Semantic Browsing
An algorithm to surf
the meaning
Francesco Lentini
NKS 2007 Wolfram Science Conference
[by reading path
algorithm]
Every document and intelligent message
contains a “secret map”. An equally
intelligent algorithm can be used to
decode this map and use it to tag, mark-up,
summarise and generate hypertext links.
This is called reading and interpreting text
with a click, but we call it "semantic
browsing".
Let us suppose that it is necessary to
analyse a binary code signal originating
from a remote region of cosmic space. All
that we can see is a string of bits:
010100110110010101101101011000010110111001
110100011010010110001100100000010000100111
001001101111011101110111001101101001011011
1001100111
To be certain that this is not merely a
random series of symbols we require a
meaning detector, such as data-mining
techniques. Unfortunately, data-mining
operate by applying the syntax rules of
known languages. However, at
message-internal level, we do not even know
whether any such rules exist, therefore we
need a new kind of algorithm:
The Semantic Browsing (SB) algorithm
attempt to overcome the semantic barrier at
message-internal level. One way to
understand the concept is to examine several
messages where the meaning is already known.
For instance, SB examines this document
itself, trying to answers to a very complex
question: What is (are) the most important
information(s) contained in this document?
And the result is 1 to 3 possible reading-paths (in order of rilevance):
- message-internal
- algorithm
- meaning
Finally, SB examines a text consisting
entirely of random phrases. And the answer
is: NONE.
Even if we have a well working machine to
read, this is an exciting work in progress.
Target of the research is to reach an
acceptable solution to one of the “really
big questions” posed by the doyen of
American physicists, John Wheeler: What
makes meaning? Through the SB algorithm
we are in search of the lost meaning, veiled
in the documents of every author and every
epoch. |
