It can be basically any thing you can do with a standard Solr query.
> On Feb 13, 2020, at 9:09 AM, Nitin Arora <nitinaror...@gmail.com> wrote:
>
> 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
>>
>>
