This repository classifies Goodreads Fantasy book reviews into subgenres using advanced topic modeling techniques like NMF, LDA, and BERTopic. A dataset of 2M English-language reviews is analyzed, with topics compared to predefined subgenres using cosine similarity. Heatmaps and summaries visualize the results.

Pipeline de PLN do projeto "Mood Hound" (6º DSM - 2023, FATEC Profº Jessen Vidal - SJC)

Non-Negative Matrix Factorization (NMF) is a powerful technique used in audio processing for separating mixed audio sources into their constituent parts

The repository contains files (notebooks, data) for the course work of the 2nd course: "Topic modeling for text document analysis".

Two Movie recommenders deployed on Flask app. The recommender are build on NMF and Cosine Similarity model, trained on MovieLens 100k, and automatically updated every 12 hour!

Implementation of the Non-negative Multiple Matrix Factorization (NMMF) algorithm proposed in Takeuchi et al, 2013 with some modifications. There is a python native version NMMFlexPy and a R wrapper NMMFlexR