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Cited by 208

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A probabilistic approach to semantic representation

Open access
Griffiths, Thomas L., Steyvers, Mark·2019·Proceedings of the Twenty-Fourth Annual Conference of the Cognitive Science Society

Abstract

Semantic networks produced from human data have statistical properties that cannot be easily captured by spatial representations. We explore a probabilistic approach to semantic representation that explicitly models the probability with which words occur in different contexts, and hence captures the probabilistic relationships between words. We show that this representation has statistical properties consistent with the large-scale structure of semantic networks constructed by humans, and trace the origins of these properties.

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Metadata

Authors
Griffiths, T. L., & Steyvers, M.
Venue
Proceedings of the Twenty-Fourth Annual Conference of the Cognitive Science Society
Publisher
Routledge
Published
2019-04-24
Pages
381-386
OpenAlex
W125892352
Cited by
208
References
3
FWCI
2.40
Type
conference paper
Language
en
Open access
bronze

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CoChat. (2026). Citation check: A probabilistic approach to semantic representation. https://app.cochat.ai/papers/10.4324/9781315782379-102
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Griffiths, T. L., & Steyvers, M. (2019). A probabilistic approach to semantic representation. Proceedings of the Twenty-Fourth Annual Conference of the Cognitive Science Society. https://doi.org/10.4324/9781315782379-102

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.