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Re: [ontolog-forum] blogic iswc keynote

To: "'[ontolog-forum] '" <ontolog-forum@xxxxxxxxxxxxxxxx>
From: "Rich Cooper" <rich@xxxxxxxxxxxxxxxxxxxxxx>
Date: Fri, 25 Dec 2009 15:19:39 -0800
Message-id: <20091225231947.282FE138D54@xxxxxxxxxxxxxxxxx>



Yes, the concept mining task behind database mining requires that the miner develop theories of how the data is organized.  


But there has to be an allowance for theories which, while useful for many cases, are not always unambiguously true or false for every case.  If a theory assigns True to a signature row r, it may not always get that assignment right as compared to the reality being approximated by the theory.  So the theory can assign True to a false case, False to a true case, T-t and F-f or, gasp, inconsistencies such as T-f and F-t.  


So actually, there are four combinations of TrueS and FalseS for any given row r:

True                  (r in TrueS)        and (r not in FalseS);

False                (r not in TrueS)  and (r in Falses);

Unknown           (r not in TrueS)  and (r not in FalseS);

and       Inconsistent      (r in TrueS)        and (r in FalseS).  


The Inconsistent version is sometimes abbreviated as STP (a polite interpretation isn’t available).  In a nutshell, it suggests that the theory may need further refinement.  But that might be a very useful theory because it sheds statistical light on just how much coverage the theory provides given a fixed set of cases, each with a row r to be classified.  


And of course, there can be tables of many current theories in the database, some theories of which are true, some of which aren’t, and some of which are not fully defined yet.  Therefore the theory-based approach to database classification tasks can be viewed as a recursive process of cut and fit.  


But the point is that, if someone neglects the complexity of negation, thereby avoiding the duality and even inconsistencies of real world theories, she can get too comfortable settling into a complete world of theory without meaning.  Too much internet. 


Empirical knowledge is an essential addition to theoretical knowledge, and constitutes those terminal concepts which can be personally experienced – the meaning.  Those are the concepts that our tiny tot uses when she processes language at age two.  She builds still more meaning as she grows, developing representations on top of (and in addition to) the earlier concepts. 


You may be right that there is no set of universal primitives, even though Anna Wierzbicka seems to think even “very general” primitives can be adequate for elaboration, or specialization, or generalization, into deeper meanings.  But there are definitely effects of early learning which are felt throughout our lifetimes.  So the primitives are there, even though they may also be augmented with entirely new experiences (and thus new primitives) from time to time as we age.  At least until we start losing concepts faster than we gain them!






Rich Cooper


Rich AT EnglishLogicKernel DOT com

From: ontolog-forum-bounces@xxxxxxxxxxxxxxxx [mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx] On Behalf Of sowa@xxxxxxxxxxx
Sent: Friday, December 25, 2009 10:54 AM
To: [ontolog-forum]
Subject: Re: [ontolog-forum] blogic iswc keynote



I agree.

> "without negations" literally means without KNOWING EXPLICIT negations.
> Most DBs that get exception cases store them in a table like the one that
> caused the exception. So, in effect, there are tables of TrueS and Tables
> of FalseS - or "fluents" as some logicians like to call them. Therefore,
> negation is in fact modeled where appropriate in current DB practices.

Your note illustrates the point that a relational database
can be used to support various kinds of semantics.

The default way of using SQL is negation as failure:  each
table contains the n-tuples for which a relation is true.
Any n-tuple not listed is assumed to be false.  That is the
so-called closed-world assumption.  If the conditions of
that assumption hold, then negation as failure is the
equivalent of true negation.

But it's possible to use two tables per relation:  one would
contain all the n-tuples for which the relation is known to
to be true, the  other would contain all n-tuples for which
the relation is known to be false, and the truth value of any
n-tuple not in either table would have the truth value unknown.

With an appropriate front end, the RDB would support a three
valued logic:  known true, known false, and unknown.


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