
VP trees: A data structure for finding stuff fast - rcfox
http://stevehanov.ca/blog/index.php?id=130
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pornel
The cool thing about VP trees is that your space doesn't have to be Euclidean,
i.e. you can have dimensions that depend on other dimensions, e.g. in RGBA
color space values of RGB are meaningless when A=transparent. You can't search
that space with KD trees, but you can with VP trees.

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arnoldoMuller
VP trees are well known but not necessarily the best approach for large
datasets or high dimensional objects. I am creating a startup that offers the
fastest similarity search engine built so far (10X faster than LSH from MIT).
See more here: <http://simmachines.com>

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smspence
I don't understand how this is related to the article. The article has to do
with searching spatial data structures, such as you would make for
partitioning the space of a large scene in a graphics or mapping application
(or game, etc.). Maybe I'm wrong and someone could enlighten me....

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willvarfar
3D spatial problems are just three dimensions. True you can do that with VP
but you can do that with octtree too.

Imagine beyond 3D like clustering of friends or likes or recommendations or
all those other N-dimensional data-points and you'll see the overlap.

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joshu
Right. There are plenty of cases where you ONLY have the distance (or
similarity) between two points and don't actually have an n-dimensional point
in space.

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zrail
Am I the only one this link isn't working for? When I click on it I get
"index.php". file(1) says this:

    
    
        /Users/zrail/Downloads/index.php: data
    

Edit: Here's a link to what appears to be the original paper:

<http://pnylab.com/pny/papers/vptree/vptree/>

