Re: HM.Frameworks: Physical Description

[Rob Nixon <robnixon@execpc.com>]

This is the first contribution I've made to this list.  I've been thinking along the same lines regarding the "intensity" measure of arc strength that Kurt mentioned.   I would say that this is more than just an observation, I believe that a mechanism such as this would be an important addition.

Rob

Kurt Cagle wrote:

I'm noticing on the discussion on arcs (kindaLike, etc.) that we seem to be moving into a Fuzzy Logic (FL) realm. It occurs to me that it may be worth either labeling or supporting arcs with an intensity indicator as well [0,1] that would provide a mechanism for correlation across a specific operator. For instance, if you have an arc operator of "Like" then a like intensity of 0 would correspond to no correlation (the arc between the two entities implies no correlation) while an intensity of 1 would imply total correlation (1 is a synonym for the other) and an intensity of 0.7 would indicate that there is a certain amount of correlation (the two are similar but not the same). While for some of the arcs being dealt with these intensities are largely subjective, the same can be said for HumanML in general. I'd push this approach for a couple of reasons. First of all, it makes it possible to follow correlative links into a hyper-linked environment, making it feasible to provide a point at which point information ceases being reliably relevant.  For instance, if you had an arc:      Like at 0.7A ---------------------> B and another arc      Like at 0.8B ---------------------> C then you can view the arc A->C as being similar at 56% (which could be interpreted as there is about a 1 in 2 chance that the two nodes are highly similarly, or more accurately that there is a 56% correlation between A and C). You could then follow a grove of nodes pruning those that fall below a certain threshhold (say 0.1 correlation) as no longer being relevant to the current arc. This also makes it possible to perform other analytical metrics (Bayes, for instance) or to determine the mean relevance of a tree to a given node. This is just an observation, do with it as you will. -- Kurt