Analogical learning of visual/conceptual relationships in sketches

  • Authors:

  • Kenneth D. Forbus;Jeffrey Usher;Emmett Tomai

  • Affiliations:

  • Qualitative Reasoning Group, Northwestern University, Evanston, IL;Qualitative Reasoning Group, Northwestern University, Evanston, IL;Qualitative Reasoning Group, Northwestern University, Evanston, IL

  • Venue:
  • AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
  • Year:
  • 2005

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Abstract

This paper explores the use of analogy to learn about properties of sketches. Sketches often convey conceptual relationships between entities via the visual relationships between their depictions in the sketch. Understanding these conventions is an important part of adapting to a user. This paper describes how learning by accumulating examples can be used to make suggestions about such relationships in new sketches. We describe how sketches are being used in Companion Cognitive Systems to illustrate one context in which this problem arises. We describe how existing cognitive simulations of analogical matching and retrieval are used to generate suggestions for new sketches based on analogies with prior sketches. Two experiments provide evidence as to the accuracy and coverage of this technique.