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