).
        Use of a distributional semantic model.
        Two phase search process combining entity search
         with spreading activation search.
Digital Enterprise Research Institute                 www.deri.ie




                                  Proposed Approach
Query Approach Rationale
Digital Enterprise Research Institute   www.deri.ie
Query Approach Rationale
Digital Enterprise Research Institute   www.deri.ie
Query Approach Rationale
Digital Enterprise Research Institute   www.deri.ie
Query Approach Rationale
Digital Enterprise Research Institute   www.deri.ie




          Final Query- Data Matching:
Semantic Relatedness
Digital Enterprise Research Institute                   www.deri.ie


        Computation of a measure of “semantic proximity”
         between two terms.
        Allows a semantic approximate matching between
         query terms and dataset terms.
        Most existing approaches use WordNet-based
         solutions for approximate semantic matching.
        Distributional semantic approaches address these
         limitations.
Distributional Semantics
Digital Enterprise Research Institute                                      www.deri.ie




        Assumption: the context surrounding a given word
         in a text provides important information about its
         meaning.
        Meaning is mediated by word distribution in the
         corpora.
        Simplified semantic model.

         Opera is an art form in which singers and musicians perform a
         dramatic work combining text (called a libretto) and musical score.
         Opera is part of the Western classical music tradition. Opera
         incorporates many of the elements of spoken theatre, such as acting,
         scenery, and costumes and sometimes includes dance. The
         performance is typically given in an opera house, accompanied by an
         orchestra or smaller musical ensemble.
Explicit Semantic Analysis (ESA)
Digital Enterprise Research Institute                        www.deri.ie




        Based on Wikipedia.
        Interpretation vector using Wikipedia articles titles.
Building the T- Space (Steps)
Digital Enterprise Research Institute                 www.deri.ie




        Building the distributional semantic model using
         ESA.
        Construction of instances spaces (TF/IDF).
        Construction of classes spaces (ESA).
        Construction of relation spaces (ESA).
Building the T- Space
Digital Enterprise Research Institute                                      www.deri.ie




                                                  relations




              instances                                       properties



                                        classes
Building the T- Space
Digital Enterprise Research Institute   www.deri.ie
Instances
Digital Enterprise Research Institute   www.deri.ie
Building the T- Space
Digital Enterprise Research Institute   www.deri.ie
Classes
Digital Enterprise Research Institute      www.deri.ie




                                        Universal
                                        ESA Space
Building the T- Space
Digital Enterprise Research Institute   www.deri.ie
Relations
Digital Enterprise Research Institute       www.deri.ie




                                        Universal
                                        ESA Space
Building the T- Space
Digital Enterprise Research Institute   www.deri.ie
Querying the T- Space
Digital Enterprise Research Institute   www.deri.ie
Querying the T- Space
Digital Enterprise Research Institute   www.deri.ie
Querying the T- Space
Digital Enterprise Research Institute   www.deri.ie
Querying the T- Space
Digital Enterprise Research Institute   www.deri.ie
Digital Enterprise Research Institute                       www.deri.ie




                                        Treo (Irish): Route, path
Digital Enterprise Research Institute                www.deri.ie




                                        Evaluation
Quality of Results
Digital Enterprise Research Institute                                                  www.deri.ie


          QALD DBPedia Training Set.
          50 natural language queries.
          DBpedia 3.6.

                                        Full DBPedia QuerySet (50 queries)
                Avg. Precision                Avg. Recall     MRR       % of queries
                                                                         answered
                        0.482                    0.491       0.516           58%


                                  Partial DBPedia QuerySet (38 queries)
                Avg. Precision                Avg. Recall     MRR       % of queries
                                                                         answered
                        0.634                   0. 645       0.679           76%
Error Distribution
Digital Enterprise Research Institute   www.deri.ie
Conclusion & Future Work
Digital Enterprise Research Institute                                    www.deri.ie


          The T-Space semantic model shows a promising direction for
           providing data model independent queries over RDF data.
          Improvement of semantic tractability.
          The distributional semantic model supports a flexible
           matching between query terms and dataset terms in a best-
           effort scenario.



          Further improvements are needed:
                 QA features (e.g. answer type detection, operators).
                 User feedback mechanisms (disambiguation).
                 Entity recognition for complex classes.

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A Multidimensional Semantic Space for Data Model Independent Queries over RDF Data

