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>
