Markus, could your algorithm work together with human direction? Like, if we entered which properties are common for a class, and then a user creates an instance of that class, would the algorithm be able to sort those properties based on how often they appear on the database?

Thanks,
Micru


On Tue, Jul 1, 2014 at 10:23 PM, Markus Krötzsch <markus@semantic-mediawiki.org> wrote:
On 01/07/14 22:14, Markus Krötzsch wrote:
...


(2) "Grade I listed building"
http://tools.wmflabs.org/wikidata-exports/miga/?classes#_cat=Classes/Id=Q15700818


Related properties: English Heritage list number, masts, Minor Planet
Center observatory code, home port, coordinate location, OS grid
reference, mother house, architect, manager/director, Emporis ID,
MusicBrainz place ID, country, architectural style, visitors per year,
Commons category, Structurae ID (structure), officially opened by,
floors above ground, inspired by, religious order, number of platforms,
street, owned by, diocese

These are computed fully automatically from the data, with no manual
filtering or user input. But don't get me wrong -- great work! Brilliant
to have such a thing integrated into the UI. In any case, my algorithm
for computing the related properties is certainly very different from
theirs; I am sure it also has its glitches.

P.S. One weakness of my algorithm you can already see: it has troubles estimating the relevance of very rare properties, such as "Minor Planet Center observatory code" above. A single wrong annotation may then lead to wrong suggestions. Also, it seems from my list under (2) that some Grade I listed buildings are ships. This seems to be an error that is amplified by the fact that property "masts" is used only 11 times in the dataset I evaluated (last week's data). I guess the new property suggester rather errs on the other side, being tricked into suggesting very frequent properties even in places that don't need them.

-- Markus



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