All Good Recommendations Come with an Explanation
On November 29, 2022, Hoang successfully defended his dissertation entitled “Mining Product Textual Data for Recommendation Explanations”. While we were then coming out of...
On November 29, 2022, Hoang successfully defended his dissertation entitled “Mining Product Textual Data for Recommendation Explanations”. While we were then coming out of...
In August 2022, Hady, Zhang Ce, and Thuat travelled to Washington D.C. to attend the 28th ACM SIGKDD Conference on Knowledge Discovery and Data...
On 10 February 2022, Tuan Truong successfully defended his dissertation, entitled “Modeling Sentiments and Preferences from Multimodal Data”. In a sign of the times,...
Tuan, Aghiles, and Hady will be delivering a tutorial at the RecSys-21 conference that will take place in September 2021. The slides and the...
In a previous blog post, we introduce the problem of top-K recommendation retrieval using Matrix Factorization (MF). We also highlight the importance of indexing structures as a...
Personalized recommender systems attempt to generate a limited number of item options (e.g., products on Amazon, movies on Netflix, or videos on Youtube, etc.)...
Join us for TechFest 2020 by Preferred.AI! Our theme this year is Zooming In. Inside an innovative app is a cool AI algorithm. On...
Previously, we gave our readers a glance at visual sentiment analysis in an earlier blog post. The goal of the task was seeking the...
Text documents are usually linked to one another. For example, academic papers cite other papers, web pages link to other pages, etc. Most of...
Generative models specify procedures allowing us to produce data samples, e.g., images, texts, user preferences, etc. These models are central to unsupervised learning, and...