Design a Location Recommendation System

Q: Design a Location Recommendation System

This question evaluates a candidate's ability to design end-to-end machine learning recommendation systems, covering competencies in candidate generation, ranking models, feature engineering, real-time serving, evaluation metrics, and considerations for privacy, bias, and abuse resistance.

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Question

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Design a machine learning system that recommends places to a user in a maps or local-discovery product.

A user opens the app and expects relevant nearby suggestions such as restaurants, cafes, attractions, or other points of interest. The system should use signals such as the user's current location, time of day, historical behavior, preferences, and place metadata to rank candidates.

Discuss:

product goals and success metrics
candidate generation and retrieval
ranking features and model choices
cold-start handling for new users and new places
real-time serving architecture and latency constraints
feedback loops, exploration vs. exploitation, and online learning considerations
offline and online evaluation
privacy, bias, and abuse resistance

Design a Location Recommendation System

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