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Re: [ontolog-forum] What is"understanding"

To: "[ontolog-forum]" <ontolog-forum@xxxxxxxxxxxxxxxx>
From: "John F. Sowa" <sowa@xxxxxxxxxxx>
Date: Thu, 03 Apr 2008 17:12:26 -0400
Message-id: <47F5483A.4030006@xxxxxxxxxxx>
Len,    (01)

I strongly disagree with the following point:    (02)

LY> Can you at least (and at last) agree that learning from text
 > or any other form of NL is not a most promising approach to
 > knowledge acquisition.    (03)

I don't believe that the Semantic Web and related efforts can
succeed without much more automated or at least semi-automated
knowledge acquisition.    (04)

I agree with Sergei on the following point:    (05)

SN> While we don't want human annotation/analyses we think
 > that there may be a good way of using people to validate the
 > results of learning, so as to improve its quality faster
 > (and therefore cheaper).    (06)

It's possible to extract an enormous amount of information
from natural language by automated means, but I agree with
Sergei (and many others) that human assistance is important
for validation.    (07)

For an example of a legacy re-engineering project that
combined information from analysis of computer programs
(1.5 million lines of COBOL plus scripts written in IBM's
Job Control Language) with 100 megabytes of English
documentation (reports, manuals, emails, etc.), see    (08)

    Analogical Reasoning    (09)

One of the top consulting firms estimated that the analysis
stage (not the new programming effort) would require 40
people for 2 years -- 80 person-years.    (010)

But two people, Arun Majumdar and Andre LeClerc, did the
analysis in 8 weeks, using computer analysis of English
plus legacy software (with human assistance when the
computer requested it).  That's 16 person-weeks, for a
productivity increase of 260 times or 25,900 percent.    (011)

That is a success story that led us to start up the
VivoMind company.  Since then, we've had other results
that show that human-computer collaboration is far, far
superior -- in both quality *and* quantity -- to humans
doing the analysis and knowledge representation without
computer assistance.    (012)

John    (013)

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