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AIF-C01 Practice Question: An e-commerce company uses Amazon Personalize to…

An e-commerce company uses Amazon Personalize to provide product recommendations. The business team observes that the recommendations are dominated by popular items and rarely suggest niche products, even for users with long purchase histories. Which Personalize recipe or configuration change would BEST address this issue?

⚠ Common exam trap

A common mix-up: candidates confuse the explore-holdoff feature with hyperparameter tuning (like learning rate) or assume that switching to a popularity-based recipe would solve the problem, when in fact the correct approach is to enable exploration within the existing personalization recipe.

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Use the aws-user-personalization recipe and enable the explore-holdoff feature

The aws-user-personalization recipe includes an explore-holdoff feature that controls the balance between exploiting known user preferences and exploring less popular items. Enabling this feature reduces the dominance of popular items by allowing the model to recommend niche products, even for users with long purchase histories, addressing the bias toward popular items.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Increase the minimum interaction threshold for item inclusion

    Why it's wrong here

    This would filter out niche items, making the problem worse.

  • Decrease the learning rate for the model

    Why it's wrong here

    Learning rate is not a configurable parameter in Personalize recipes.

  • Switch from aws-user-personalization recipe to aws-popularity-count recipe

    Why it's wrong here

    Popularity-count will amplify popular items, not reduce them.

  • Use the aws-user-personalization recipe and enable the explore-holdoff feature

    Why this is correct

    This recipe includes automatic popularity-bias reduction; explore-holdoff can further encourage exploration of less popular items.

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Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

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