The thesis explores the Italian wine e-commerce market through the use of machine learning techniques. Data is collected via web scraping from specialized websites, then cleaned and preprocessed. A semantic analysis of product descriptions is conducted to extract relevant information. Finally, price ranges are modeled using supervised algorithms.
La tesi esplora il mercato e-commerce del vino in Italia mediante l’impiego di tecniche di machine learning. I dati vengono raccolti tramite web scraping da siti specializzati, quindi puliti e preprocessati. Un’analisi semantica delle descrizioni dei vini consente di estrarre le informazioni. Infine, le fasce di prezzo vengono modellate con algoritmi supervisionati.
Il mercato vitivinicolo online: un'analisi del contesto italiano basata su algoritmi di Machine Learning
BOLLA, MOSE'
2024/2025
Abstract
The thesis explores the Italian wine e-commerce market through the use of machine learning techniques. Data is collected via web scraping from specialized websites, then cleaned and preprocessed. A semantic analysis of product descriptions is conducted to extract relevant information. Finally, price ranges are modeled using supervised algorithms.| File | Dimensione | Formato | |
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Bolla_Mose.pdf
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1.54 MB | Adobe PDF |
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https://hdl.handle.net/20.500.12608/93884