Concept information
Preferred term
probabilistic topic model
Definition
- "A generative probabilistic model that uses Bayesian inference to abstract the mental “topics” used to compose a set of documents." (Jones et al., 2015, p. 251).
Broader concept
Synonym(s)
- topic model
- topic modeling
Belongs to group
Bibliographic citation(s)
-
• Blei, D. M. (2012). Probabilistic topic models. Communications of the ACM, 55(4), 77-84. https://doi.org/10.1145/2133806.2133826
{{#each properties}}• Document type: literature review
• Access: closed
- • Griffiths, T. L., & Steyvers, M. (2004). Finding scientific topics. Proceedings of the National Academy of Sciences, 101(suppl 1), 5228‑5235. https://doi.org/10.1073/pnas.0307752101
• Document type: empirical study
• Access: open
- • Griffiths, T. L., Steyvers, M., & Tenenbaum, J. B. (2007). Topics in semantic representation. Psychological Review, 114(2), 211‑244. https://doi.org/10.1037/0033-295X.114.2.211
• Document type: empirical study
• Access: closed
- • Jones, M. N., Willits, J. A., & Dennis, S. (2015). Models of semantic memory. In J. R. Busemeyer, Z. Wang, J. T. Townsend, & A. Eidels (Eds.), The Oxford handbook of computational and mathematical psychology (p. 232‑254). Oxford University Press.
• Document type: literature review
• Access: closed
- • Kumar, A. A. (2020). Semantic memory : A review of methods, models, and current challenges. Psychonomic Bulletin & Review. https://doi.org/10.3758/s13423-020-01792-x
• Document type: literature review
• Access: open
Creator
- Frank Arnould
Model of
In other languages
-
French
-
modèle thématique
URI
http://data.loterre.fr/ark:/67375/P66-Z32BVG4N-3{{/each}}{{label}}
{{#each values }} {{! loop through ConceptPropertyValue objects }} {{#if prefLabel }}{{/if}} {{/each}}{{#if notation }}{{ notation }} {{/if}}{{ prefLabel }} {{#ifDifferentLabelLang lang }} ({{ lang }}){{/ifDifferentLabelLang}}{{#if vocabName }} {{ vocabName }} {{/if}} - • Griffiths, T. L., & Steyvers, M. (2004). Finding scientific topics. Proceedings of the National Academy of Sciences, 101(suppl 1), 5228‑5235. https://doi.org/10.1073/pnas.0307752101