On Wed, Jan 20, 2016 at 9:34 PM, David Causse
<dcausse(a)wikimedia.org
<javascript:_e(%7B%7D,'cvml','dcausse@wikimedia.org');>> wrote:
Hi,
Yes we can combine many factors, from templates (quality but also
disambiguation/stubs), size and others.
Today cirrus uses mostly the number of incoming links which (imho) is
not very good for morelike.
On enwiki results will also be scored according the weights defined in
https://en.wikipedia.org/wiki/MediaWiki:Cirrussearch-boost-templates.
I wrote a small bash to compare results :
https://gist.github.com/nomoa/93c5097e3c3cb3b6ebad
Here is some random results from the list (Semetimes better, sometimes
worse) :
$ sh morelike.sh Revolution_Muslim
Defaults
"title": "Chess",
"title": "Suicide attack",
"title": "Zachary Adam Chesser",
=======
Opening text no boost links
"title": "Hungarian Revolution of 1956",
"title": "Muslims for America",
"title": "Salafist Front",
$ sh morelike.sh Chesser
Defaults
"title": "Chess",
"title": "Edinburgh",
"title": "Edinburgh Corn Exchange",
=======
Opening text no boost links
"title": "Dreghorn Barracks",
"title": "Edinburgh Chess Club",
"title": "Threipmuir Reservoir",
$ sh morelike.sh Time_%28disambiguation%29
Defaults
"title": "Atlantis: The Lost Empire",
"title": "Stargate",
"title": "Stargate SG-1",
=======
Opening text no boost links
"title": "Father Time (disambiguation)",
"title": "The Last Time",
"title": "Time After Time",
Le 20/01/2016 19:34, Jon Robson a écrit :
I'm actually interested to see whether this
yields better results in
certain examples where the algorithm is lacking [1]. If it's done as
an A/B test we could even measure things such as click throughs in the
related article feature (whether they go up or not)
Out of interest is it also possible to take article size and type into
account and not returning any morelike results for things like
disambiguation pages and stubs?
[1]
https://www.mediawiki.org/wiki/Topic:Swsjajvdll3pf8ya
On Wed, Jan 20, 2016 at 9:47 AM, Adam Baso <abaso(a)wikimedia.org
<javascript:_e(%7B%7D,'cvml','abaso@wikimedia.org');>> wrote:
> One thing we could do regarding the quality of the output is check
> results
> against a random sample of popular articles (example approach to find
> some
> articles) on mdot Wikipedia. Presuming that improves the quality of the
> recommendations or at least does not degrade them, we should consider
> adding
> the enhancement task to a future sprint, with further instrumentation
> and
> A/B testing / timeboxed beta test, etc.
>
> Joaquin, smaxage (e.g., 24 hour cached responses) does seem a good fix
> for
> now for further reduction of client perceived wait, at least for
> non-cold
> cache requests, even if we stop beating up the backend. Does anyone
> know of
> a compelling reason to not do that for the time being? The main thing
> that
> comes to mind as always is growing the Varnish cache object pool -
> probably
> not a huge deal while the thing is only in beta, but on the stable
> channel
> maybe noteworthy because it would run on probably most pages (but
> that's
> what edge caches are for, after all).
>
> Erik, from your perspective does use of smaxage relieve the backend
> sufficiently?
>
> If we do smaxage, then Web, Android, iOS should standardize their URLs
> so we
> get more cache hits at the edge across all clients. Here's the URL I
> see
> being used on the web today from mobile web beta:
>
>
>
https://en.m.wikipedia.org/w/api.php?action=query&format=json&forma…
>
>
> -Adam
>
> On Wed, Jan 20, 2016 at 7:45 AM, Joaquin Oltra Hernandez
> <jhernandez(a)wikimedia.org
> <javascript:_e(%7B%7D,'cvml','jhernandez@wikimedia.org');>>
wrote:
>
>> I'd be up to it if we manage to cram it up in a following sprint and
>> it is
>> worth it.
>>
>> We could run a controlled test against production with a long batch of
>> articles and check median/percentiles response time with repeated
>> runs and
>> highlight the different results for human inspection regarding
>> quality.
>>
>> It's been noted previously that the results are far from ideal (which
>> they
>> are because it is just morelike), and I think it would be a great
>> idea to
>> change the endpoint to a specific one that is smarter and has some
>> cache (we
>> could do much more to get relevant results besides text similarity,
>> take
>> into account links, or see also links if there are, etc...).
>>
>> As a note, in mobile web the related articles extension allows
>> editors to
>> specify articles to show in the section, which would avoid queries to
>> cirrussearch if it was more used (once rolled into stable I guess).
>>
>> I remember that the performance related task was closed as resolved
>> (
https://phabricator.wikimedia.org/T121254#1907192), should we
>> reopen it or
>> create a new one?
>>
>> I'm not sure if we ended up adding the smaxage parameter (I think we
>> didn't), should we? To me it seems a no-brainer that we should be
>> caching
>> this results in varnish since they don't need to be completely up to
>> date
>> for this use case.
>>
>> On Tue, Jan 19, 2016 at 11:54 PM, Erik Bernhardson
>> <ebernhardson(a)wikimedia.org
>>
<javascript:_e(%7B%7D,'cvml','ebernhardson@wikimedia.org');>>
wrote:
>>
>>> Both mobile apps and web are using CirrusSearch's morelike: feature
>>> which
>>> is showing some performance issues on our end. We would like to make
>>> a
>>> performance optimization to it, but before we would prefer to run an
>>> A/B
>>> test to see if the results are still "about as good" as they are
>>> currently.
>>>
>>> The optimization is basically: Currently more like this takes the
>>> entire
>>> article into account, we would like to change this to take only the
>>> opening
>>> text of an article into account. This should reduce the amount of
>>> work we
>>> have to do on the backend saving both server load and latency the
>>> user sees
>>> running the query.
>>>
>>> This can be triggered by adding these two query parameters to the
>>> search
>>> api request that is being performed:
>>>
>>> cirrusMltUseFields=yes&cirrusMltFields=opening_text
>>>
>>>
>>> The API will give a warning that these parameters do not exist, but
>>> they
>>> are safe to ignore. Would any of you be willing to run this test? We
>>> would
>>> basically want to look at user perceived latency along with click
>>> through
>>> rates for the current default setup along with the restricted setup
>>> using
>>> only opening_text.
>>>
>>> Erik B.
>>>
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