Hi Lydia,

I am currently drafting my proposal, I shall submit within a few hours once
the initial version is complete.

I installed mediawiki-vagrant on my PC and it went quite smoothly. I could
do all the usual things through the browser; I logged into the mysql server
to examine the database schema.

I also began to clone the
wikidata-vagrant<https://github.com/SilkeMeyer/wikidata-vagrant> repo.
But it seems that the 'git submodule update --init' part would take a long
time - if I'm not mistaken, it's a huge download (excluding the vagrant up
command, which alone takes around 1.25 hours to download everything). I
wanted to clarify something before downloading it all.

Since the entity suggester will be working with wikidata, it'll obviously
need to access the whole live dataset from the database (not the xml dump)
to make the recommendations. I tried searching for database access APIs or
high-level REST APIs for wikidata, but couldn't figure out how I to do
that. Could you point me to the proper documentation?

And also, what is the best way to add a few .jar files to wikidata and
execute them with custom commands (nohup java blah.jar --blah blah -->
running as daemons)? I can of course set it up on my development box inside
virtualbox - I want to know how to "integrate" it into the system so that
any other user can download vagrant and wikidata and have the jars all
ready and running? What is the proper development workflow for this?

Thanks,
Nilesh



On Sun, Apr 28, 2013 at 3:01 AM, Nilesh Chakraborty <nil...@nileshc.com>wrote:

> Awesome. Got it.
>
> I see what you mean, great, thank you. :)
>
> Cheers,
> Nilesh
> On Apr 28, 2013 2:56 AM, "Lydia Pintscher" <lydia.pintsc...@wikimedia.de>
> wrote:
>
>> On Sat, Apr 27, 2013 at 11:14 PM, Nilesh Chakraborty <nil...@nileshc.com>
>> wrote:
>> > Hi Lydia,
>> >
>> > That helps a lot, and makes it way more interesting. Rather than being a
>> > one-size-fits-all solution, as it seems to me, each property or each
>> type
>> > of property (eg. different relationships) will need individual attention
>> > and different methods/metrics for recommendation.
>> >
>> > The examples you gave, like continents, sex, relations like father/son,
>> > uncle/aunt/spouse, or place-oriented properties like place of birth,
>> > country of citizenship, ethnic group etc. - each type has a certain
>> pattern
>> > to it (if a person was born in the US, US should be one of the
>> countries he
>> > was a citizen of; US census/ethnicity statistics may be used to predict
>> > ethnic group etc.) I'm already starting to chalk out a few patterns and
>> how
>> > they can be used for recommendation. In my proposal, should I go into
>> > details regarding these? Or should I just give a few examples and
>> explain
>> > how the algorithms would work, to explain the idea?
>>
>> Give some examples and how you'd handle them. You definitely don't
>> need to have it for all properties. What's important is giving an idea
>> about how you'd tackle the problem. Give the reader the impression
>> that you know what you are talking about and can handle the larger
>> problem.
>>
>> Also: Don't make the system too intelligent like it knowing about US
>> census data for example. Keep it simple and stupid for now. Things
>> like "property A is usually used with value X, Y or Z" should cover a
>> lot already and are likely enough for most cases.
>>
>>
>> Cheers
>> Lydia
>>
>> --
>> Lydia Pintscher - http://about.me/lydia.pintscher
>> Community Communications for Technical Projects
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>


-- 
A quest eternal, a life so small! So don't just play the guitar, build one.
You can also email me at cont...@nileshc.com or visit my
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