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Mushroom Effect or Why You Need Knowledge Graphs for Dialogue Systems

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LSWT2019 Talk by Dr. Michael Galkin, Smart Data Analytics, Fraunhofer IAIS

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Mushroom Effect or Why You Need Knowledge Graphs for Dialogue Systems

  1. 1. Michael Galkin 7. Leipziger Semantic Web Tag 22.05.2019 The Mushroom Effect Or Why You Need Knowledge Graphs for Dialogue Systems Dr. Michael Galkin Fraunhofer IAIS & Smart Data Analytics Dresden
  2. 2. Michael Galkin 7. Leipziger Semantic Web Tag 22.05.2019 Outline Background Mushrooms? With KG Flavors About us: CEE AI Dresden
  3. 3. Michael Galkin 7. Leipziger Semantic Web Tag 22.05.2019 Background We build conversational AI platforms
  4. 4. Michael Galkin 7. Leipziger Semantic Web Tag 22.05.2019 Background We build conversational AI platforms Powered by knowledge graphs
  5. 5. Michael Galkin 7. Leipziger Semantic Web Tag 22.05.2019 Background We build conversational AI platforms Powered by knowledge graphs Obtained by integrating heterogeneous data
  6. 6. Michael Galkin 7. Leipziger Semantic Web Tag 22.05.2019 Mushrooms? Berlin Hbf What is this building? Q
  7. 7. Michael Galkin 7. Leipziger Semantic Web Tag 22.05.2019 Mushrooms? Berlin Hbf What is this building? Q This is Berlin HauptbahnhofA
  8. 8. Michael Galkin 7. Leipziger Semantic Web Tag 22.05.2019 Mushrooms? What is this building? Q This is Berlin HauptbahnhofA What is its architectural style? Q Berlin Hbf
  9. 9. Michael Galkin 7. Leipziger Semantic Web Tag 22.05.2019 What is its architectural style?
  10. 10. Michael Galkin 7. Leipziger Semantic Web Tag 22.05.2019 What is its architectural style? Wikipedia
  11. 11. Michael Galkin 7. Leipziger Semantic Web Tag 22.05.2019 What is its architectural style? SQuAD
  12. 12. Michael Galkin 7. Leipziger Semantic Web Tag 22.05.2019 What is its architectural style? MS MARCO
  13. 13. Michael Galkin 7. Leipziger Semantic Web Tag 22.05.2019 What is its architectural style? HotPot QA
  14. 14. Michael Galkin 7. Leipziger Semantic Web Tag 22.05.2019 Mushrooms! What is this building? Q This is Berlin HauptbahnhofA What is its architectural style? Q MushroomA
  15. 15. Michael Galkin 7. Leipziger Semantic Web Tag 22.05.2019 Mushrooms! What is its architectural style? Q
  16. 16. Michael Galkin 7. Leipziger Semantic Web Tag 22.05.2019 Mushrooms! What is its architectural style? Q ✓ its = Berlin Hauptbahnhof ✓ In Berlin ✓ Concept ~ Style ❌ Applicable to the city concept, not architectural style of the station ❌ Close, but not correct
  17. 17. Michael Galkin 7. Leipziger Semantic Web Tag 22.05.2019 With KG flavors Can mushrooms be an architectural style?
  18. 18. Michael Galkin 7. Leipziger Semantic Web Tag 22.05.2019 With KG flavors Can mushrooms be an architectural style? Probably not If not, what can be an appropriate value?
  19. 19. Michael Galkin 7. Leipziger Semantic Web Tag 22.05.2019 So why you need graphs? Implicit or explicit constraints on produced answersHow many children does Berlin Hbf have?
  20. 20. Michael Galkin 7. Leipziger Semantic Web Tag 22.05.2019 So why you need graphs? Implicit or explicit constraints on produced answers - reduce candidates space - help to fight the mushroom effect - ontologies help How many children does Berlin Hbf have? Train stations don’t have kids
  21. 21. Michael Galkin 7. Leipziger Semantic Web Tag 22.05.2019 So why you need graphs? Implicit or explicit constraints on produced answers - reduce candidates space - help to fight the mushroom effect - ontologies help Complex QA via (sub)graphs aggregations What is the busiest train station in Germany? How many children does Berlin Hbf have? Train stations don’t have kids
  22. 22. Michael Galkin 7. Leipziger Semantic Web Tag 22.05.2019 So why you need graphs? Implicit or explicit constraints on produced answers - reduce candidates space - help to fight the mushroom effect - ontologies help Complex QA via (sub)graphs aggregations What is the busiest train station in Germany? select ?station ?visits where { ?station wdt:P31 wd:Q18543139 . # central stations ?station wdt:P17 wd:Q183 . # in Germany ?station wdt:P1373 ?visits . # daily visits } ORDER BY DESC(?visits) LIMIT 1 # sort How many children does Berlin Hbf have? Train stations don’t have kids Hamburg Hbf
  23. 23. Michael Galkin 7. Leipziger Semantic Web Tag 22.05.2019 So why you need graphs? Graphs significantly improve reasoning compared to sole natural language inference Takeaway 1
  24. 24. Michael Galkin 7. Leipziger Semantic Web Tag 22.05.2019 So why you need graphs? Graphs significantly improve reasoning compared to sole natural language inference Reasoning outcomes are explainable and traceable Takeaway 1 Takeaway 2
  25. 25. Michael Galkin 7. Leipziger Semantic Web Tag 22.05.2019 KDDS Knowledge-driven in-car dialogue system (EN/DE) Full DBpedia 2019 (wikidata branch) > 50M entities > 4B triples
  26. 26. Michael Galkin 7. Leipziger Semantic Web Tag 22.05.2019 KDDS @ Hannover-Messe Building KGs from enterprise sources is still a challenge
  27. 27. Michael Galkin 7. Leipziger Semantic Web Tag 22.05.2019 KDDS @ Hannover-Messe Building KGs from enterprise sources is still a challenge Depth of knowledge vs variety of domains
  28. 28. Michael Galkin 7. Leipziger Semantic Web Tag 22.05.2019 KDDS @ Hannover-Messe Building KGs from enterprise sources is still a challenge Depth of knowledge vs variety of domains Explainability is crucial
  29. 29. Michael Galkin 7. Leipziger Semantic Web Tag 22.05.2019 Fraunhofer IAIS Standort Dresden ML2R National Competence Center for Machine Learning Rhein-Ruhr Fraunhofer-Alliance Big Data AI The biggest Fraunhofer alliance with > 30 institutes led by IAIS AI4EU EU Lighthouse Project for AI International Data Spaces Association Data sovereignty for Big Data and AI, 100+ companies CEE AI Center for Explainable and Efficient AI Technologies with TU Dresden Fraunhofer Center for Machine Learning IAIS-led part of Fraunhofer Cluster of Excellence Cognitive Internet Technologies
  30. 30. Michael Galkin 7. Leipziger Semantic Web Tag 22.05.2019 Fraunhofer IAIS Dresden Center for Efficient and Explainable AI Prof. FitzekProf. Lehmann ● Efficient AI ○ Hardware and software are usually decoupled instead of embedded ○ 100-times more energy efficient by 2030 ● Explainable AI ○ Make AI more traceable ○ Make AI decisions more explainable
  31. 31. Michael Galkin 7. Leipziger Semantic Web Tag 22.05.2019 Center for Explainable and Efficient AI

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