The document discusses improving user experience through location-based search optimizations. It describes using a Solr index with geographic data and population information to reorder search results for a query like "Brooklyn" to prioritize Brooklyn, NY over other locations. Code examples are provided to load location data into Solr and implement a custom score function that considers distance to search point and population to rank cities. The approach enhanced data quality with minimal effort.
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Solving the "Brooklyn Problem"
1. Solving The
Brooklyn Problem:
Better UX through cheap hacks
Kellan Elliott-McCrea, Etsy
@kellan
Thursday, April 21, 2011
19. http://localhost:8393/solr/
placesuggest/select?
q=b*&sfield=latlong&pt=37.7749295
,-122.4194155&sort=div(geodist
(),sqrt(sum(population,1)))%20asc
Thursday, April 21, 2011
20. OM
G
CO
NT
http://localhost:8393/solr/
EX
TS
placesuggest/select?
GE EN
q=b*&sfield=latlong&pt=37.7749295
OC SIT
O D IV
,-122.4194155&sort=div(geodist
IN E PE
(),sqrt(sum(population,1)))%20asc
G! RS
!!!! ON
AL
IZ
ED
Thursday, April 21, 2011
22. the tear down
* Solr 3.10+ working geo-spatial extensions
* 2.6 million points == 380Mb index
* the data sucks, and it doesnt matter (much)
* a few days of work, 85% increase in data
quality.
Thursday, April 21, 2011