On Thu, Sep 16, 2010 at 03:22:15PM +0200, Andreas wrote:
> We are talking about nearly 500.000 records with considerable overlapping.
Other things to consider is whether each one contains unique entries and
hence can you do a "best match" between datasets--FULL OUTER JOIN is
your friend here, but duplicates become a problem.
> It's not only typos to catch. There is variation in the way to write
> things that not necessarily are wrong.
> e.g.
> Miller's Bakery
> Bakery Miller
> Bakery Miller, Ltd.
> Bakery Miller and sons
> Bakery Smith (formerly Miller)
Soundex is tolerant to quite a lot of this, but word order is important.
When I've had to do this before ~360k merging with ~80k addresses I've
gone with normalised postcodes (in the UK postcodes contain a nice mix
of letters and numbers meaning that I can be reasonable sure about
typos) and then gone through a reasonable chunk by hand to make sure
things are working "correctly".
Just thought; depending on your spacial sparsity, you may be able
to get away with trusting the zip code and checking when the soundex of
the name is different.
> and the usual
> Strawberry Street
> Strawberrystreet
> Strawberry Str.42
> Strawberry Str. 42
> Strawberry Str. 42-45
Soundex gets those all the same (and even '42-45 Strawberry Str'), so
that's easy. In fact it completely ignores the numbers so you'll have
to do something specific about them.
--
Sam http://samason.me.uk/
