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10 Best Articles on Recommender Systems

The most useful articles on recommender systems from around the web—beginners to advanced—curated by thought leaders and our community. We focus on timeless pieces and update the list whenever we discover new, must-read articles or videos—make sure to bookmark and revisit this page.

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Top 5 Recommender Systems Articles

At a glance: these are the articles that have been most read, shared, and saved on recommender systems by Refind users.

  1. RecSysOps: Best Practices for Operating a Large-Scale Recommender System
  2. Recommender Systems in a Nutshell
  3. On YouTube’s recommendation system
  4. Why AI Isn’t Providing Better Product Recommendations
  5. Two Decades of Recommender Systems at Amazon.com

How to ...?

Short Articles

Short on time? Check out these useful short articles on recommender systems—all under 10 minutes.

Long Articles

These are some of the most-read long-form articles on recommender systems.

Related Topics

Publications

We monitor hundreds of publications, blogs, newsletters, and news sources in Recommender Systems, including:

KDnuggets profile image

KDnuggets

KD stands for Knowledge Discovery. Covering #DataScience #MachineLearning #AI #Analytics. Edited by @mattmayo13. Founded by Gregory Piatetsky-Shapiro.

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Google AI

Google AI is focused on bringing the benefits of AI to everyone. In conducting and applying our research, we advance the state-of-the-art in many domains.

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Towards Data Science

A Medium publication sharing concepts, ideas, and codes. Share your insights and projects with like-minded readers: http://bit.ly/write-for-tds.

What is Refind?

Every day Refind picks 5 links from around the web for every user, tailored to the user’s interests. Picking only a handful of links means focusing on what’s relevant and useful. We favor timeless pieces—links with long shelf-lives, articles that are still relevant one month, one year, or even ten years from now. These lists of the best resources on any topic are the result of years of careful curation.

How does Refind curate?

It’s a mix of human and algorithmic curation, following a number of steps:

  1. We monitor 10k+ sources and 1k+ thought leaders on hundreds of topics—publications, blogs, news sites, newsletters, Substack, Medium, Twitter, etc.
  2. In addition, our users save links from around the web using our Save buttons and our extensions.
  3. Our algorithm processes 100k+ new links every day and uses external signals to find the most relevant ones, focusing on timeless pieces.
  4. Our community of active users gets 5 links every day, tailored to their interests. They provide feedback via implicit and explicit signals: open, read, listen, share, add to reading list, save to «Made me smarter», «More/less like this», etc.
  5. Our algorithm uses these internal signals to refine the selection.
  6. In addition, we have expert curators who manually curate niche topics.

The result: lists of the best and most useful articles on hundreds of topics.

How does Refind detect «timeless» pieces?

We focus on pieces with long shelf-lives—not news. We determine «timelessness» via a number of metrics, for example, the consumption pattern of links over time.

How many sources does Refind monitor?

We monitor 10k+ content sources on hundreds of topics—publications, blogs, news sites, newsletters, Substack, Medium, Twitter, etc.

Which sources does Refind monitor on recommender systems?

We monitor hundreds of sources on recommender systems, including KDnuggets, Google AI, Towards Data Science, and many more.

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