I have a ColdFusion 10-based GIS application with a search form. One of 
the searches that can be performed is an address search. Address data is 
stored in an enterprise database that I can't alter, so I have to work 
with it the way it is.

Addresses are broken apart into six separate database columns, not 
counting the city, state or zip code.  Not every address uses every one 
of the six columns, but some use as many as five of them.

Anyway, the search form currently is rather cumbersome as users have to 
enter pieces of the address into different form fields.  It works, but 
as I said, it's cumbersome.

I decided to try to see if I could use Solr to do more intelligent 
address searches from one form field, ala Google or Yahoo maps.  I 
created a collection on my dev server.  I wrote a query that assembled 
the six pieces into a single address column, then used <cfindex> to put 
the query results into the index (I put the address column into the body 
attribute of <cfindex>).  Last, I wrote a simple one field form to 
perform the search.

This seems to work, but it pulls back a horrifically large amount of 
results of dubious match quality.  For example, a search using "1234 
Main St" (fictitious example address to protect the innocent) returned 
34,040 rows out of 123,000 address records.  The reason? It's finding 
matches to any single piece of the search string.

 From the ColdFusion docs, it looks like I might be able to tighten up 
the search results by prefixing each "piece" of the search criteria with 
a "+" character.  However, that will force exact matches (except when 
the street name is also the city name, such as Oakland Blvd in the city 
of Oakland), and I'd like to keep a little bit of "fuzzy" search 
capability for typos and such (like Google does).

Has anyone played around with parsing addresses and assembling an 
optimized Solr search?  I'm hoping to save some time on experimentation.

Thanks,
Carl V.

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