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MLS-C01 · Question #125

A retail company is using Amazon Personalize to provide personalized product recommendations for its customers during a marketing campaign. The company sees a significant increase in sales of…

The correct answer is A. Use the event tracker in Amazon Personalize to include real-time user interactions. https://docs.aws.amazon.com/personalize/latest/dg/maintaining-relevance.html

Machine Learning Implementation and Operations

Question

A retail company is using Amazon Personalize to provide personalized product recommendations for its customers during a marketing campaign. The company sees a significant increase in sales of recommended items to existing customers immediately after deploying a new solution version, but these sales decrease a short time after deployment. Only historical data from before the marketing campaign is available for training. How should a data scientist adjust the solution?

Options

  • AUse the event tracker in Amazon Personalize to include real-time user interactions.
  • BAdd user metadata and use the HRNN-Metadata recipe in Amazon Personalize.
  • CImplement a new solution using the built-in factorization machines (FM) algorithm in Amazon
  • DAdd event type and event value fields to the interactions dataset in Amazon Personalize.

How the community answered

(24 responses)
  • A
    71% (17)
  • B
    4% (1)
  • C
    17% (4)
  • D
    8% (2)

Explanation

https://docs.aws.amazon.com/personalize/latest/dg/maintaining-relevance.html

Topics

#Amazon Personalize#Real-time data ingestion#Recommendation systems#Model adaptation

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