Abstract
The expanded version of Tversky’s feature model by Geist, Lengnink and Wille (GLW) provides a compelling representation of similarity by adding an incomparability option. However, previous research has found the GLW model lacking when compared with participants’ responses. We present several new models based on the GLW model and validate them on data from previous similarity experiments. The results indicate that human similarity perception is not well described by a partial order.
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References
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Acknowledgement
This work was supported by the DFG SFB/TRR 135 “Cardinal Mechanisms of Perception”, project C6.
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Serr, A., Schubert, M., Endres, D. (2019). Mathematical Similarity Models: Do We Need Incomparability to Be Precise?. In: Endres, D., Alam, M., Ĺžotropa, D. (eds) Graph-Based Representation and Reasoning. ICCS 2019. Lecture Notes in Computer Science(), vol 11530. Springer, Cham. https://doi.org/10.1007/978-3-030-23182-8_20
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DOI: https://doi.org/10.1007/978-3-030-23182-8_20
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