One of the things that I'm focusing on is combining the Solr similarity score with the vector score in a consistent manner. My main concern is dealing with the unbounded nature of the Solr similarity score and how to balance that with a vector score.
So my first question are there any mechanisms now to scale or squash the Solr similarity score before combining with a vector score? Below are two ideas I have for squashing / scaling the score: 1) SquashingScoreQuery. This is a wrapper query that squashes the score of its wrapped query using a sigmoid function. 2) Min/Max scale the main query score in the ReRanker. This simply adds a flag to the ReRanker to min/max scale the main query scores before combining with the ReRank query. Do others have thoughts on this?
