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OntoGen

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http://ontogen.ijs.si

http://ontogen.ijs.si

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  • 1. Semi-Automatic Data-Driven Ontology Construction System Blaz Fortuna, Marko Grobelnik, Dunja Mladenic Jozef Stefan Institute http://ontogen.ijs.si OntoGen
  • 2. How does it work?
    • OntoGen suggests concepts
      • Suggestions are generated automatically
        • … from the text corpus by clustering similar documents
        • … based on user query
        • … through text corpus map
    • User selects appropriate suggestions and adds them to the ontology
      • OntoGen helps deciding which suggestions to include
        • … by extracting main keywords from the documents
        • … with ontology and concept visualizations
        • … by list documents behind concepts
    • Behind each concept there is a set of documents
      • Documents are automatically assigned to concepts
      • Document assignments can be edited manually
    HCII2007, July 26th Blaz Fortuna, Jozef Stefan Institute, Slovenia
  • 3. Main Features
    • Interactive user interface
      • User can interact in real-time with the integrated machine learning and text mining methods
    • Concept discovery methods:
      • Unsupervised
        • System provides suggestions
      • Supervised
        • Concept learning
        • Concept visualization
    • Methods for helping at understanding the discovered concepts:
      • Keyword extraction
        • Generates a list of characteristic keywords of a given concept
      • Concept visualization
        • Creates a map of documents from a given concept
        • Also available as a separate tool named Document Atlas
          • http://docatlas.ijs.si
    HCII2007, July 26th Blaz Fortuna, Jozef Stefan Institute, Slovenia
  • 4. Main view Concept hierarchy List of suggested sub-concepts Ontology visualization Selected concept
  • 5. Concept suggestion Selected concept Suggested subconcepts Add new concept New concept HCII2007, July 26th Blaz Fortuna, Jozef Stefan Institute, Slovenia
  • 6. Personalized suggestions UK takeovers and mergers The following are additions and deletions to the takeovers and mergers list for the week beginning August 19, as provided by the Takeover … Lloyd’s CEO questioned in recovery suit in U.S. Ronald Sandler, chief executive of Lloyd's of London, on Tuesday underwent a second day of court interrogation about … HCII2007, July 26th Blaz Fortuna, Jozef Stefan Institute, Slovenia Topics view Countries view
  • 7. Concept learning Query New Concept Finish HCII2007, July 26th Blaz Fortuna, Jozef Stefan Institute, Slovenia
  • 8. Concept’s instances visualization
    • Instances are visualized as points on 2D map
      • The distance between two instances on the map correspond to their content similarity
      • Characteristic keywords are shown for all parts of the map
    • User can select groups of instances on the map to create sub-concepts.
    HCII2007, July 26th Blaz Fortuna, Jozef Stefan Institute, Slovenia
  • 9. Concept management Concept’s details Concept’s instance management Selected concept Keywords Selected instance
  • 10. Adding new documents to ontology New documents Classification of selected document Content of selected document HCII2007, July 26th Blaz Fortuna, Jozef Stefan Institute, Slovenia Selected document
  • 11. Evaluation
    • First prototype was successfully used in several commercial projects:
      • Applied in multiple domains: business, legislations and digital libraries
      • Users were always domain experts with limited knowledge and experience with ontology construction / knowledge engineering
      • Valuable data from first trails was used as input for the interface design of the second prototype (the one presented here).
    • Feedback from the users of the second prototype
      • Main impression was that the tool saves time and is especially useful when working with large collections of documents
      • Among main disadvantages were abstraction and unattractive look
      • Many users use the program for exploration of the data
    HCII2007, July 26th Blaz Fortuna, Jozef Stefan Institute, Slovenia
  • 12. Future work
    • Tools for suggestion and learning of more complex relations
    • Extended support for collaborative editing of ontologies
    • Easier input of background knowledge
    • Improvement of the user interface based on the feedback from user trails and real-world users
    HCII2007, July 26th Blaz Fortuna, Jozef Stefan Institute, Slovenia
  • 13.
    • Questions? Comments?
    Thank you for listening! HCII2007, July 26th Blaz Fortuna, Jozef Stefan Institute, Slovenia http://ontogen.ijs.si

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