Frequent Traveler: Definition, Features, Modeling, and Product Use
Context: You are a data scientist at a professional networking platform. Using user activity and coarse location signals (e.g., city-level geolocation from login/IP/GPS, timezone), define and operationalize a “frequent traveler,” propose features and models to identify them, and discuss product applications and pitfalls.
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How would you define a “frequent traveler”?
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Which data points or features would you use to identify frequent travelers?
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Why is it important to consider both frequency and distance of location changes rather than just frequency alone?
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Once you’ve identified frequent travelers, how can you use this information in a product or service?
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What analytical or modeling approaches might you use to classify users as frequent travelers?
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What pitfalls might arise if you only focus on the frequency of location changes without considering distance?