I used a popularity score based on the DVD being in people’s queues and the
streaming views. The Peter Jackson films were DVD only. They were in about 100
subscriber queues. The first Twilight film was in 1.25 million queues.
Now think about the query “twilight zone”. How do you make “Twilight”
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,
> whil
On Friday, March 18, 2016 3:53 PM, wun...@wunderwood.org wrote:
>
> Popularity has a very wide range. Try my example, scale 1 million and 100
> into the same 1.0-0.0 range. Even with log popularity.
Well, in our case, we don't really care do differentiate between documents with
low popularity.
On Friday, March 18, 2016 4:25 PM, wun...@wunderwood.org wrote:
>
> That works fine if you have a query that matches things with a wide range of
> popularities. But that is the easy case.
>
> What about the query "twilight", which matches all the Twilight movies, all
> of which are popular (mil
You can also use functions to “compress” the source number, so that the
effect of a certain boost becomes bigger or smaller compared to the other
boost you have.
--
Jan Høydahl, search solution architect
Cominvent AS - www.cominvent.com
> 17. mar. 2016 kl. 23.21 skrev Upayavira :
>
> Yes. Boost
Think about using popularity as a boost. If one movie has a million rentals and
one has a hundred rentals, there is no additive formula that balances that with
text relevance. Even with log(popularity), it doesn’t work.
With multiplicative boost, we only care about the difference between the one
Hi,
After reading a bit on various sites, and especially the blog post "Comparing
boost methods in Solr", it seems that the preferred boosting type is the
multiplicative one, over the additive one. But I can't really get my head
around *why* that is so, since in most boosting problems I can thi
On Friday, March 18, 2016 5:11 PM, wun...@wunderwood.org wrote:
>
> I used a popularity score based on the DVD being in people's queues and the
> streaming views.
> The Peter Jackson films were DVD only. They were in about 100 subscriber
> queues.
> The first Twilight film was in 1.25 million
Yes. Boosting adjusts an existing score. That original score can vary,
e.g. depending upon how many search terms there are.
If you use additive boosting, when you add a boost to a search with one
term, (e.g. between 0 and 1) you get a different effect compared to when
you add the same boost to a s
On Thursday, March 17, 2016 11:21 PM, u...@odoko.co.uk wrote:
>
> If you use additive boosting, when you add a boost to a search with one term,
> (e.g. between 0 and 1)
> you get a different effect compared to when you add the same boost to a
> search with four terms (e.g. between 0 and 4).
Wo
On 3/18/2016 6:34 AM, jimi.hulleg...@svensktnaringsliv.se wrote:
> I'm not sure I follow your logic now. If one can express the popularity as a
> value between 0.0 and 1.0, why can't one use that, together with a weight
> (indicating how much the popularity should influence the score, in general)
On Thursday, March 17, 2016 7:58 PM, wun...@wunderwood.org wrote:
>
> Think about using popularity as a boost. If one movie has a million rentals
> and one has a hundred rentals, there is no additive formula that balances
> that with text relevance. Even with log(popularity), it doesn't work.
I
That works fine if you have a query that matches things with a wide range of
popularities. But that is the easy case.
What about the query “twilight”, which matches all the Twilight movies, all of
which are popular (millions of views). Or “Lord of the Rings” which only
matches movies with hundr
Popularity has a very wide range. Try my example, scale 1 million and 100 into
the same 1.0-0.0 range. Even with log popularity.
As another poster pointed out, text relevance scores also have a wide range.
In practice, I never could get additive boost to work right at Netflix at both
ends of th
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