Neural networks for automatic text annotation: a comparative analysis of transformer-based models
Allayarova, Ayazhan (A.A. 2024/2025) Neural networks for automatic text annotation: a comparative analysis of transformer-based models. Tesi di Laurea in Big data and smart data analytics, Luiss Guido Carli, relatore Irene Finocchi, pp. 56. [Master's Degree Thesis]
Full text for this thesis not available from the repository.
Abstract/Index
Literature review. Classical approaches to text annotation. Early neural networks for NLP. Transformers as a revolution in NLP. NLP in the financial domain. Methodology. Dataset overview. Data preprocessing. Experiment 1: abstractive summarization. Experiment 2: sentiment analysis. Tools and environment. Results and discussion. Performance metrics of summarization models. Comparison of quantitative metrics. Qualitative analysis. Sentiment analysis.
References
Bibliografia: pp. 52-55.
| Thesis Type: | Master's Degree Thesis |
|---|---|
| Institution: | Luiss Guido Carli |
| Degree Program: | Master's Degree Programs > Master's Degree Program in Data Science e Management (LM-91) |
| Chair: | Big data and smart data analytics |
| Thesis Supervisor: | Finocchi, Irene |
| Thesis Co-Supervisor: | Martino, Alessio |
| Academic Year: | 2024/2025 |
| Session: | Autumn |
| Deposited by: | Alessandro Perfetti |
| Date Deposited: | 05 Jun 2026 10:15 |
| Last Modified: | 05 Jun 2026 10:15 |
| URI: | https://tesi.luiss.it/id/eprint/46086 |
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