It's weird how stuff bubbles up from the back of your brain...

[elfs]

Last night I realized that, given you have two vectors in a 3-dimensional space starting from the same point that are not the same vector, that those two vectors create a plane-- then the same is true for any n-dimensional space. 3 dimensionas, 10 dimensions, 40 dimensions, it doesn't matter.

Why is this important? Simple; once you've identified the plane, you can find the angle between the two vectors.

If can get two people to answer 100 yes or no questions, you can create two vectors in a 100-d space and find the angle between those vectors. Those people with the smallest angle will have the greatest similarities in response. This is the basis of a vast number of recommendation engines.

It was the n-dimensionality that was bugging me. I finally grasped how little that matters in the end.

Comments

[ivolucien.livejournal.com]

<nods> I'm doing something similar with my project, but in addition to the general "plane" I'm working with categorically related sets of responses as distinct entities in order to support goal specificity and human-centric search, sort and filter functionality. I'm still playing with modeling options, and the assignment of "intensities" as you say, will be a process of ongoing refinement.

Have you run across any articles or related info that you could easily point me to? I'm always looking for fuel for the creative fire. ^_^