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@article{westera:_word,
  abstract = { Cognitive scientists have long used distributional semantic
  representations of categories.  The predominant approach uses
  distributional representations of category-denoting nouns, like
  "city" for the category city.  We propose a novel scheme that
  represents categories as prototypes over representations of
   textit {names} of its members, such as "Barcelona", "Mumbai",
  and "Wuhan" for the category city. This name-based representation
  empirically outperforms the noun-based representation on two
  experiments (modelling human judgments of category relatedness and
  predicting category membership) with particular improvements for
  ambiguous nouns. We discuss the model complexity of both classes of
  models and argue that the name-based model has superior explanatory
  potential with regard to concept acquisition.},
  added-at = {2021-07-09T11:27:40.000+0200},
  author = {Westera, Matthijs and Gupta, Abhijeet and Boleda, Gemma and Padó, Sebastian},
  biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2e7dc0d19377b7de5c332f392f55fe283/sp},
  interhash = {2672b0d253e761282b859ae438a6277e},
  intrahash = {e7dc0d19377b7de5c332f392f55fe283},
  journal = {Cognitive Science},
  keywords = {article myown},
  number = 9,
  pages = {e13029},
  timestamp = {2021-09-07T16:13:44.000+0200},
  title = {Distributional models of category concepts based on names of category members},
  url = {https://doi.org/10.1111/cogs.13029},
  volume = 45,
  year = 2021
}