Inside Libpostal - a fast, multilingual, international street address parser trained on OpenStreetMap data · Mapzen

Inside #Libpostal - a fast, multilingual, international street address parser trained on OpenStreetMap data · Mapzen
▻https://mapzen.com/blog/inside-libpostal

https://s3.amazonaws.com/assets-staging.mapzen.com/images/inside-libpostal/address-parsing.gif

▻https://github.com/openvenues/libpostal

#nlp #machine_learning #text-mining #geocoding #géolocalisation #cli #outils

As a motivating example, consider the following two equivalent ways to write a particular Manhattan street address with varying conventions and degrees of verbosity:

> 30 W 26th St Fl #7
> 30 West Twenty-sixth Street Floor Number 7

Obviously ’30 W 26th St Fl #7 != ’30 West Twenty-sixth Street Floor Number 7’ in a string comparison sense, but a human can grok that these two addresses refer to the same physical location.