If you have a table with 16 columns, q1, q2 ..., q16, could you do the
following?

SELECT id, (abs(q1 - input1) + abs(q2 - input2) ... + abs(q16 - input16))
AS v FROM table ORDER BY v DESC LIMIT 0,10;

This way you can limit the size with a WHERE v > threshold, etc.

--Dan


On Fri, Apr 11, 2014 at 12:59 PM, Chris McCann <[email protected]>wrote:

> SD Ruby,
>
> I'm looking for a solution to a search problem and want to survey the
> community to see if anyone else has dealt with this type of search.
>
> The application I'm building supports an image processing system.  We have
> a mathematical way of uniquely representing any particular image as a
> vector of 16 values, each ranging between 0 and 255.
>
> I need to implement a search mechanism that finds the closest matches to a
> given image, also represented as a 16 element vector.  This is usually
> called a "vector space model" search, and it's implemented for full text
> search in Postgres as well as Lucene, and probably many other full text
> search systems.
>
> The problem I'm wrestling with is I'm not searching on text, I'm searching
> on integers.  I basically need to search for the closest match like this:
>
> Say my search image has a vector with elements q(1) to q(16),  [q(1) =
> 122, q(2) = 7, q(3) = 89,, ..., q(16) = 224].
>
> To compare that vector against the image vectors in the database I need to
> calculate the "distance" between the query vector (q) and each of the
> database vectors (d):
>
> distance = square_root( (q(1) - d(1))^2 + (q(2) - d(2))^2 + ... (q(16) -
> d(16))^2)
>
> The lower the distance the closer the match, with dist == 0 being an exact
> match.
>
> My research hasn't led me to a direct implementation of this in Postgres
> or Lucene since they are designed for text searching, though the underlying
> principles are the exact same.  Anyone ever tackle this type of search with
> numerical values?
>
> Thanks in advance,
>
> Chris
>
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