Services or capabilities described in this page might vary by Region. To see the differences applicable to the China Regions, see Getting Started with Amazon Web Services in China Regions. Only “Region Availability” and “Feature Availability and Implementation Differences” sections for specific services (in each case exclusive of content referenced via hyperlink) in Getting Started with Amazon Web Services in China Regions form part of the Documentation under the agreement between you and Sinnet or NWCD governing your use of services of Amazon Web Services China (Beijing) Region or Amazon Web Services China (Ningxia) Region (the “Agreement”). Any other content contained in the Getting Started pages does not form any part of the Agreement.
Amazon Personalize Documentation
Automated machine learning
Once you have provided your data via Amazon S3 or via real-time integrations, Amazon Personalize can load and inspect the data, enable you to select the right algorithms, train a model, provide metrics, and generate personalized recommendations. As your data set grows over time from new metadata and the consumption of real-time user event data, your models can be retrained to provide relevant and personalized recommendations.
Batch recommendations
Compute recommendations for large numbers of users or items, store them, and feed them to batch-oriented workflows such as email systems.
New user and new item recommendations
Generate recommendations even for new users and find new item recommendations for your users.
Contextual recommendations
Improve relevance of recommendations by generating them within a context.
Similar item recommendations
Improve the discoverability of your catalog by surfacing similar items to your users.
Unlock Information in Unstructured Text
Unlock the information trapped in product descriptions, reviews, movie synopses or other unstructured text to help you generate highly relevant recommendations for users. Provide unstructured text as part of your catalog and Amazon Personalize extracts key information to use when generating recommendations.
Prioritizing your business goals and what is relevant for your users
Consider what’s relevant to your users and what is important for your business when generating recommendations. You can define an objective to influence recommendations. This can be used to help you maximize for metrics you define as important to your business.
Integrate with your existing tools
Amazon Personalize can be integrated into websites, mobile apps, or content management and email marketing systems, via an inference API call. The service lets you generate user recommendations, similar item recommendations and personalized re-ranking of items. You can call the Amazon Personalize APIs and the service will output item recommendations or a re-ranked item list, which you can use in your application.
GetRecommendations API - returns a list of relevant items when you provide a userID. The API can also be used to return a list of similar itemIDs given an input itemID.
GetPersonalizedRanking – You can use an API to re-rank a list of itemIDs given a userID and a list of itemIDs to be re-ranked.
Additional Information
For additional information about service controls, security features and functionalities, including, as applicable, information about storing, retrieving, modifying, restricting, and deleting data, please see https://docs.amazonaws.cn/en_us/. This additional information does not form part of the Documentation for purposes of the Sinnet Customer Agreement for Amazon Web Services (Beijing Region), Western Cloud Data Customer Agreement for Amazon Web Services (Ningxia Region) or other agreement between you and Sinnet or NWCD governing your use of services of Amazon Web Services China Regions.
