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Extreme Markup Languages Web Page


Extreme Markup Languages 2007



Extreme2007.jpg

This section of this page contains all the files of interest pertaining to the Extreme Markup Languages 2007 presentation by
    David Dodds:  

OntoClock, The Difference Between Having Ontological Knowledge and Knowing It



    (There are also two 2007 poster papers material available through this page as well.)



On this page are links to mp3 podcasts of my EML presentations (papers and posters) , support material / files for same, and useful data files relevant to my EML activities. There is a zip file    extrememl2007dodds.zip    on this page, which needs to be downloaded in its entirety, in order to follow along the narrative podcast for my EML2007 presentation. An SVG viewer, such as Firefox, is useful. Internet Exploder does an unnaccceptable job at this.
There is a PDF    EML2007DODD0411.pdf  , in the zipped group which is my paper sent for the EML2007 call for papers LBN.




The ontologies have the knowledge indicated below (amongst many other things):

all geometrical objects have a size.
a graph-bar has color and is a (kind of) plane.
and can be inferred
    to have a size since it is a geometrical object and
    to have an area since it is a plane which is a 2 dimensional object.

a bit more inferencing provides area to be the value of size for 2D objects and
volume to be the value of size for 3D objects and
length [to be the value of size] for 1D objects.

((note that a 1D object might be a highly-inflected (fractal [or fractional dimension]) curve))
(example Koch curve  or Sierpinski curve)
[and one way of calculating the length of such a line (curve) is the box dimension with sides of length r]

circle has scalar radius
radius is a 1D geometrical object
and can be inferred : the radius of a circle has a length, a numerically specified linear extent

 To you (the reader) this circle stuff is mind-numbingly obvious, it is what you use everyday as common knowledge, it is in fact part of your cognitive finessing knowledge. To a machine where no one is home this circle stuff is news and provides a means to implement a model of human's cognitive finessing. (which includes the capability of inferring equalities-identities and similarities.)





2007 Conference PAPERS and  Support Material

Download the zipped support materials file, press the button.

Download Part One of PAPER PODCAST,     press the button. sbut1.jpglisten to the PAPER PODCAST

Download Part Two of PAPER PODCAST,     press the button. sbut3.jpglisten to the PAPER PODCAST

Download Part Three of PAPER PODCAST,  press the button. sbut8a2.JPGlisten to the PAPER PODCAST

Download Poster Paper One, press the button. view the PDF file

Download Poster Paper Two, press the button. view the PDF file








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Extreme Markup Languages 2002 - 2006




2002 - 2006 Conference PAPERS and  Support Material


Read / listen to my 2006 Extreme ML material,                press the button. place6

Read / listen to my 2005 Extreme ML material,                press the button. place5

Read / listen to my 2004 Extreme ML material,                press the button. place4

Read / listen to my 2002 Knowledge Technology  material, press the button. place2




Usuality?! What the heck is Usuality?

"He's dead, Jim."*

Is this usuality? well, uh, not exactly. Let's look at what Lotfi Zadeh meant by his term, usuality.

First of all, it is NOT the same as probability.

Read the extensive usuality feature, press the button. view the usuality file




(* International viewers of this web page may not have been watchers of the 1960's TV program, Star Trek, from which this phrase was taken. Trekkie fans around the world will recognize this oft said, and punned, statement. If you don't see the relevancy or humour in this reference please just bear with us anyway. (For the record, nobody thinks dead people are funny.)



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