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Re: [ontolog-forum] Axiomatic ontology

To: "[ontolog-forum] " <ontolog-forum@xxxxxxxxxxxxxxxx>
From: "Sharma, Ravi" <Ravi.Sharma@xxxxxxxxxxx>
Date: Fri, 1 Feb 2008 22:45:57 -0700
Message-id: <D09FFCFB3952074082D4280BC24EAFA8B14A92@xxxxxxxxxxxxxxxxxxxxxxxxxx>
John
1. Are these semantic distances similar to Mahalanobis distances of
Multivariate statistics?
2. I debated in 1960's with a Yale Philosophy Professor (I believe
Norwood Hanson) who was also a pilot as well and unfortunately he died
in a plane accident. We talked about "picture theory of theory meaning"
and one of the threads in our conversation was that understanding is
often through visualization rather through language.
3. I have often wondered as to how - for few limited phenomena that I
can explain in multiple languages - limited and varied as the
translation is - it draws from conceptual rather than textual
understanding of the phenomena or subjects under consideration. Is this
not cognitive reasoning or concept(understanding)?    (01)

Thanks.    (02)

Ravi    (03)

(Dr. Ravi Sharma) Senior Enterprise Architect    (04)

Vangent, Inc. Technology Excellence Center (TEC)    (05)

8618 Westwood Center Drive, Suite 310, Vienna VA 22182
(o) 703-827-0638, (c) 313-204-1740 www.vangent.com    (06)



-----Original Message-----
From: ontolog-forum-bounces@xxxxxxxxxxxxxxxx
[mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx] On Behalf Of John F.
Sowa
Sent: Friday, February 01, 2008 11:05 PM
To: [ontolog-forum]
Subject: Re: [ontolog-forum] Axiomatic ontology    (07)

Pat,    (08)

Re reliable sources:  If an issue is important, I would never accept
any answer from anybody without getting a second or third or fourth
opinion.  But many of those sources are also available on the WWW:    (09)

PC> ... like dictionaries, encyclopedias, glossaries, thesauri, and
 > other ontologies, and occasionally textbooks.    (010)

I also download many classic books and quite a few articles on my
own computer so that I have my preferred selection, which I can
search with Google Desktop.    (011)

PC> Show me a text that requires a little thought to understand,
 > and then look at an automatic translation. Yechh! "Understanding"
 > it is **not**.    (012)

SYSTRAN was used to translate many pages of physics articles from
Russian to English during the 1960s (after Bar Hillel had said that
MT would never be practical).  But the physicists actually liked
it -- and they often *preferred* MT to a human translation.    (013)

They reasons they gave were interesting:  They could get a machine
translation within a day, but a human translation would take a week
or more.  Very often, they would look at the article and realize
that it wasn't what they wanted.  If they had asked a human to spend
time working on the translation, they would feel guilty about throwing
it away.  But they had no guilt feelings about the machine translation.    (014)

As for quality, it wasn't a problem because the most important info
was in the equations, and all the readers needed was enough background
to explain how the equations were being used.  Sometimes, the computer
made mistakes, such as generating the translation "nuclear waterfall"
instead of "nuclear cascade".  But they knew perfectly well what was
meant, and they even joked about nuclear waterfalls.  Furthermore,
the computer was always consistent in its choice of words so that
they knew that the same English words always went with the same
Russian words.  And some of them knew enough Russian so that they
could check the translations -- they used the system as a convenient
dictionary.    (015)

Re quality:  When SYSTRAN was converted from the original IBM 7094
to System/360, the output was switched from upper case to mixed case.
Even though the output was identical to what had been generated by
the 7094, the users thought that the quality had improved.    (016)

PC> Do you know of any programs publicly available that actually can
 > do the kind of spatial reasoning that people can do?  Do you think
 > that virtual reality and other simulations actually reason spatially
 > in some way similar to the way people do?    (017)

Both computers and humans can transform images by rotations, reversals,
combinations, etc.  But there are still many unsolved questions about
how the human brain does anything.    (018)

In any case, the algorithms we use for computing semantic distance
measures on graphs (conceptual graphs, by the way, but that really
isn't much of a restriction, since CGs can represent any graph) can
be adapted to compute semantic distance measures on geometrical
representations.    (019)

Whether those operations are similar to what goes on inside the brain
is unlikely, but the crucial test is whether the measures that the
computer would determine as close or distant have a high correlation
with what people would consider close or distant.    (020)

If you can hold your nose to look at Google, you can type "spatial
reasoning" to get 329,000 things to look at -- or not, as you prefer.    (021)

Joh    (022)


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