As well as the ability to manually search for content, Explore’s machine learning tools will provide contextual discovery within the platform, delivering more meaningful content while saving users time and effort. The more users interact with their subscription content – the more titles read, the more searches made – Explore builds a profile of reading preferences and makes suggestions of titles from their available collections to read next. These personalised recommendations make it easy for users to find and use these valuable resources.

Content is arranged across these different lanes – the same titles could appear in multiple lanes, so users can easily and quickly see suggestions for titles most relevant to their interests.

  • Must-read: Personalised to users, this is the single title that best aligns to their learning, reading and searching patterns.
  • See what’s trending: the three resources from the subscription(s) that are most popular across the entire VitalSource catalogue.
  • Top Picks: shows all titles within the available subscription(s), minus the ‘Must-read’ title, ranked by relevancy according to each user’s activity in the platform.
  • Trending: shows all titles within the available subscription(s), minus the three ‘See what’s trending’ titles, ranked by popularity across the entire VitalSource catalogue.
  • Recently Added: subscription content ordered by when it was added or acquired.
  • Subject lanes: where the publisher has included taxonomy or other subject classification data as part of a title’s records, Explore will show up to three subject lanes – scoped by discipline, ordered by what’s trending, and personalised to a user’s activity.


Users can click on any of the lane names (in blue) to filter the view of titles to solely those allocated to that lane.


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