I have a little over 6000 books. They are loosely arranged "by subject".
Google has a pile of scanned books (although I can't get access).
The "by subject" classification is a sorta-useful choice but it mixes my book
on invertebrate learning (octopus) with the "biology pile", or the "learning pile",
or other "piles". The question becomes "where does it fit"?
Currently most of my books (after 1970 or so) have an ISBN but that is related
to the publisher, not the subject. The Dewey system helps a little but not all
books seem to have a number. Many people gift me books they no longer want
so they don't come from libraries (great joy!)
I've been toying with the idea of "conceptual distance" but haven't found a way
to express or compute it. I've recently been thinking about asking an AI system
to generate a "classification in a landscape". Thinking about it, I recently pondered
the idea of using an AI to read the table of contents to find and arrange youtube
videos for each chapter. Thus a table of contents creates a "local landscape".
I came across a recent article
https://thelastwave.substack.com/p/associative-data-structures
This person queries Claude (Anthropic) about concept associations
and builds a network of concepts. As expected, there are "clusters" that show
up in such a network of concepts (which I call "clades").
So it seems that it would be possible to create a "position number" for a book
(or video, or idea, or ...) in a "landscape". So information sources have a
"conceptual distance" from many other related concepts. This is essentially
exposing the "concept map of the internet".
A useful side-effect of such a landscape is that it highlights "clades" (or "clusters").
Such a landscape is a guide to select future "interdisciplinary research".
How to "number" such a concept graph so it could be used to "compute distance"
is still beyond me. My book on graph theory calls me :-)
Google has that pile of scanned books. It would be possible to have an AI look
at all of the table of contents and create a "concept landscape". This would be
a "first cut" at knowledge organization. It can't be too hard to train an AI on the
scanned book data. The AI could probably invent a "distance metric".
Tim (axiomcas@gmail.com)