  • 1. Digital Enterprise Research Institute www.deri.ie A Multidimensional Semantic Space for Data Model Independent Queries over RDF Data André Freitas, João Gabriel Oliveira, Edward Curry Seán O’Riain  Copyright 2009 Digital Enterprise Research Institute. All rights reserved.
  • 2. Outline Digital Enterprise Research Institute www.deri.ie  Problem Space & Motivation  Description of the Approach  Evaluation  Conclusion & Future Work
  • 3. Linked Data Digital Enterprise Research Institute www.deri.ie  Uses the Web infrastructure and standards to expose and interlink datasets.  Linked Data vision:  The Web as a single Dataspace.  Web of interlinked datasets.
  • 4. Linked Data: Adoption Digital Enterprise Research Institute www.deri.ie
  • 5. Queries over Linked Data Digital Enterprise Research Institute www.deri.ie  Linked Data brings a fundamental challenge for data consumption:  How to query heterogeneous and distributed datasets?  At Web scale it is unfeasible for end-users to be aware of the location and structure of datasets.  Demand for new query mechanisms for Linked Data (data model independency).
  • 6. Query/Search Spectrum Digital Enterprise Research Institute www.deri.ie Adapted from Kauffman et al (2009)
  • 7. Fundamental Problem Digital Enterprise Research Institute www.deri.ie From which university did the wife of Barack Obama graduate?  Popescu (2003): Semantic tractability problem.
  • 8. Semantic Matching Problem Digital Enterprise Research Institute www.deri.ie From which university did the wife of Barack Obama graduate?
  • 9. Semantic Matching Problem Digital Enterprise Research Institute www.deri.ie From which university did the wife of Barack Obama graduate? Entity identification
  • 10. Semantic Matching Problem Digital Enterprise Research Institute www.deri.ie From which university did the wife of Barack Obama graduate? Entity search
  • 11. Semantic Matching Problem Digital Enterprise Research Institute www.deri.ie From which university did the wife of Barack Obama graduate? Approximate semantic matching
  • 12. Semantic Matching Problem Digital Enterprise Research Institute www.deri.ie From which university did the wife of Barack Obama graduate? Approximate semantic matching
  • 13. Semantic Matching Problem Digital Enterprise Research Institute www.deri.ie From which university did the wife of Barack Obama graduate? Approximate semantic matching
  • 14. Semantic Matching Problem Digital Enterprise Research Institute www.deri.ie From which university did the wife of Barack Obama graduate? Structural matching
  • 15. Semantic Matching Problem Digital Enterprise Research Institute www.deri.ie From which university did the wife of Barack Obama graduate? T- Space
  • 16. Strategy Digital Enterprise Research Institute www.deri.ie  Best-effort query model (ranked results).  Use of a distributional semantic model.  Two phase search process combining entity search with spreading activation search.
  • 17. Digital Enterprise Research Institute www.deri.ie Proposed Approach
  • 18. Query Approach Rationale Digital Enterprise Research Institute www.deri.ie
  • 19. Query Approach Rationale Digital Enterprise Research Institute www.deri.ie
  • 20. Query Approach Rationale Digital Enterprise Research Institute www.deri.ie
  • 21. Query Approach Rationale Digital Enterprise Research Institute www.deri.ie Final Query- Data Matching:
  • 22. Semantic Relatedness Digital Enterprise Research Institute www.deri.ie  Computation of a measure of “semantic proximity” between two terms.  Allows a semantic approximate matching between query terms and dataset terms.  Most existing approaches use WordNet-based solutions for approximate semantic matching.  Distributional semantic approaches address these limitations.
  • 23. Distributional Semantics Digital Enterprise Research Institute www.deri.ie  Assumption: the context surrounding a given word in a text provides important information about its meaning.  Meaning is mediated by word distribution in the corpora.  Simplified semantic model. Opera is an art form in which singers and musicians perform a dramatic work combining text (called a libretto) and musical score. Opera is part of the Western classical music tradition. Opera incorporates many of the elements of spoken theatre, such as acting, scenery, and costumes and sometimes includes dance. The performance is typically given in an opera house, accompanied by an orchestra or smaller musical ensemble.
  • 24. Explicit Semantic Analysis (ESA) Digital Enterprise Research Institute www.deri.ie  Based on Wikipedia.  Interpretation vector using Wikipedia articles titles.
  • 25. Building the T- Space (Steps) Digital Enterprise Research Institute www.deri.ie  Building the distributional semantic model using ESA.  Construction of instances spaces (TF/IDF).  Construction of classes spaces (ESA).  Construction of relation spaces (ESA).
  • 26. Building the T- Space Digital Enterprise Research Institute www.deri.ie relations instances properties classes
  • 27. Building the T- Space Digital Enterprise Research Institute www.deri.ie
  • 28. Instances Digital Enterprise Research Institute www.deri.ie
  • 29. Building the T- Space Digital Enterprise Research Institute www.deri.ie
  • 30. Classes Digital Enterprise Research Institute www.deri.ie Universal ESA Space
  • 31. Building the T- Space Digital Enterprise Research Institute www.deri.ie
  • 32. Relations Digital Enterprise Research Institute www.deri.ie Universal ESA Space
  • 33. Building the T- Space Digital Enterprise Research Institute www.deri.ie
  • 34. Querying the T- Space Digital Enterprise Research Institute www.deri.ie
  • 35. Querying the T- Space Digital Enterprise Research Institute www.deri.ie
  • 36. Querying the T- Space Digital Enterprise Research Institute www.deri.ie
  • 37. Querying the T- Space Digital Enterprise Research Institute www.deri.ie
  • 38. Digital Enterprise Research Institute www.deri.ie Treo (Irish): Route, path
  • 39. Digital Enterprise Research Institute www.deri.ie Evaluation
  • 40. Quality of Results Digital Enterprise Research Institute www.deri.ie  QALD DBPedia Training Set.  50 natural language queries.  DBpedia 3.6. Full DBPedia QuerySet (50 queries) Avg. Precision Avg. Recall MRR % of queries answered 0.482 0.491 0.516 58% Partial DBPedia QuerySet (38 queries) Avg. Precision Avg. Recall MRR % of queries answered 0.634 0. 645 0.679 76%
  • 41. Error Distribution Digital Enterprise Research Institute www.deri.ie
  • 42. Conclusion & Future Work Digital Enterprise Research Institute www.deri.ie  The T-Space semantic model shows a promising direction for providing data model independent queries over RDF data.  Improvement of semantic tractability.  The distributional semantic model supports a flexible matching between query terms and dataset terms in a best- effort scenario.  Further improvements are needed:  QA features (e.g. answer type detection, operators).  User feedback mechanisms (disambiguation).  Entity recognition for complex classes.