On 2012-07-18 3:51 AM, Tony Arcieri wrote:
The trust function is a collaborative filtering algorithm such as Slope One
or Singular Value Decomposition. The inputs to the trust function are
BitCoin style peer-specific "long chain" files of a peer's transfer history
that a given peer has collected through direct interaction. We might look
for the following: success/failure and transfer rate.
The first thing we do is build a sparse matrix of the similarity of all
peers to all other peers in the system (let's assume Slope One is the
algorithm for now). This is what we'll use for computing trust.
Now we actually do the collaborative filtering calculation: we look for
peers that are similar to ourself, by inputting our own transfer history
and the sparse matrix we calculated in the previous step.
The output should be peers similar to ourself: namely ones which experience
a similar history of success/failures and similar transfer rates. With
enough information, this should begin to reveal this like which peers are
"closest" to us on the network (i.e. least bottlenecked by the network
relative to us, not geographical closeness or closeness in the DHT)
What we want is peers that are trusted by entities like ourselves,
and/or have engaged in transactions that are beneficial to entities like
ourselves, not those that allegedly trust entities that we trust and
have allegedly engaged in transactions like those that we have engaged in.
Slope One and Singular Value Decomposition does not trivially give us
that, and it is not immediately obvious to me how to fix them to give us
that. I expect it can be done, just do not quite see how.
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