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  Inducing Metric Violations in Human Similarity Judgements

Laub, J., Macke, J., Müller, K.-R., & Wichmann, F. (2007). Inducing Metric Violations in Human Similarity Judgements. In B. Schölkopf, J. Platt, & T. Hoffman (Eds.), Advances in Neural Information Processing Systems 19 (pp. 777-784). Cambridge, MA, USA: MIT Press.

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Datensatz-Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-CBE7-3 Versions-Permalink: https://hdl.handle.net/21.11116/0000-0002-E20C-2
Genre: Konferenzbeitrag

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externe Referenz:
https://papers.nips.cc/paper/3090-inducing-metric-violations-in-human-similarity-judgements.pdf (Verlagsversion)
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Urheber

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 Urheber:
Laub, J, Autor
Macke, JH1, 2, 3, Autor           
Müller, K-R, Autor           
Wichmann, FA2, 3, Autor           
Affiliations:
1Research Group Computational Vision and Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497805              
2Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
3Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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Schlagwörter: -
 Zusammenfassung: Attempting to model human categorization and similarity judgements is both a very interesting but also an exceedingly difficult challenge. Some of the difficulty
arises because of conflicting evidence whether human categorization and similarity judgements should or should not be modelled as to operate on a mental representation that is essentially metric. Intuitively, this has a strong appeal as it would allow (dis)similarity to be represented geometrically as distance in some internal space. Here we show how a single stimulus, carefully constructed in a
psychophysical experiment, introduces l2 violations in what used to be an internal similarity space that could be adequately modelled as Euclidean. We term this one
influential data point a conflictual judgement. We present an algorithm of how to analyse such data and how to identify the crucial point. Thus there may not be a
strict dichotomy between either a metric or a non-metric internal space but rather degrees to which potentially large subsets of stimuli are represented metrically
with a small subset causing a global violation of metricity.

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Sprache(n):
 Datum: 2007-09
 Publikationsstatus: Erschienen
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: BibTex Citekey: 4266
 Art des Abschluß: -

Veranstaltung

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Titel: Twentieth Annual Conference on Neural Information Processing Systems (NIPS 2006)
Veranstaltungsort: Vancouver, BC, Canada
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Projektinformation

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Quelle 1

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Titel: Advances in Neural Information Processing Systems 19
Genre der Quelle: Konferenzband
 Urheber:
Schölkopf, B1, Herausgeber           
Platt, JC, Herausgeber
Hoffman, T, Herausgeber
Affiliations:
1 Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795            
Ort, Verlag, Ausgabe: Cambridge, MA, USA : MIT Press
Seiten: - Band / Heft: - Artikelnummer: - Start- / Endseite: 777 - 784 Identifikator: ISBN: 0-262-19568-2