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Hi Len,
In fact, this research started when I discovered that the actual semantic
web technologies as recommended by W3C don't help me aggregate different
statement about a particular concept. Actually, the main source of web
document classification is Google. Let's consider that Google is offering a
point of view or a view of the world. Some others like Teoma are proposing a
different point of view. If we have only one source of classification then
no problems, we go back to the middle ages and get a single view of world.
However, if, more than one proposition is made about a concept and if these
sources a quite different, then, it would be useful to be able to merge them
in an intelligent way.
Just, for a moment, go to http://www.infospace.com/home/dog/index.htm or
http://www.mama.com both are aggregating different point of views. We simply
do not know how they come to the conclusion that a particular resource is
more closely related to a concept than another. Without considering the
social interaction or the why people link or interact in certain ways, how
do I reconciliate different propositions. If people start to publish marked
up information in the form of frames (ala RDF) and if people publish
information in the form a text, how can I conciliate different propositions
about a certain concept?
If I am using the topic map method, I will collect a collection of resources
about a particular topic. If I am using RDF I will aggregate propositions
about a topic. Whatever the method I am using (topic map or RDF) I have to
evaluate how related a resource (a proposition or a document) is to a
concept/topic/class. The result needs both a notation (for presentation) and
an algorithm (for computation). This is operational, non philosophical and
it does not depends on the linear or non linear nature of the web.
As roger pointed out, we have emergent + computed proposition. These
propositions are the result of people behavior, cognitive models and
algorithms used by search engines. On the other hand, we have propositions
based on formal and documented ontologies. For the latter, the problem is to
relate a particular statement to its ontology. For example if I include the
following statement in a web page and thus provide both text and data for
two agents: a) a human being or automatic classification engine, b) a data
collector.
<rdf: description about="aparticularresource">
<property>value</property>
......
</rdf:description>
The first problem is to get access to the ontology if there is one attached
to this statement. I may have mine but as I said earlier my definition of a
chemist may not be the same one as the author of this description.
Problem 1:
----------
How to get access to the ontology behind an RDF description? Where is it
located where in an RDF fragment? How do I get the link to fetch such
definition?
Problem 2:
----------
If the same document being categorized by one or several search engines
provides an RDF description about this document and if the document also
provides one, which algorithm can I use to resolve the conflicting
descriptions about the same resource? Is there one, none? Len if you think
role playing can help; frankly I don't have a clue how. Can you publish the
link pointing to this research so that at least I can analyze if their
solution find its home for this type of problem. Because for the moment, I
think I have a different ontology categorizing "role playing" than yours :-)
Does anyone have any pointers on paper containing either a solution of some
directions for a solution? Does the Semantic web Work group is working on
problem 1? If yes, what is the current proposal?
Cheers
Didier PH Martin
http://www.didier-martin.com
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