JFS > I sympathize with the logical positivists for wanting to use symbolic
> logic to state the facts and theories of science. That is possible.
> But it's *impossible* to formalize the preliminary stages of debate
> and analysis *prior to* formalization. (01)
John, do you think the recent work on standardization, specifically on
ontologies, has brought us any closer to the formalization step? If
so, what, if any, are the fields which are headed in that direction?
We don't have the terms yet, but if we share a common language, (OWL,
CL, etc), are we any closer to this step? (02)
JFS> The simple reason is that mathematics of any kind (including symbolic
> logic) makes statements with sharp, absolute criteria of precision.
> (Even fuzzy logic and probability theory make precise statements
> about fuzziness and probabilities.) In the initial unsettled stages
> of research, such precision is impossible. It's also impossible to
> quantify the exact amount of fuzziness. That's why ordinary language
> is far better suited to the *development* of a theory than to the
> final statement of the theory. (03)
Fields such as fuzzy logic and probability theory let us make
statements about the world based on empirical data. Classification
algorithms, specifically tree based ones like C4.5, are completely
based on attributes and their values. They generalize using tree
pruning and raising. Even in natural language, saying that something
is "small" has to be taken within the context of that sentence. (04)
I recognize that not all things can be interpreted with the methods of
logical positivists, but I'm wondering whether there is a point where
statistical analysis can take over where we simply don't know enough
about a topic to infer information using logic alone. (05)
--
Bart Gajderowicz
MSc Candidate, '10
Dept. of Computer Science
Ryerson University
http://www.scs.ryerson.ca/~bgajdero (06)
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