Jim Davies: Publications

Davies, J. & Gagné, J. (2010). Estimating quantitative magnitudes using semantic similarity. Conference of the American Association for Artificial Intelligence workshop on Visual Representations and Reasoning (AAAI-10-VRR), 14--19.

Cite this for:

SYSTEM: Visuo
When estimating quantitative magnitudes, using a semantically-related base for analogy works better than using a semantically-unrelated base.

BibTex Entry:

@InProceedings{DaviesGagne2010,
  author = 	 {Davies, Jim and Gagné, Jonathan},
  title = 	 {Estimating quantitative magnitudes using semantic similarity},
  booktitle = 	 {Conference of the American Association for Artificial Intelligence workshop on Visual
Representations and Reasoning (AAAI-10-VRR),
  pages = 	 {14--19},
  year = 	 {2010},
  editor = 	 {}
}

Download: [ PDF ]

Abstract

We present an AI called Visuo that guesses quantitative visuospatial magnitudes (e.g., heights, lengths) given adjective-noun pairs as input (e.g., “big hat”). It uses a database of tagged images as memory and infers unexperienced magnitudes by analogy with semantically related concepts in memory. We show that transferring width-height ratios from a semantically-related concept yields significantly lower error rates than using dissimilar concepts when predicting the width-height ratios of novel inputs.

Back to Jim Davies's list of publications.

JimDavies ( jim@jimdavies.org )