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From Joao Palotti <joaopalo...@gmail.com>
Subject SOLR Learning to Rank Questions
Date Thu, 03 Aug 2017 10:14:38 GMT
​
Dear all,

First of all, I would like to thank you guys for the amazing job with SOLR.
In special, I highly appreciate the learning to rank plugin. It is a
fantastic work.

I have two
​ ​
two questions for the LTR people and I hope this mailing list is the right
place for that.

*1)​ ​This is a direct implementation doubt:*

Let's say that I have the popularity of my documents (document hits) in an
external SQL database instead of saving it in the index.

Can I use this information as a feature? How?


*2) This is slightly more philosophical than a practical question:*

Let's say I would like to normalize the score of my documents, for example,
with MinMaxNormalizer. If I correctly understood it, I would have to
calculate the min and the max values for the score seen in the training set
and upload these values in my model.
When using the model, MinMaxNormalizer will apply its normalization formula
for each value retrieved based on the max and the min set in the model.

Although this is a valid approach, I see it as a global approach, not a
local (per query) one.
Hope you understand what I am talking about here.

I was expecting to have a MinMaxNormalizer without previously min and max
set. This would simply apply the min_max formula to all results for
each query. Thus, when I use this new approach, the first document would
have score 1.0 and the last document retrieved would have score 0.0.

Would it be better to normalize per query instead of a global normalization?


Thanks a lot in advance.
Looking forward to hearing back from you soon.

Best,
--
João Palotti
Website: joaopalotti.com
Twitter: @joaopalotti <https://twitter.com/joaopalotti>
Me at Google Scholar
<https://scholar.google.com/citations?user=ZEoF2A4AAAAJ&hl=en>

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