What I like about the way this is done at Reltio is the transparency. You can really 'calculate' the score and get predictable results. Many of us have seen other technologies that have a real 'black box' approach. In my consulting days, I was trying to debug some matching and found that a change of a single letter could lead to scores that were 20+ points higher/lower. You just never know what you were going to get.
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Gino Fortunato
Senior Solution Engineer
Reltio
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Original Message:
Sent: 01-27-2023 14:10
From: Suchen Chodankar
Subject: Does the scoring algorithm at the backend also works in the same way..?
The score that comes out of the Levenshtein algorithm is not used as is. We have our internal algorithm for generating the relevance score, which is for Levenshtein algorithm it is, I think I documented here so that we all can see it here. It's a distance between S one and S two, which is the Levenshtein algorithm provides. And then we have divided it by the maximum length of string one and length of S two. So that is for the Levenshtein algorithm. For the dynamic one, we have slightly different one here. I think the answer that you're looking for is whether we are using the value that is coming from this algorithm as is, the answer is no. This gives us similarity as 50% between Robert and Robbie. If we were to use the Levenshtein algorithm as is, this could be slightly lower, which is why we are not using this formula now. I hope that answers your question.
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Suchen Chodankar
Original Message:
Sent: 01-27-2023 14:07
From: Chetan P
Subject: Does the scoring algorithm at the backend also works in the same way..?
This is regarding Traditional Matching Rule which follows Edit distance concept. Based on reviewing Reltio's advanced match rule i can see Damerau–Levenshtein comparator functionality match to the same. For example, "Difference between the pattern based on multiple hops determining the score between two strings?"
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Chetan P
Senior MDM Specialist
Freshworks
Chennai
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