UTL_MATCH contains methods for matching strings and comparing their similarity. The
edit distance, also known as the Levenshtein Distance, might be a good place to start. Since one string is a substring it may help to compare the edit distance
relative to the size of the strings.
--Addresses that are most similar to each substring.
select substring, address, edit_ratio
from
(
--Rank edit ratios.
select substring, address, edit_ratio
,dense_rank() over (partition by substring order by edit_ratio desc) edit_ratio_rank
from
(
--Calculate edit ratio - edit distance relative to string sizes.
select
substring,
address,
(length(address) - UTL_MATCH.EDIT_DISTANCE(substring, address))/length(substring) edit_ratio
from
(
--Fake addreses (from http://names.igopaygo.com/street/north_american_address)
select '526 Burning Hill Big Beaver District of Columbia 20041' address from dual union all
select '5206 Hidden Rise Whitebead Michigan 48426' address from dual union all
select '2714 Noble Drive Milk River Michigan 48770' address from dual union all
select '8325 Grand Wagon Private Sleeping Buffalo Arkansas 72265' address from dual union all
select '968 Iron Corner Wacker Arkansas 72793' address from dual
) addresses
cross join
(
--Address substrings.
select 'Michigan' substring from dual union all
select 'Not-So-Hidden Rise' substring from dual union all
select '123 Fake Street' substring from dual
)
order by substring, edit_ratio desc
)
)
where edit_ratio_rank = 1
order by substring, address;
These results are not great but hopefully this is at least a good starting point. It should work with any language. But you'll still probably want to combine this with some language- or locale- specific comparison rules.
SUBSTRING ADDRESS EDIT_RATIO
--------- ------- ----------
123 Fake Street 526 Burning Hill Big Beaver District of Columbia 20041 0.5333
Michigan 2714 Noble Drive Milk River Michigan 48770 1
Michigan 5206 Hidden Rise Whitebead Michigan 48426 1
Not-So-Hidden Rise 5206 Hidden Rise Whitebead Michigan 48426 0.5
