- From: Shaw, Ryan <ryanshaw@unc.edu>
- Date: Tue, 14 Jul 2020 23:48:15 +0000
- To: Ivan Bashkirov <ivan.bashkirov@opencorporates.com>
- CC: "public-reconciliation@w3.org" <public-reconciliation@w3.org>
Hello, Here's our attempt to explain how we calculate our reconciliation scores: https://github.com/periodo/periodo-reconciler#how-reconciliation-works In practice, I don't know how interpretable the scores are even given this explanation. Cheers, Ryan > On Jul 12, 2020, at 9:58 AM, Ivan Bashkirov <ivan.bashkirov@opencorporates.com> wrote: > > Hi all, I have a question about approaches services are using to produce a reconciliation score that is meaningful to the end users. > > Crucially, we want the users to know why the score is what it is, and how they can make it better. As I understand, most reconciliation services produce a somewhat abstract score from 0 to 100 that roughly translates as "confidence", or "probability" that the result is the one a user is looking for. It would be great to hear what strategies people are using to produce the score.
Received on Tuesday, 14 July 2020 23:48:29 UTC