<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Andrew Lovett</style></author><author><style face="normal" font="default" size="100%">Dedre Gentner</style></author><author><style face="normal" font="default" size="100%">Eyal Sagi</style></author><author><style face="normal" font="default" size="100%">Kenneth Forbus</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Modeling Perceptual Similarity as Analogy Resolves the Paradox of Difference Detection</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the 2nd International Analogy Conference</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><pub-location><style face="normal" font="default" size="100%">Sofia, Bulgaria</style></pub-location><abstract><style face="normal" font="default" size="100%">There is a paradoxical dissociation between recognizing that two stimuli are different and recognizing how they are different. We show that this dissociation can be captured by modeling perceptual similarity as a species of analogical processes. Using SME to model comparison, we show that the dissociation arises naturally from different stages in the analogical mapping process. Rather than relying on hand-coded input representations, our model uses an automatic, incremental encoding process to generate representations from the same stimuli as given to human participants.</style></abstract></record></records></xml>