I have been trying to come up with a way to have the computer help me
with a database of homes listed by address. My problem is probably
not uncommon in that the addresses for a property can be entered
differently by different people who enter them into the database. For
example, St. vs. Street, suffixes such as NW, or SE, 1st Street vs.
First St., etc. The permutations are enormous. I have tried sorting
by address to group them as best I can, but then I am having to just
look at them to try to decide which ones are actually the same
physical property address. I could do that for a small database, but
this one can have more than 100,000 property records in it. There is
no other common field in the database other than the street address,
so it looks like I'm stuck with trying to group them, somehow.

On Sun, 4 May 2008 08:05:49 -0700 (PDT), wrote:

I have been trying to come up with a way to have the computer help me
with a database of homes listed by address. My problem is probably
not uncommon in that the addresses for a property can be entered
differently by different people who enter them into the database. For
example, St. vs. Street, suffixes such as NW, or SE, 1st Street vs.
First St., etc. The permutations are enormous. I have tried sorting
by address to group them as best I can, but then I am having to just
look at them to try to decide which ones are actually the same
physical property address. I could do that for a small database, but
this one can have more than 100,000 property records in it. There is
no other common field in the database other than the street address,
so it looks like I'm stuck with trying to group them, somehow.

Given that limited information, it is probably not a trivial task.

There was a US patent granted:

Method of standardizing address data
US Patent Issued on August 20, 2002

http://www.patentstorm.us/patents/64...scription.html

You might be able to restrict how the addresses are entered, but that won't
help you with what you already have.

Possibly if you made a list of synonyms, gave each synonym a unique value, and
then sorted them by that. For example:

1st First
NW Northwest North West NorthW
1 One
--ron