How LinkedIn replaced five feed retrieval systems with one LLM model, at 1.3 billion-user scale

How LinkedIn replaced five feed retrieval systems with one LLM model — and what engineers building recommendation pipelines can learn from the redesign.
Tech Xplore

New deep learning framework solves the cold-start problem

Recommender systems suggest potentially relevant content by evaluating user preferences and are essential in reducing ...
IEEE

Graph-Based User-Centric Recommender System Using Neo4j, Cypher, and Jaccard Similarity in the Field of e-Commerce

Abstract: This paper presents a scalable and interpretable recommender system architecture that uses a property graph model implemented in Neo4j to generate personalized product recommendations. By ...
InfoWorld

What I learned using Claude Sonnet to migrate Python to Rust

Using an AI coding assistant to migrate an application from one programming language to another wasn’t as easy as it looked. Here are three takeaways.
IEEE

Integrating Digital Food Nudges and Recommender Systems: Current Status and Future Directions

Abstract: Recommender systems are widely regarded as effective tools for facilitating the discovery of relevant content. In the food domain, they help users find recipes, choose grocery products, and ...
The Daily Cougar

Algorithmic curation: Your recommendations choose you

The most effective forms of control do not feel like control at all. They feel like a recommendation. On social media platforms, buttons such as “not interested” and engagement signals appear to grant ...