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Session Track B Session 2
Duration 1.5 hour
Date/Time Apr 12 2017 18:30 GMT
9:30am PDT/12:30pm EDT
5:30pm BST/6:30pm CEST
Convener TBD

Ontology Summit 2017 Track B Session 2     (2)

Meeting ID 768423137     (4)

Please use the chatroom above. Do not use the video teleconference chat, which is only for communicating with the moderator.     (7)

When you use the Video Conference URL above, you will be given the choice of using the computer audio or using your own telephone. Some attendees had difficulties when using the computer audio choice. If this happens to you, please leave the meeting and reenter it using the telephone choice with access code 768423137.     (8)


Abstract     (9)

Context: Background knowledge and ontologies can be used to improve machine learning model selection, processing, data preparation and results.     (9A)

Perception: Machine Learning requires knowledge of the domain being examined to define relevant hypotheses, infer missing information in data, choose relevant features, etc.     (9B)

Motivation: Discuss the kinds of ontologies needed for ML, and their "ground rules" and requirements.     (9C)

Agenda     (10)

  • Introduction     (10A)
  • Speakers     (10B)
    • Courtney Falk     (10B1)
      • Title: The Meaning-Based Machine Learning Project     (10B1A)
      • Abstract: Meaning-based machine learning (MBML) is a project to investigate how to get meaningful output from existing machine learning techniques. MBML builds from the Ontological Semantics Technology (OST) where natural language resources map to an ontology. An application of MBML to detecting phishing emails provides some initial experimental results. Finally, future research directions are explored.     (10B1B)
    • Bryan Bell, Expert System     (10B2)
      • Title: Leveraging FIBO with Semantic Analysis to Perform On-Boarding, KYC and CDD     (10B2A)
  • Discussion     (10C)

Attendees     (11)

Proceedings     (12)

Resources     (13)

Previous Meetings     (14)