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I have a dataset of land parcels owned by the government and I am attempting to match street addresses to an existing list of government agencies. I've used fuzzy matching and used a regex that ignores casing and distinctions between direction (for example North and N are treated the same).

However, the program ends up having a very poor matching rate, as a lot of the addresses are not getting matched. What are some other ways I should try to improve the matching rate?

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  • $\begingroup$ Which government? The locale of the address might be relevant here. Can you post some examples of addresses and their matches? $\endgroup$ – Valentin Calomme May 8 at 11:36
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You can try using this to help: https://github.com/openvenues/libpostal

libpostal looks like it can normalize across various geographic styles with the expand addresses functions.

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