Algorithm for matching objects
If your comparison works with "create a sum of all features and find those which the closest sum", there is a simple trick to get close objects:

Put all objects into an array
Calculate all the sums
Sort the array by sum.

If you take any index, the objects close to it will now have a close index as well. So to find the 5 closest objects, you just need to look at index+5 to index-5 in the sorted array.
I have 1,000 objects, each object has 4 attribute lists: a list of words, images, audio files and video files.
I want to compare each object against:

a single object, Ox, from the 1,000.
every other object.

A comparison will be something like:
sum(words in common+ images in common+...).
I want an algorithm that will help me find the closest 5, say, objects to Ox and (a different?) algorithm to find the closest 5 pairs of objects 
I've looked into cluster analysis and maximal matching and they don't seem to exactly fit this scenario. I don't want to use these method if something more apt exists, so does this look like a particular type of algorithm to anyone, or can anyone point me in the right direction to applying the algorithms I mentioned to this?