Matrix Organizations: How Leaders Can Be More Effective

Matrix structures don’t work on their own. The work is less about control and more about integration, often without formal ...
IEEE

Improved Collaborative Non-Negative Matrix Factorization and Total Variation for Hyperspectral Unmixing

Abstract: Hyperspectral unmixing (HSU) is an important technique of remote sensing, which estimates the fractional abundances and the mixing matrix of endmembers in each mixed pixel from the ...
IEEE

Collaborative Kalman Filtering for Dynamic Matrix Factorization

Abstract: We propose a new algorithm for estimation, prediction, and recommendation named the collaborative Kalman filter. Suited for use in collaborative filtering settings encountered in ...
GitHub

hexiangnan/neural_collaborative_filtering

This is our implementation for the paper: Xiangnan He, Lizi Liao, Hanwang Zhang, Liqiang Nie, Xia Hu and Tat-Seng Chua (2017). Neural Collaborative Filtering. In Proceedings of WWW '17, Perth, ...
Frontiers

Collaborative filtering based on nonnegative/binary matrix factorization

Collaborative filtering generates recommendations by exploiting user-item similarities based on rating data, which often contains numerous unrated items. To predict scores for unrated items, matrix ...
Scientific American

How Recommendation Algorithms Work—And Why They May Miss the Mark

Whether we’re using Spotify, Amazon, Netflix or Instagram, we encounter algorithms that recommend content or products to us every day. In 2017 Netflix stated that its users discover around 80 percent ...
Scientific Research Publishing

A Conceptual and Computational Framework for Aspect-Based Collaborative Filtering Recommender Systems ()

Many datasets in E-commerce have rich information about items and users who purchase or rate them. This information can enable advanced machine learning algorithms to extract and assign user ...
GitHub

CF4J: Collaborative Filtering for Java

A Java's Collaborative Filtering library to carry out experiments in research on Collaborative Filtering based Recommender Systems. The library has been designed from researchers to researchers. If ...