Amazon Personalize • Collaborative Filtering • Content-based Filtering • Hybrid = Collaborative Filtering + Content-based Filtering Collaborative Filtering user1 user2 user3 user1 user2 user3 Content-based Filtering article read by me Similar Recommend new article Read Personalization Non-Personalization Deliver high-quality recommendations Deliver personalization in days, not months Real-time Works with any product or content Amazon Personalize Solution (Recipes) Model selection, training, tunning and verification Campaign Model hosting, and inference Amazon Personalize Data Set Group Users Items Interactions Data Sets User events / interactions Item meta data (a.k.a catalog information - optional) User meta data (e.g. demographics – optional) Amazon Personalize How it works • GetRecommendations • GetPersonalizedRanking Setting up Amazon Personalize Formatting Your Input Data Example 컬럼 Header CSV 포맷 Users Items Interactions https://docs.aws.amazon.com/personalize/latest/dg/how-it- works-dataset-schema.html Users Items Interactions https://docs.aws.amazon.com/personalize/latest/dg/how-it- works-dataset-schema.html { "type": "record", "name": "Users | Items | Interactions", "namespace": "com.amazonaws.personalize.schema", "fields": [ { "name": "Field Name", "type": "Data Type" }, .... ], "version": "1.0" } Minimum Suggested Data Volume • More than 50 users. • More than 50 items. • More than 1,500 interactions. ※ https://github.com/aws-samples/amazon-personalize-samples/blob/master/PersonalizeCheatSheet2.0.md User personalization Personalized ranking Similar items Recipes • User-personalization • HRNN, HRNN-Metadata, HRNN-Coldstart(legacy) • Popularity-Count (baseline) Recipe • SIMS Recipe • Personalized-Ranking Use case by Recipes • Coverage • Relevance ( ≈ Accuracy) • Mean Reciprocal Rank@K • NDCG@K • Precision@K Coverage Relevance ※ Relevance: https://docs.aws.amazon.com/personalize/latest/dg/working-with-training-metrics.html • Coverage • Relevance ( ≈ Accuracy) • Mean Reciprocal Rank@K • NDCG@K • Precision@K • Serendipity ( ≈ Surprise) Serendipity Coverage Relevance ※ Relevance: https://docs.aws.amazon.com/personalize/latest/dg/working-with-training-metrics.html relevance serendipity Why Serendipity? It keeps your customers interested. Amazon Personalize Let’s build it • visit • view • cart • buy Web Server Users Items Transactions (Interactions) Web Server Reco. Server ? response request recommendations • visit • view • cart • buy Users Items Transactions (Interactions)