On Friday, March 18, 2016 2:19 PM, apa...@elyograg.org wrote: > > The "max score" of a particular query can vary widely, and only has meaning > within the context of that query. > One query on an index might produce a max score of 0.944, so *every* document > has a score less than one, > while another query *on the same index* (that might even have some of the > same result documents) > might produce a max score of 12.7, so the top docs have a score *much* higher > than one. > > If your additive boost is 5, this represents a relative boost of over 500 > percent for the top docs > of the first query I talked about above, but less than 50% for the top docs > of the second.
Thanks Shawn. I think I understand. I guess I was stuck in the mindset of having all original scores within a defined interval. Although I still don't fully understand why solr can't normalize the score, so it is always between say 0.0 and 100.0. Because surely solr knows what the maximum "raw score" is. Sure, I have read the page "Scores As Percentages", but the main argument there against a normalized score seems to be that it still doesn't make different queries truly "comparable", but that's not what I'm after anyway. I would only use the normalized score in my own boost calculation, nothing else. But, anyway... Since the score(1+boost...) suggestion from Upayavira solves the problem with weights, I guess I will start using multiplicative boosts now. :) But it would be nice to see how other people handle weighted boosts. And, in general I find it a bit hard to find concrete examples of queries where one combines multiple boost factors (like date recency, popularity, document type etc). Most documentation seem to focus on *one* factor only. Like "this is how you sort/score based on popularity", "this is how you get more recent documents first" etc... /Jimi
