I’ve worked on lots of recommender systems over the years and one of the most common questions that I have been asked by non-recommendery folk is, “But how exactly does the recommender algorithm work?”. It’s a question that I’ve come to loath, fear and love, in ever changing quantities. I loath it because… Read More But how exactly does the recommender algorithm work?
Kris Jack, Ed Ingold and Maya Hristakeva. Introduction Mendeley Suggest, a personalised research literature recommender, has been live for around nine months so we thought we’d mark this traditional human gestation period with a blog post about its architecture. We’ll present how the architecture currently looks, pointing out which technologies we use, justifying decisions that… Read More Mendeley Suggest Architecture
Introduction When recommending items to users, it’s not a good idea to recommend the same ones over and over again if the user isn’t interacting with them. In a previous post, we discussed a technique called dithering that allows us to change the order of recommended items, creating the illusion of freshness, and reducing the chances… Read More Impression Discounting
This is the first in a series of posts on evaluation metrics for recommender systems. It’s important to be able to measure attributes of your recommender so that you can start to understand it better and eventually improve it. These metrics allow you to predict both how well your recommender will perform before you test… Read More Evaluation Metrics – Part 1
This is the final part in a five part series on overviewing recommender algorithms. In the first post, we introduced the main types of recommender algorithms by providing a cheatsheet for them. In the second, we covered the different types of collaborative filtering algorithms highlighting some of their nuances and how they differ from one… Read More Overview of Recommender Algorithms – Part 5
Netflix is a company that demonstrates how to successfully commercialise recommender systems. Netflix manages a large collections of movies and television programmes, making the content available to users at any time by streaming them directly to their computer/television. It’s a very profitable company that makes its money through monthly user subscriptions. Users can cancel their… Read More Recommender Systems in Netflix
Mendeley Suggest is an article recommender system for researchers. It’s designed to help them discover new research based on their short and long term interests and to keep them up-to-date with what’s popular and trending in their domains. The first set of recommendations is based on all of the articles that you have added to… Read More Mendeley Suggest