giacomopracucci / classification-and-topic-modeling

Text classification and topic modeling using an e-commerce dataset containing product descriptions. Developed during 2nd year of study in Data Science (January 2023), together with my colleagues Dario Galimberti and Paola Impiccichè.

Text Classification and Topic Modeling on E-commerce text dataset

Authors:

• Dario Galimberti
• Paola Impiccichè
• Giacomo Pracucci

This project presents a study on text classification and topic modeling using an e-commerce dataset containing product descriptions.

The task of Text Classification involves the categorization of product descriptions into predefined classes using three Machine Learning algorithms: Multinomial Naive Bayes, Logistic Regression and Random Forest.

The second part discusses the task of Topic Modeling using Latent Dirichlet Allocation (LDA) and BERTopic, to discover latent themes or topics present in the descriptions of different product lines.