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Keeping up-to-date with published research just got easier

With 4000* new papers published every day, Recommended helps you find the right one to read next. *Source: The STM Report, March 2015

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How does it work?

Powered by an adaptive algorithm, Recommended learns about your individual research interests by analysing the last 100 papers you’ve read across nature.com, SpringerLink and BioMed Central.

Recommended then looks for similar primary papers to your reading history, utilising approximately 45,000 journals from Crossref and PubMed. These get combined with data from other sources, such as Altmetric, to create a recommendation score which our service uses to deliver primary papers that meet the quality threshold, from all publishers.

Recommended continually learns and improves from how users interact with its suggestions.

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How is Recommended being used?

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Please confirm your email address to start receiving article recommendations.

We would love to hear your feedback to help us shape and improve the service. Please email us at recommended@springernature.com.

Help us build world class tools for researchers

Developer positions open

We are currently looking for developers who are positive, keen to learn, happy to muck in with front & back end code, and who are professional and thoughtful.

Our team is small, flexible and values discussion. We believe that:

  • Learning from your mistakes is better than being right
  • Data and user research work better together
  • Every team member owns the work that we do
  • The only true definition of done is delivering code all the way to production

Situated in the heart of the Knowledge Quarter in Kings Cross, London, we're committed to supporting researchers with the work they do by building the best tools to solve their problems.

We believe we're onto something with Recommended, but we need your help to continue our success.

If this sounds interesting, send your CV to: recommended@springernature.com.

The Recommended team is part of Springer Nature digital.

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