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Food Informatics-Sharing Food

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  • fyisisch, chemisch, sensorisch
  • Much food-related knowledge is available in various research fields Much food-related knowledge is available in various research fields
  • Research: Wageningen UR, TNO, Vrije Universiteit Amsterdam, University of Amsterdam IT partners: IBM Business: Unilever, Friesland Foods
  • Transcript

    • 1. Food Informatics: Sharing Food Knowledge for Research & Development Nicole Koenderink , Lars Hulzebos, Hajo Rijgersberg, Jan Top [email_address] Agrotechnology & Food Innovations Wageningen UR, The Netherlands
    • 2. Custard Why does custard taste so creamy? AOS Workshop - Use of Ontologies in Applications – Nicole Koenderink Movement of tongue Percentage of fat particles Bite size Oral texture Perception of thickness Temperature Colour Odour Amount of saliva
    • 3. Outline
      • Problem & Purpose
      • Approach
      • First Results
      • Conclusion & Future Work
      • Problem & Purpose
      AOS Workshop - Use of Ontologies in Applications – Nicole Koenderink
    • 4. Problem & Purpose – Food Informatics
      • Goal: make food-related information available for food researchers.
      • Pay attention to:
        • Relevance
        • Reliability/Quality
        • Timeliness
      AOS Workshop - Use of Ontologies in Applications – Nicole Koenderink
    • 5. Problem & Purpose – Food Informatics
      • Food Informatics: develop tools and technologies to enable application of ontologies for knowledge sharing
      • Collaboration between:
        • Research
        • IT partners
        • Business
      AOS Workshop - Use of Ontologies in Applications – Nicole Koenderink
    • 6. Problem & Purpose – Food Informatics However…. only few ontologies exist dedicated to the field of food.
      • Our first purpose:
      • collect “structured” knowledge on the field of food
      • support users in creating relevant food ontologies
      AOS Workshop - Use of Ontologies in Applications – Nicole Koenderink
    • 7. Outline
      • Problem & Purpose
      • Approach
      • First Results
      • Conclusion & Future Work
      • Approach
      AOS Workshop - Use of Ontologies in Applications – Nicole Koenderink
    • 8. Approach – relevant knowledge
      • Ontology contains domain knowledge
      • Without defined purpose it is impossible to determine which knowledge is relevant and thus which knowledge should be added to ontology
      • Traditionally: (purpose) independent representation of domain knowledge
      AOS Workshop - Use of Ontologies in Applications – Nicole Koenderink
    • 9. Approach – knowledge acquisition
      • Complete oral K.A. process:
      • Tedious & time-consuming for expert
      • Complete text mining process:
      • Too generic for purpose-oriented ontology
      Our approach AOS Workshop - Use of Ontologies in Applications – Nicole Koenderink Interviews, Oral K.A. Text mining automation
    • 10. Approach (1) Goal definition AOS Workshop - Use of Ontologies in Applications – Nicole Koenderink
    • 11. Approach (2) Search potential relevant triples AOS Workshop - Use of Ontologies in Applications – Nicole Koenderink
    • 12. Approach (3) & (6) Potential relevant triples AOS Workshop - Use of Ontologies in Applications – Nicole Koenderink
    • 13. Approach (4) Search new information AOS Workshop - Use of Ontologies in Applications – Nicole Koenderink
    • 14. Approach (5) Parsed triples AOS Workshop - Use of Ontologies in Applications – Nicole Koenderink
    • 15. Outline
      • Problem & Purpose
      • Approach
      • First Results
      • Conclusion & Future Work
      • First Results
      AOS Workshop - Use of Ontologies in Applications – Nicole Koenderink
    • 16. First Results
      • Case study: Research Management System catalogue food according to properties of ingredients
      • Needed: ontology of food ingredients
      AOS Workshop - Use of Ontologies in Applications – Nicole Koenderink
    • 17.
      • Triple collection filled with
        • CABS thesaurus
        • NALT thesaurus
        • AGCOM thesaurus
      • Total amount of triples (May): approx. 350,000
      First Results AOS Workshop - Use of Ontologies in Applications – Nicole Koenderink Total: 651640 triples
      • IARC thesaurus
      • USDA thesaurus
      • CARAT thesaurus
      • www.bulkfoods.com
      • Unilever triples
    • 18. First Results 6th AOS Workshop - Use of Ontologies in Applications
    • 19. First Results
    • 20. First Results
    • 21. First Results - 0 0 30,796 12 50% 3 6 30,791 11 13% 8 62 30,764 10 24% 36 152 30,523 9 28% 150 532 29,783 8 17% 392 2,274 27,183 7 27% 775 2,831 19,660 6 52% 1,001 1,934 9,548 5 55% 552 1,004 3,505 4 57% 182 319 885 3 67% 55 83 181 2 100% 7 7 - 1 % relevant new concepts # of relevant new concepts # of new concepts cumulative # proposed triples step
    • 22. First Results
      • Result: basis for ontology with 3150 concepts within 4 hours
      • Number of relations per concept varies
    • 23. Conclusions
      • Purpose is necessary to define relevant knowledge; ontology is purpose-dependent.
      • With the proposed semi-automatic knowledge acquisition method, the expert decides which knowledge is relevant
      • Observation: it is difficult for an expert to stay focused on the objective of the ontology.
      AOS Workshop - Use of Ontologies in Applications – Nicole Koenderink
    • 24. Conclusions
      • The proposed two-step approach has as advantage that in a short period many possibly relevant concepts are indicated
      • A drawback of this method is that the expert has to assess each time a huge amount of triples
      • Future work: the method needs a “filter routine” to assist the expert in this process.
      AOS Workshop - Use of Ontologies in Applications – Nicole Koenderink
    • 25. Conclusions
      • The relations in the thesaurus are general
      • Future work: the expert must be enabled to redefine relations
        • Example: potato starch is related to potato
        • is changed to
        • potato starch is made from potato
        • or
        • potato starch is substance of potato
      AOS Workshop - Use of Ontologies in Applications – Nicole Koenderink
    • 26. Future Work
      • Design filter routine
      • Implement redefinition support
      • Expand the triple collection with triples obtained from less structured documents
      • Next step: transform the found collection of concepts and relations to an ontology
      AOS Workshop - Use of Ontologies in Applications – Nicole Koenderink
    • 27. Acknowledgements
      • Thanks to:
      • Jannie van Beek
      • Remco van Brakel
      • the Dutch Ministry of Education, Culture and Science
      • the Dutch Ministry of Economic Affairs
      • the Ministry of Agriculture
      Questions? [email_address] AOS Workshop - Use of Ontologies in Applications – Nicole Koenderink
    • 28.  
    • 29. Parsing triples – Example adoption UF: product introduction NT: adoption behaviour adoption process adoption behaviour BT: adoption behaviour adoption process BT: adoption
    • 30. Parsing triples – Example <TERM> := [A-z]1* <RELATION> := [A-z]1* + “:” <BLANK> := empty line <TERM> [ <RELATION> [ <TERM>]1* ]1* <BLANK> <OBJECT> <PREDICATE> <SUBJECT> 1 1* 1*
    • 31. Parsing triples – Example adoption behaviour BT adoption adoption NT adoption process adoption NT adoption behaviour adoption UF product introduction Object Predicate Subject