Thanks guys! Will play around with it function query.
Thanks,
-Utkarsh
On Tue, Jul 30, 2013 at 10:50 AM, Chris Hostetter
wrote:
>
> : bq: I am also trying to figure out if I can place
> : extra dimensions to the solr score which takes other attributes into
> : consideration
>
> To re-iterate er
: bq: I am also trying to figure out if I can place
: extra dimensions to the solr score which takes other attributes into
: consideration
To re-iterate erick's point, you should definitely look at using things
like the {!boost} qparser combined with funciton queries that take into
account pre-
bq: I am also trying to figure out if I can place
extra dimensions to the solr score which takes other attributes into
consideration
Have you looked at function queries? The whole point of them is
to do something that influences score, which may be quite
complex. There are ways to, say, multiply t
I agree with your comment on separating noise with the actual relevant
result.
My approach to separate relevant result with noise is not algorithmic but
an absolute measure, i.e. top 5 or top 10 results will always be relevant
(at-least the probability is higher).
But again, that kind of simple sor
You can certainly just include the attachment count in the
response and have the app apply the secondary sort. But
that doesn't separate the "noise" as you say.
How would you identify "noise"? If you don't have an algorithmic
way to do that, I don't know how you'd manage to separate
the signal
I have a solr query which has a bunch of boost params for relevancy. This
search works fine and returns the most relevant documents as per the user
query. For example, if user searches for: "iphone 5", keywords like
"apple", "wifi" etc are boosted. I get these keywords from external
training. The t
