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From Vaghawan Ojha <>
Subject Re: How Does The Score Works In UR
Date Sat, 08 Apr 2017 04:27:38 GMT
Hi Pat,

Thank you very much for the explanation, seems like I forgot to properly
search this question in the group. By ranking you means the order of the
product right?

Also I wanted to replicate such dot products of all user history vector
segments against the correlator fields in the model in a very very small
data, so that I could have a test of what's really working behind. And also
I wanted to learn about the implicating algorithms. I've seen the
presentation in the doc site of UR. Should you have any resources which
could lead me to better understand all these please point me.


On Sat, Apr 8, 2017 at 12:16 AM, Pat Ferrel <> wrote:

> The limit depends on your data. I tell people to ignore the value as you
> do when searching (no one uses the score when doing searches do they?) Only
> the ranking/ordering makes any real difference.
> The score is the sum of dot products of all user history vector segments
> against the correlator fields in the model. If you boost or add properties
> to your queries they multiply times some of the dot products before
> summation. So given any boosting the max is hard to state and we have found
> no particular use for it. Other tuning parameters give you the best ways of
> affecting the score so looking at the score afterwards is not very helpful
> except to rank results.
> On Apr 7, 2017, at 1:02 AM, Vaghawan Ojha <> wrote:
> Hi,
> I was just curious, how does the score works in the UR, I've seen the UR
> presentation in the documentation site, but I couldn't be sure what it
> really signifies.
> For example: what's the limit of the score? What's the possibly highest
> score?
> Thanks
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