Amazon Personalize launches new recipe that increases the relevance of similar items recommendations
We are excited to announce a new recipe in Amazon Personalize that, when given an item, will recommend similar items based on both user-item interaction data and item metadata. The combination of your users’ historical interactions and the information you have about your items increases the relevance of recommendations and ensures similar items capture your users’ attention. To assess the similarity of items we measure how frequently the items are found together in users’ histories. As a benchmark, we found that the new recipe is 10.2% more accurate in identifying similar items than recipes that use interactions data alone. This means your users will be more likely to find the items most related to what they are viewing.
We are excited to announce a new recipe in Amazon Personalize that, when given an item, will recommend similar items based on both user-item interaction data and item metadata. The combination of your users’ historical interactions and the information you have about your items increases the relevance of recommendations and ensures similar items capture your users’ attention. To assess the similarity of items we measure how frequently the items are found together in users’ histories. As a benchmark, we found that the new recipe is 10.2% more accurate in identifying similar items than recipes that use interactions data alone. This means your users will be more likely to find the items most related to what they are viewing.
Using the new recipe is simple. Provide metadata about your items along with users’ interactions with your items and Amazon Personalize automatically identifies the most relevant data to recommend similar items in your application.
Amazon Personalize enables you to personalize your website, app, ads, emails, and more, using the same machine learning technology as used by Amazon, without requiring any prior machine learning experience. To get started with Amazon Personalize, visit our documentation.