Springer Nature launches Recommended

New service aims to connect researchers with relevant content.

Recommended will use an algorithm to recommend relevant research content to researchers.

The service has been developed to help researchers keep up to date in their specialist area - something that is increasingly difficult because of the rapid increase in published research. Specific recommendations will be drawn from over 65 million papers using an algorithm tailored to individual needs. The recommendations are publisher neutral.

Recommended learns about users by analysing the last 100 articles they have read on Springer Nature websites and searching for similar primary papers using Crossref and PubMed. It them uses additional date from Altmetric and other sources to identify recommended papers.  The service continues to learn about the user by analysing how they interact with the recommended papers.

More information via Springer Nature.  Original Source Knowledgespeak.