Audio Source Separation using the Non Negative Matrix Multiplication

Building a Collaborative Filtering based Recommender system using e-commerce data.

Semi-Supervise cellular deconvolution of Bulk RnaSeq using NMF and CiberSortx, DCQ or others

A Project on Topic Modeling using alogoriths like LSA/LSI, LDA, NMF on RACE dataset

Code and associated data relating to Kowalski, MacGregor, Long, Bell, and Cronin, "Automated Library Generation and Serendipity Quantification enables Diverse Discovery in Coordination Chemistry", JACS, 2022

Codebase and Data for the work on Network diffusion-based approach for survival prediction and identification of biomarkers using multi-omics data of Papillary Renal Cell Carcinoma

Machine learning model using NLP topic modeling to automatically classify customer complaints based on products and services for improved customer service in the financial industry.

Unsupervised classification of products based on their text description (NLP) or image (computer vision)

Detailed sentiment analysis (overall and aspect based sentiment analysis) on major Singapore attractions.

Code to recreate results from the "Multi-view biclustering via non-negative matrix tri-factorisation" paper.

This project demonstrates the application of Non-Negative Matrix Factorization (NMF) for topic modeling on a dataset of abstracts

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.

Survey Insights Engine

This project processes customer complaint data using pandas for data manipulation and applies text preprocessing techniques, including lemmatization, to clean and normalize complaint text. The `tqdm` library provides progress bars for efficient tracking of text processing tasks.

This project aims to identify key topics in Quora questions related to popular applications. We'll use Non-Negative Matrix Factorization (NMF) to extract meaningful themes and patterns from this data.

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

Topic Modelling von Tagesschau-Nachrichtenmeldungen mit NMF

2023 NCKU Image Processing Homework Code