Semantic Browsing
An algorithm to surf
the meaning
Francesco Lentini
NKS 2007 Wolfram Science Conference
[by reading-path meaning]
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. |
