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The idea comes from observing people copying and pasting addresses in Sorting Office.
When the user is not concerned about personal information of the addresses she's dealing with, she may be submitting to SO the name of the person alongside her address. This has two negative outcomes: the address may be less recognisable as a valid address and/or the person name may be confused for the house name.
By giving SO "dictionaries" of first and last names, and expecting these to be at the beginning of the address, we may detect people's names as such and drop them before attempting parsing the rest.
Moving to ready and flagging for community support even though final implementation is likely to be core team.
Community : any thoughts on how to implement this would be much appreciated?
We would want to import business names but not personal data.
We are prepared to learn over time what are personal names, but typically like a good starting list of stuff to exclude.
We need an algorithm that could, say, exclude "Rose Tyler" and remove 'Rose' from "Rose, 8 Tardis Towers" but would allow "Rose Avenue" to sail through as that is a reasonable road.
The idea comes from observing people copying and pasting addresses in Sorting Office.
When the user is not concerned about personal information of the addresses she's dealing with, she may be submitting to SO the name of the person alongside her address. This has two negative outcomes: the address may be less recognisable as a valid address and/or the person name may be confused for the house name.
By giving SO "dictionaries" of first and last names, and expecting these to be at the beginning of the address, we may detect people's names as such and drop them before attempting parsing the rest.
Moreover,
FYI @peterkwells .
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