Thanks Erick, a follow-up question for RerankQParser: How complex can the rerank query itself be? Can we add multiple boost factors based on different conditions - say, if category is X boost by 2, if brand is Y boost by 3, etc.?
On Mon, 10 Feb 2020 at 18:12, Erick Erickson <erickerick...@gmail.com> wrote: > There isn’t really an “industry standard”, since the reasons someone > wants this kind of behavior vary from situation to situation. That said, > Solr has RerankQParserPlugin that’s designed for this. > > Best, > Erick > > > On Feb 10, 2020, at 4:23 AM, Nitin Arora <nitinaror...@gmail.com> wrote: > > > > I am looking for an efficient way for setting the MM(minimum should > match) > > parameter for my solr search queries. As we go from MM=100% to MM=0%, we > > move from lots of zero result queries on one hand to too many irrelevant > > results (which may then get boosted by other factors) on the other. I can > > think of multiple ways to approach this: > > 1) Try decreasing mm from 100% to 90% to 80% in a staggered manner till > you > > have just the right number of results. Does not sound very efficient > though. > > 2) Use a low value of MM, say 0%, and then pick only the top 200 results > to > > apply other boost factors to. Would not allow to use bf, bq, boost within > > SOLR. > > > > My question is, What is the standard industry practice in this matter. > How > > do you go about ensuring that your search returns *just the right* number > > of results so that you can use other boost functions on the relevant set > of > > results. > > > > Thanks in advance > > Nitin > >
