SUO: Re: automating abduction?
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Deju Vu & More Reading --
| These sorts of issues arose in the cognitive sciences a few years ago
| under the name of the "prior ordering of hypotheses" problem. There
| is a nicely edited volume, whose discussion centers around a dialogue
| between Jean Piaget and Noam Chomsky, that provides a flavor of one of
| the high points of the whole topic, as it was playing out at that time,
| but, sadly, it also betrays the many ways that people just kept on
| talking past each other.
|
| Massimo Piattelli-Palmarini (ed.),
|'Language and Learning: The Debate between Jean Piaget and Noam Chomsky',
| Harvard University Press, Cambridge, MA, 1980. French edition:
|'Théories du langage, théories de l'apprentissage, Editions du Seuil, 1979.
| Original debate held in October 1975.
|
| As you can well imagine, it was in vain that I suggested to my many cohorts
| at the time that a reclusive American farmer-philosopher, who flourished --
| or was it "fluoresced"!? -- somewhat earlier in that benighted century just
| nearly passed, might conceivably have had anything pertinent or impertinent
| to say on the matter. Since Chomsky -- not among my cohorts, that was another
| garden altogether! -- was just about the only major participant in the fray who
| quoted Peirce with any sort of regularity or who gave him much credit by name,
| no matter how many there were who repeated his phrases without seeming to know,
| or to care, who said them first, well, for these reasons and others I did not
| stick around to see how the discussion turned out. Somehow, I doubt if the
| tenor of it has progressed even as far as Peirce had already gotten by 1865.
|
| There is, naturally enough, the analogous set of issues that arise in the theories
| of probability and statistics, under the name of the "reference class" problem, if
| I remeber correctly, and it seems like a nice discussion of this, among many other
| interesting things, was given in a Peircean context by none other than Arthur Burks.
|
| Arthur W. Burks,
|'Chance, Cause, Reason: An Inquiry into the Nature of Scientific Evidence',
| University of Chicago Press, Chicago, IL, 1977.
Jon Awbrey
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Tom Johnston wrote:
>
> Richard:
>
> I know John Sowa recommends an automatic ontology category generation
> mechanism as well. But I don't understand how it would work. If you
> can send me any references, I'd appreciate it.
>
> Here's an example of what puzzles me about how we could automatically
> generate higher level ontological categories.
>
> One heuristic that comes to mind is that whenever two or more entities
> share identical attributes (assume everything is well-defined), we can
> create a supertype and move the common attributes up to it. In this way,
> an algorithm could generate, for any set of tables, a next-level-up set of
> supertype tables. Iterating the process, we would end up with a multi-level
> ontology with a single entity as the highest entry (the ousia/"thing"/substance
> entity). In an OO environment, the existence of one or more common methods
> would probably suffice, even if there were no common attributes.
>
> This seems based on the principle that a supertype (I'm talking in terms of
> relational data models, now) of a set of entities exists whenever that set
> shares one or more attributes in common. This makes for tidier databases
> and, in an OO environment, simpler code.
>
> If I had time (or if you request it), I would (or will) develop an example
> in which this heuristic generates a plethora of supertype entities, with
> many starting entities defined as subtypes of many of those supertype
> entities -- a "spaghetti" structure, in other words. OK, here's one quick
> example. Consider a Parts table in a manufacturing database, and the many
> tables which contain a foreign key back to Parts (the Inventory and Bill of
> Materials tables, for example). Should we define a supertype for Inventory
> and Bill of Materials on the basis of this one common attribute? If so, it's
> name would be something like "Things Related to Parts". Every transaction
> table, in any database, will have a date-time-entered attribute. Should all
> transaction tables then be subtypes of a "Transaction Date-Time" supertype
> table? If not, how would an algorithm using this heuristic weed out such
> fluff? Or are there other algorithms that won't generate fluff?
>
> In this structure, many of the generated entities would seem, intuitively,
> to be wrong, to not correspond to a "natural kind" in the real world. Since
> the human user is part of the information system, along with the codebase
> and the database (a point I have emphasized in several articles of mine, and
> which I think John Sowa might approvingly interpret as a bit of the semiotic
> perspective on my part), it is important for our entities to be intuitive,
> to seem to represent "natural kinds"; for otherwise, we will use the
> database incorrectly, populating it with category mistakes and often
> not being sure how to frame a query to get what we want from it.
>
> So: how can an algorithm generate natural kinds?
>
> Tom
>
> -----Original Message-----
> From: Richard Cooper [mailto:rich@valutech.com]
> Sent: Wednesday, August 27, 2003 12:24 PM
> To: Tom Johnston; John F. Sowa; West, Matthew R SITI-ITPSIE
> Cc: SUO; cg@cs.uah.edu
> Subject: RE: Re: An article on the pitfalls of metadata
>
> Tom Johnston wrote:
>
> <snip/>
>
> > My first question would
> > be: which one has
> > successfully incorporated the largest and most diverse set of
> > lowest level
> > (i.e. working database level) ontologies? Which ones can most
> > completely
> > rely on the data model itself to fully express the semantics
> > up and down the
> > entire ontology, without "patching things up" with ad hoc
> > program code.
> > (Sorry, I don't know how to translate this point, expressed
> > in my preferred
> > language, into the language of axiomatized formal systems.)
> >
> > Whichever one it is, that's the one we should go with. Let's
> > work to add
> > more lowest level ontologies to it. In the process, we may
> > sometimes make a
> > good case for revisions a couple of levels higher up. We may on rare
> > occasions make a good case for revisions much higher up. Some of those
> > revisions will not force structural changes elsewhere in the
> > web of this
> > ontology, e.g. adding a creation-date-timestamp to the top-level
> > entry/table/class. Other revisions will force structural
> > changes, and such
> > changes can be painfully expensive. But the further up we go, the less
> > frequent the revisions will be. Once again, this is just
> > Quine's sphere of
> > language, his (or Peirce's?) holism.
> >
> > Tom
> <snip/>
>
> Tom, why not use the process you described above as the initial
> statement of an algorithm to automate the merger of lower level
> data models?
>
> Observations about the actual databases stored with two data
> models might be analyzed to come up with a higher level model
> that incorporates both. Since the top level model is empty,
> when two data models merge to no common elements, the two are
> clearly independent nodes on the lattice. Some of the data
> mining techniques can be applied to this approach.
>
> I don't think its necessary, or even useful, to develop the
> lattice manually since it will be necessarily a dynamic lattice
> that changes with time. So its not the initial lattice that
> we should spend effort on, its the method (algorithm, process)
> for building the lattice and refining it through observations.
>
> JMHO,
> Rich
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