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Re: [ontolog-forum] Are classifications nothing more than Indexes?

To: ontolog-forum@xxxxxxxxxxxxxxxx
From: John F Sowa <sowa@xxxxxxxxxxx>
Date: Mon, 12 Aug 2013 09:38:45 -0400
Message-id: <5208E565.30406@xxxxxxxxxxx>
Frank, Simon, and William,    (01)

Frank's question raises some serious issues that cut through the
debate about theories, primitives, logics, and ontologies:    (02)

FG
> Are classifications nothing more than what Librarians call "Indexes"?
> ...
> In the process of analyzing and trying to provide solutions for each
> of these  common Library Constructs, and specifically in the context
> of analyzing Indexes,  we keep coming to the conclusions that
>
> 1. Indexes are nothing more than "classification" constructs, and
> 2. Indexes highlight how ineffective hierarchical representations of
>    Taxonomy  really are because "Electronic Indexes" can be and commonly
>    are recursive,  also "looping-back" on and leveraging each other.    (03)

Ranganathan was a librarian who invented a classification scheme
based on *facets*, which can be combined to form a partial ordering.
It could be extended to a complete lattice.  In Simon's quotation,    (04)

SS
> "The intellect cannot be tied down with a decimal thong"
> -- http://www.cafepress.com/ranganathong    (05)

WF
> Combinations of classifiers that are part of orthogonal classification
> schemes  need to be accommodated in a different manner (most effectively,
> in my  experience, through composition, but most commonly through "multiple
> inheritance"  (but me, I do not know what "inheritance" means, except in
> biology and in  class-oriented programming languages --
> ((though I used to  know, before I thought about it much)).    (06)

That last line is significant.  Nearly everybody who starts with
an elegant formal paradigm gets hit with cold, hard reality when
they try to make it work on a large scale.    (07)

Ludwig Wittgenstein and Terry Winograd are two people who started
with elegant formal systems:  Wittgenstein's _Tractatus_ in 1921,
and Winograd's SHRDLU system in 1971.  After facing reality, both
of them spent years preaching about and against the limitations of
their earlier systems and other similar systems.    (08)

Netflix is an example of a very large and profitable library system.
One reason why they are so profitable is that they developed a method
for analyzing and classifying their customers' preferences that quite
accurately predicts what videos they are likely to select.  For a
summary of the issues and their methods, see    (09)

    http://www.wired.com/underwire/2013/08/qq_netflix-algorithm/
    The Science Behind the Netflix Algorithms that Decide
    What You’ll Watch Next    (010)

That title is a misnomer, since the article says very little about
the science or the algorithms.  But it does give a fair amount of
insight into the issues involved:    (011)

Carlos Gomez-Uribe from Netflix:
> By looking at the metadata, you can find all kinds of similarities
> between shows. Were they created at roughly the same time? Do they tend
> to get the same ratings? You can also look at user behavior—browsing,
> playing, searching. Sometimes what’s similar depends on who you’re
> talking about. Take director Pedro Almodóvar. You might have four very
> different movies by Almodóvar. But he’s such a strong voice that, by
> himself, he makes those videos similar to one another. For a different
> director — say, Spielberg — that might not be the case.    (012)

This paragraph summarizes the kinds of issues that plague all elegant
classification schemes:  the number of different reasons why a viewer
or a reader may choose one item or another is open ended.  No simple
selection of features, facets, or primitives will work.  It reminds
me of a dreaded comment that some people inflict on other people:    (013)

    "Oh, you should meet so-and-so -- you have so much in common."    (014)

When I was studying mathematics at MIT, my mother sent me a letter
that mentioned a recommendation from one of her friends: "Your son
should go see my nephew, who is studying mathematics at Harvard."
That nephew was Ted Kaczynski, who became the Unabomber.    (015)

John    (016)

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