GitHub

A context-aware, hybrid recommendation engine demonstrating Neural Collaborative Filtering and Matrix Factorization architectures.

Most food delivery platforms prioritize operational convenience—showing what is open or popular—rather than truly understanding user intent. This leads to repetitive, non-personalized experiences.
IEEE

Recommending the Right Biofertilizer Using Deep Collaborative Matrix Factorization in the Coffee Plantation

Abstract: Biofertilizer is an assortment of organic fertilizers that incorporates live organisms into the soil to boost soil health and plant growth. Traditional collaborative filtering was utilized ...
IEEE

Sparse Nonnegative Matrix Factorization Based on Collaborative Neurodynamic Optimization

Abstract: This paper presents a collaborative neurodynamic approach to sparse nonnegative matrix factorization (SNMF). SNMF is formulated as a bilevel optimization problem. In the lower level of the ...
GitHub

daviddaadams/ds-portfolio-recommender-system

This project implements multiple recommendation algorithms from scratch, evaluates them on the MovieLens 100K dataset, and provides comprehensive documentation for learning and interviews. UserBasedCF ...