Amazon Personalize now supports contextual recommendations
Amazon Personalize is a machine learning service which enables you to personalize your website, app, ads, emails, and more, with custom machine learning models which can be created in Amazon Personalize, with no prior machine learning experience. Today, we’re pleased to announce support for contextual recommendations, through which you can improve relevance of recommendations by generating them within a context, for instance device type, location, time of day, etc. Contextual information is also useful in personalization for new/unidentified users even when the past interactions of these users are not known.
Amazon Personalize is a machine learning service which enables you to personalize your website, app, ads, emails, and more, with custom machine learning models which can be created in Amazon Personalize, with no prior machine learning experience. Today, we’re pleased to announce support for contextual recommendations, through which you can improve relevance of recommendations by generating them within a context, for instance device type, location, time of day, etc. Contextual information is also useful in personalization for new/unidentified users even when the past interactions of these users are not known.
To use this feature, you provide contextual information (e.g, device type) as part of user-item interactions or events data to Personalize and then train a context aware model using the HRNN-Metadata or Personalized Ranking recipes; you can then query for context aware recommendations by providing the real time context for a user at the time of inference.
Contextual recommendations is now available in US East (N. Virginia, Ohio), US West(Oregon), Europe(Ireland) and Asia Pacific (Tokyo, Singapore, Mumbai, Sydney) regions. Please visit the Amazon Personalize getting started guide for more information.