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I
don't think it weird but I'm not surprised by that. It is pretty
simple. We use markup over delimited ASCII
because we want to put more semantic hints as to the producer's
intent. If we want stronger hints, we go
to a
language like RDF to provide stronger linking among the signs. If we
want to send our intent and ensure
it
can't be misinterpreted, we package up the intentions/functions/methods with the
data and send that.
So
once again, if there is to be a pragmatic layer, and I assume that means
something codified in the
program or code that flips the bits on the machines, then other than
sharing a philosophy of meaningful
utterances, norms and affordances, how would one communicate those
utterances, norms, and affordances?
IOW,
what is above semantics? Pragmatics. How do we implement
pragmatics? Objects.
Other
means may be possible but that is a first position. Even an
interpreter for a set of RDF assertions
attempting to evaluate a text requires a functional
contextualizer.
len
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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