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Re: [xml-dev] Mailmen, POST, Intent, and Duck Typing
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That's weird. It's an inversion of what is expected. But I think what
you are referring to is what happens when things are schematised. OO
programmers want to know "how to do it", so laying out a schema is
considered "helpful". But the issue is whether there is room for the
unexpected. This is another way of looking at these issues. Too much
risk is just too risky, but no risk is boring. When I read a book I
take risks in my interpretation of what I am reading, the risks are
meant to expand my interest, in the broadest sense. When I read a book
(search through texts) I determine what are the patterns of interest.
But we are all thinking about applications such as text searching in an
educational context as just an example, where that connection making
and the attendant risk, is delegated to others. For instance the
program designer might incorporate an anonymous recommendation system
that works on some algorithmic assessment of how the material in
question is used, quite possibly something quite similar to what an
individual would do in assessing the potential interest of a text
anyway (i.e. what are people saying about that book!).
As you say, we don't want all the results to be homogenized. Indeed, we
shouldn't want something that has been available previously in a
different and, arguably, better form (word of mouth).
There are very definite constraints on how such programs can be
designed if they are not just gimmicks. Certainly one axis is that or
risk, and the analysis of that must take into account the consequences
of delegating that risk. The situation of a human actor can also be
usefully contrasted with that of a machine as the evaluation of risk
differs from one to the other.
BTW I don't think one should confuse how to do something with what it
is that gets done. The purpose and intent of communicative acts may be
amenable to codification in a computer program such that signs are
passed as symbols. All that has happened, though, is that a
communication has taken place within the expected parameters designed
around it.
Adam
On 27/02/06, Bullard, Claude L (Len) <len.bullard@intergraph.com> wrote:
Less
that that. The pragmatic layer ovoer the semantic web may simply be
the Revenge of the OOPMen (Object-oriented Programmers).
If
pragmatics as linguistics is about the purpose/intent of speech acts, then in a
computer system, a fully-laden purposeful data structure
comes
with its own methods. If signs are just typed arguments passed among
functions and passing objects is a means to pass
a
purposeful data structure, then Pragmatics On The Web comes down to
object-oriented programming on the top of RDF/CG, not
statistical divination or theory of mind.
If so,
it's a movie we've already seen. It was good on the big screen and
sorta dorky on the little screen, but I'm sure cable will
replay
it as often as they can.
len
Len,
this is
very interesting. First time I have come across Grice outside of academic,
linguistic circles. What I had read of his I always thought it must be
applicable to ontology reasoning, but never took the thought further. It is
interesting that the Grician contribution is classified as pragmatics, the
classification Peirce gave his own logic.
Thanks (all) for this
thread.
The
fact that "dumb" Bayesian
networks with no semantic formalisms have been
much more successful
than expert systems in classifying spam, and
therefore much more
useful to real people, is perhaps a beacon in this
regard.
There are those who attempt to combine the two
(losing the "purity" of both), each node of an ontology tree computed against
a statistical algorithm.
But the intriguing thing about statistical
analysis is that in some way it is not "dumb", it really is an open question
as to how neural type networks map into brain/human social functioning.
Stochastic process and models of these processes are often givens in
psychological research, i.e. a neural net model may be taken as sufficient to
model peripheral processes to that under investigation.
Ontologies are
convenient ways of organising information that take some of their convenience
from the fact that their structure contains information. But there is no
reason to believe that because an ontology can be generated it is a discovery
of what already exists, on the contrary, it is an intellectual invention that
provides short cuts to implied knowledge in some circumstances. C.S. Peirce
demonstrated the logical necessity of the underlying relationships, not
particular, specific ontologies.
I think that the issues are not of the
complexity of the machine, but the complexity of the user if the user is
human. Methods that may work for machine <-> machine negotiation may not
work for human <-> machine, pragmatically speaking. I think this is an
area for research and clarification.
Adam
On 24/02/06, Bullard,
Claude L (Len) <len.bullard@intergraph.com>
wrote:
If
I make a bet on the cat being dead, does that
alter the probability, the
fact, or in any way
change the need to open the box and look?
On
the other hand, if I am making a bet on
spam, my risks are lower than the
cat betting
that I am going to open the box.
Given the frequency
of spam, the occasional
misclassification is a low cost event,
strictly
speaking although there is a probability that
I will miss
something important.
Pragmatic systems are learning
systems.
len
From: Chris Burdess [mailto:d09@hush.ai]
The fact that "dumb"
Bayesian
networks with no semantic formalisms have been much more
successful
than expert systems in classifying spam, and therefore much
more
useful to real people, is perhaps a beacon in this
regard.
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