Analogical learning of visual/conceptual relationships in sketches

Kenneth D Forbus*, Jeffrey Usher, Emmett Tomai

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

7 Scopus citations

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.

Original languageEnglish (US)
Pages202-208
Number of pages7
StatePublished - Dec 1 2005
Event20th National Conference on Artificial Intelligence and the 17th Innovative Applications of Artificial Intelligence Conference, AAAI-05/IAAI-05 - Pittsburgh, PA, United States
Duration: Jul 9 2005Jul 13 2005

Other

Other20th National Conference on Artificial Intelligence and the 17th Innovative Applications of Artificial Intelligence Conference, AAAI-05/IAAI-05
CountryUnited States
CityPittsburgh, PA
Period7/9/057/13/05

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

Fingerprint Dive into the research topics of 'Analogical learning of visual/conceptual relationships in sketches'. Together they form a unique fingerprint.

Cite this