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What difficulty level is this interview question?

This is a easy difficulty Coding & Algorithms question, commonly asked during Onsite rounds at Netflix.

What role is this question designed for?

This question is commonly asked for Machine Learning Engineer candidates at Netflix during technical interviews.

Implement rotating homepage title selector | Netflix Interview Question

Quick Overview

This question evaluates understanding of data structures and algorithms for prioritized selection with stateful constraints, focusing on maintaining dynamic relevance scores and avoiding immediate repeats; it is categorized under Coding & Algorithms.

Implement an in-memory service that chooses which movie or show title to display on a user's homepage billboard.

Each title has a relevance score for the current user. Higher-scored titles should generally be returned first, but the service should avoid returning the same title on two consecutive calls when another title is available.

Support these APIs:

upsertTitleScore(title_id: string, score: float)
- Insert a new title or update the score of an existing title.
getTopTitle() -> string
- Return the title that should be shown now.

Requirements:

Titles with higher scores should be preferred.
If there is more than one available title, avoid returning the same title on two consecutive getTopTitle() calls.
A title remains eligible after being returned and may be returned again later.
If the system contains only one title, it may be returned repeatedly.
upsertTitleScore may be called many times for the same title_id , and updates must take effect correctly.

Design and implement the data structure and explain the time complexity of your operations.

Implement rotating homepage title selector

Quick Overview

Implement rotating homepage title selector

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