David,
This is the link to the address standardizer:
https://github.com/woodbri/address-standardizer
This is a link to all my code that I developed consulting. It includes a
few SQL geocoders based on the code above. And has some README files
discussing how to build a geocoder which is the basis for how the
geocoders work.
https://github.com/woodbri/imaptools.com
this is the geocoder for Tiger data, but the code is essentially the
same for every country because the when you load country specific data
into the database it goes into its own table and then you standardize
that data into stdstreets table and all queries are done against the
stdstreets table and you only have to tweak the address range
interpolation function which needs to access the source streets table
for the geometry and house number ranges.
https://github.com/woodbri/imaptools.com/blob/master/sql-scripts/geocoder/prep-tiger-geo-new.sql
I would approach this by:
1. get the address standardizer compiled and installed. I can help if
you run into problems or have questions.
2. load your UK street data into rawdata schema, ideally it would be
best if we can create a table/view that presents this data as a single
table where each record represents one side of the street and one
jurisdiction this may mean that a single record in your source data will
generate multiple records in this table/view (this greatly simplifies
the coding and performance later)
3. look at the prep-tiger-geo-new.sql file
4. create a stdstreets table and standardize your table/view data into it
5. look at standardization failures and adjust lexicon and grammar as needed
6. loop back to 4 until good enough
7. load functions from prep-tiger-geo-new.sql file and adjust any for
your data
8. try it out!
-Steve
On 1/9/2021 10:22 AM, Shaozhong SHI wrote:
Hi, Stephen,
Many thanks. We are interested in it is working with the UK addresses.
Please send me the link to this.
Regards,
David
On Sat, 9 Jan 2021 at 15:00, Stephen Woodbridge
<[email protected] <mailto:[email protected]>>
wrote:
David,
Yup and this is just one a dozens of cases that you have to deal
with. You are dealing with a natural language processing problem.
And you have to deal with human input that has typos and
abbreviations.
These issues are what the address standardizer fixes. It tokenized
the address and uses the gazette to standardize the terms and then
classifies each term and assigns it to part of the address based
on a grammar.
So there is a simple solution, use my address standardizer, it is
free, MIT license, it has a sample lexicon/ gazette and grammar
for the UK, it is easy to modify these to fit your needs, and it
just works. Oh if you want to do another county it also has sample
files for 25 countries.
Sent from my iPhone
On Jan 9, 2021, at 4:42 AM, Darafei Komяpa Praliaskouski
<[email protected] <mailto:[email protected]>> wrote:
Hello,
People make neural networks for this kind of task:
https://github.com/openvenues/libpostal
<https://github.com/openvenues/libpostal>
сб, 9 сту 2021, 12:40 карыстальнік Shaozhong SHI
<[email protected] <mailto:[email protected]>> напісаў:
Hi, Steve W,
it is easy to parse addresses as tokens. But it is difficult
to put tokens in right columns, due to that the same address
could be expressed with partial address or full address.
The same address can be written like, Flat 1 122 Great Avenue
London UK, or Flat 1 122 Greet Avenue Central London London
United Kingdom.
When this happens, each address has different number of
tokens, so different numbers of tokens. Is there a way to
deal with this issue so that each token can get into right
column?
Please enlighten me.
Regards,
David
On Sat, 25 Apr 2020 at 05:09, Stephen Woodbridge
<[email protected]
<mailto:[email protected]>> wrote:
And I have create an address-standardizer project here
https://github.com/woodbri/address-standardizer
<https://github.com/woodbri/address-standardizer> which
is user
configurable. I might be over kill is you just want to
strip off the
number, in which case you might just use a SQL regexp
replace to remove it.
-Steve W
On 4/25/2020 12:04 AM, Stephen Woodbridge wrote:
> PostGIS has address_standardizer extension that includes
> parse_address() and standardize_address() functions.
>
> -Steve W
>
> On 4/24/2020 9:54 PM, Imre Samu wrote:
>> > handle addresses in postgresql
>>
>> maybe you can use the
https://github.com/openvenues/libpostal
<https://github.com/openvenues/libpostal> library
>> with your favorite language bindings ( Python / Ruby /
Go / PHP /
>> Node / R / Java ...)
>>
>> or as a Postgres database extension:
>>
https://info.crunchydata.com/blog/quick-and-dirty-address-matching-with-libpostal
<https://info.crunchydata.com/blog/quick-and-dirty-address-matching-with-libpostal>
>>
>> https://github.com/pramsey/pgsql-postal
<https://github.com/pramsey/pgsql-postal>
>>
>> Regards,
>> Imre
>>
>>
>>
>>
>> Shaozhong SHI <[email protected]
<mailto:[email protected]>
>> <mailto:[email protected]
<mailto:[email protected]>>> ezt írta (időpont:
2020. ápr. 25.,
>> Szo, 2:49):
>>
>> I find this is a simple, but important question.
>>
>> How best to split numbers and the rest of address?
>>
>> For instance, one tricky one is as follows:
>>
>> 21-1 Great Avenue, a city, a country, this planet
>>
>> How to turn this into the following:
>>
>> column 1, column 2
>>
>> 21-1 Great Avenue, a city, a
country, this planet
>>
>> Note: there is a hyphen in 21-1
>>
>> Any clue?
>>
>> Regards,
>>
>> Shao
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