Latent Dirichlet allocation for topic modeling
Augello, Ginevra (A.A. 2024/2025) Latent Dirichlet allocation for topic modeling. Tesi di Laurea in Data analysis for business, Luiss Guido Carli, relatore Alessia Caponera, pp. 36. [Bachelor's Degree Thesis]
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Abstract/Index
Background. The frequentist approach. The bayesian approach. The false dilemma. De Finetti’s theorem. Some useful distributions. Latent dirichlet allocation. Language of text collections: notation and terminology. LDA’s generative process. Bag-of-words assumption and exchangeability. LDA as a hierarchical model. Inference. LDA application. Data pre-processing. Exploratory data analysis. Model implementation.
References
Bibliografia: p. 36.
| Thesis Type: | Bachelor's Degree Thesis |
|---|---|
| Institution: | Luiss Guido Carli |
| Degree Program: | Bachelor's Degree Programs > Bachelor's Degree Program in Management and Computer Science, English language (L-18) |
| Chair: | Data analysis for business |
| Thesis Supervisor: | Caponera, Alessia |
| Academic Year: | 2024/2025 |
| Session: | Summer |
| Deposited by: | Alessandro Perfetti |
| Date Deposited: | 26 Nov 2025 15:27 |
| Last Modified: | 26 Nov 2025 15:32 |
| URI: | https://tesi.luiss.it/id/eprint/44094 |
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