nature -> "human brain" -> "language terms" ==>> knowledge ?
Hello,
I follow the concept that the human brain reflects on "nature"
(as an objective reality). In its turn, the above reflection
gets "captured" into the language terminology in some "raw" form.
Below I propose the method of retrieving this "raw
knowledge", being captured in the language terminology, via
the means of the hierarchical classification of all terms
(nouns - see below), contained in the given human language
(say English Language as most scientifcally common).
The suggested approach is based on the verb <-> noun grouping
and is "stolen" by me from the Software Object Oriented
representation of the class (object). In this particular
adaption of the OO, the terms (nouns) are analogous to the
object's data and the verbs are analogous to the "methods"
(aka "member-functions") which could be applied to (performed on) the
data.
Suppose for each term (noun) avalable in the language, we
will "gather" the set of all verbs, which could be applied to
the given term (noun).
Each set is corresponding to the unique noun, as it was
described above - so the trees are built around nouns due to
their one-to-one unique relationship with the given specific
set of verbs.
Then we could compare each generated (per above description) set
against all other sets (separately on one-to-one basis) to find
whether some sets of verbs could share the "common" subsets.
Then we could attempt to detect whether some sets were
derived (inherited) from the other sets so we would be able
to build the hierarchical trees of such related sets.
Actually, the nodes of the trees should contain the nouns
(rather than corresponding sets of their verbs).
The top node of each such tree would contain the set (actually
uniquely corresponding to it noun as mentioned above), which would contain just the "common" subset of the verbs or the "minimum" number of verbs.
Such noun with the "minimum" set of verbs has the highest
level of the "abstraction" in the given tree.
To complicate the "picture" the two nodes, which belong to
two different trees, may "act" as "parents" nodes to generate
the "child" node (Multiple Inheritance), etc.
Further, some quantification of the "abstraction" value could be
applied to each distinct tree - the "most bottom" node should
have the "abstraction value" set to 0 (zero) and for each
next higher level the "abstraction value" should be
incremented by 1 (one).
The above excercise, which I am suggesting to conduct - is not intended to develop some aid in processing human texts, except may be for the
very small minor thing of being able to somewhat quantatively
characterize the average level of abstraction, used in the text (and
only if the text is recognized, using other cognitive means, as "scientific", covering certain domain(s) of the science). I
"claim", however, that the terminology, developed historically in the > human language, "subconciously" reflects (without much
of "distortion"/"noise") the objective fundamental reality of the
nature, so the language's terms are in fact "synonyms" of the
nature's attributes. So in that sense I believe my excercise could
contribute to studying of the nature itself and its universal
structure. I guess that the results obtained (as described above)
could be analyzed using methods developed in the Theory of Graphs.
Below is my view on classification of the knowledge :
Currently human race uses two major levels of expressing the knowledge:
1) Textual expression - historically it was developed/used first,
but it is rather "primitive": very context related, non-
quantative, potentially being subject of uncertainties of
interpretation(s), could be "false" in principle - hence the
problems being dealt with,
in the scientific application domain, (objectively speaking, this
not a fundamental but application domain). This textually
expressed knowledge is "acceptable" for the human
specific utilitarian domains. However, when the textual knowledge
addresses the fundamental areas/domains - it is (in my view)
should be considered to be "preliminary", subject of "upgrading"
into the mathematically expressed knowledge (see below).
2) Mathematically expressed knowledge (formulas) is: precise,
quantative,(typically) proven by (based upon quantative)
experimental data. This form of expressing the knowledge is used
for describing the fundamentals of the nature (which is not
necessary utilizable by humans and, by all means, often could not
be utilized by the humans immediately). Theoretically, this
mathematically expressed knowledge could "survive" beyond the
"era" of the human race existence (dialectically speaking,
everything starts, evolves and ends/gets "pre-empted").
Thanks,
Best Regards,
Alexander Povolotsky