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Algorithm behind duplicate check rule

Our customer is asking us what the algorithm is behind the configuration of the duplicate check rule.

For example let's assume I want a duplicate check based only on the customer name. What is the effect of moving the weighting factor up and down. Is 100 used for exact matches and does the check become more fuzzy when going to 0?

What happens when you mix up several parameters (e.g. name and address)?

How are name and address defines? concatenation of specific fields? Which ones?

It would be great if SAP could document this Black Box. The alternative for our customer is to waste hours via trials and errors....

Former Member
replied

Hi Thomas,

That was an awesome response, was always a grey area.

Meanwhile, for the below scenario, would like to understand if the algorithm still applicable.

Name = Bond
E-mail = j.bond@mi6.com

Let’s say there is already this DUPLICATE contact existing on the database:
Name = Bond
E-mail = j.bond@mi6.com

Same customer name and email address --> This is more applicable in Email/SMS to Ticket.(Ticket creation automatically linking the customer - when the customer send an sms or email)

Wished to understand what logic the system applies, to pick the customer when there are duplicate records.

Gab said the team is looking into, but this is quite an urgency for our implementation.

Is the Levenshtein algorithm still applicable in this scenario ?

Many thanks,

Vinod

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