Similarity Metrics and Clustering and Merging of Positions

[Thomas von der Elbe]

Hello Kai,

welcome to the list!

> What I'm currently missing here (maybe I just didn't see it) is any
> discussion about the application of similarity metrics and clustering
> algorithms when it comes to the problem of reducing a vast amount of
> possible positions to a few that can be voted upon.
>   

What an interesting idea! Even though I dont see the need to reduce the 
amount of different positions in order to vote upon them.

I picture Votorola working like this: Everybody can have his own 
position, but because they are structured in trees, the vast amount of 
them will be arranged according to affinity. This will be done by the 
users themselves: they look for the best place to vote by going from the 
trunk of the tree further out to the leaves. This way they would only 
have to choose a few times (at each bifurcation) between a low number of 
alternatives. A difference-engine will help here by showing only the 
differences.

Another possible way to find your place to vote, would be through a 
classification-system, which shows clusters of positions suitable for 
you through tagging for example.

But the application you describe here, could maybe be used for the same 
purpose: as a search-engine for the most similiar position to yours in 
the whole tree/forest (or even across different voting-engines).

I like this idea!

Greetings,
Thomas