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The search distance is set by searching the onboardee's location a few times. This is slow and prevents some users from completing onboarding.
One way to optimize performance is to pre-compute the nearby population of active users for each major city. This population data can also be used to rank location search results when signing up. The drawback is that this doesn't take into consideration age and gender-related two-way filters. Though we can probably construct an approximation by combining crude population data with more general statistics about the proportion of Duolicious users of each gender and in each age bracket.
The adaptive search distance can also be optimized by performing a one or two search queries to check the population in a fixed-size radius, then plugging those results into a formula which approximates the optimal search distance.
The text was updated successfully, but these errors were encountered:
The search distance is set by searching the onboardee's location a few times. This is slow and prevents some users from completing onboarding.
One way to optimize performance is to pre-compute the nearby population of active users for each major city. This population data can also be used to rank location search results when signing up. The drawback is that this doesn't take into consideration age and gender-related two-way filters. Though we can probably construct an approximation by combining crude population data with more general statistics about the proportion of Duolicious users of each gender and in each age bracket.
The adaptive search distance can also be optimized by performing a one or two search queries to check the population in a fixed-size radius, then plugging those results into a formula which approximates the optimal search distance.
The text was updated successfully, but these errors were encountered: