The power of learning categories (from features, because that is how
machine learning is done) has of course been my point throughout these
threads. (01)
With one only proviso, that the learning must be ad-hoc (the emphasis
on the process, not on any one result.) (02)
On Mon, Feb 8, 2010 at 6:19 AM, John F. Sowa <sowa@xxxxxxxxxxx> wrote:
> ...
> RC> Your hint about structuring properties into repositories is an
> > interesting one. Other than the very simple clustering approach
> > of FCA (formal concept analysis), I don’t know of approaches that
> > START with properties, other than my own stuff
> > http://www.englishlogickernel.com
> > and partition properties into groups.
>
> Actually, Aristotle thought of it first. The Tree of Porphyry from
> the 3rd century AD (see Figure 1 in the semnet.htm article) showed
> how categories and properties are interrelated. Ramon Lull in the
> 13th century had rotating disks for combining properties, and
> Leibniz was inspired by Lull to develop the first computational
> approach to developing a lattice of concept types. For a brief
> summary of both Leibniz's Universal Characteristic and FCA, see
>
> http://www.jfsowa.com/logic/math.htm#Lattice
>
> There have also been various conferences about the section of features
> or properties for data mining. See, for example, the following CFP. (03)
As I mentioned earlier, a form of this was also tried as a way to
learn grammar in the '30s and '40s. It fell out of favour because it
was found impossible to get a single consistent set of categories. A
result very like the impossibility of a single Foundation Ontology we
have been discussing. (04)
To the best of my knowledge there has been no systematic exploration
what can be achieved by "data mining" if the assumption of a single
consistent set of categories is abandoned and the focus put instead on
selecting categories appropriate to a problem to be resolved. Although
the success of indexed search could be seen as a form of this. (05)
I think it is far more important to abandon this assumption of a
single consistent set of categories than to explore different feature
sets, although different feature sets have their place. (06)
-Rob (07)
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