A Precise Definition of KnowledgeKnowledge Representation as a Means to Define the Meaning of Meaning Precisely
Copyright © Carey G. Butler
August 24, 2014
What is this video about?In
this introductory video I would like to explain what knowledge
representation is, how to build and apply them. There are basically
three phases involved in the process of building a knowledge
representation. Acquisition of data (which includes staging), collation
and the representation itself. The collation and the representation
phases of the process are mentioned here, but I will explain them
further in future videos.
You are now watching a simulation of
the acquisition phase as it collects and stores preliminary structure
from the data it encounters in terms of the vocabulary contained within
that data. Acquisition is a necessary prerequisite for the collation
phase following it, because the information it creates from the data are
used by the collation algorithms which then transform that information
into knowledge.
The statistics you are seeing tabulated are only a
small subset of those collected in a typical acquisition phase. Each of
these counters are being updated in correspondence to the recognition
coming from underlying parsers running in the background. Depending upon
the computer resources involved in the
acquisition, these parsers may even even run concurrently as is shown in this simulation.
The objects you see moving around in the video are of two different kinds:
knowledge fields or
knowledge molecules. Those nearest to you are the field representations of the actual data being collected called
knowledge fields. They
could represent an individual symbol, punctuation, morpheme, lexeme,
word, emotion, perspective, or some other unit of information in the
data. Each of them contain their own signature – even if their
value, state or other intrinsic properties are unknown or indeterminate
during the acquisition.
Those farther away from the view are
clusters of fields which have already coalesced into groups according to
shared dynamically adaptive factors such as similarity, relation,
cardinality, ordinality,... These 'molecules' also contain their own set
of signatures and may be composed of a mixture of
fields, meta-fields and hyper-fields that are unique to all others.The collation phase has the job of assigning these molecules to their preliminary
holarchical domains
which are then made visible in the resulting knowledge representation.
Uniqueness is preserved even if they contain common elements with others
in the domain they occupy.
Clusters of knowledge molecules and/or
fields grouped together are known as 'knowledge domains', 'structural
domains','dynamical domains' or 'resonance domains', depending upon
which of their aspects is being emphasized.We now need a short introduction to what knowledge representation is in order to explain why you're seeing these objects here.What is Knowledge Representation?Knowledge representation provides all of the ways and means necessary to reliably and consistently conceptualize our world.
It helps us navigate landscapes of meaning without losing our way;
however, navigational bearing isn't the only advantage. Knowledge
representation aids our recognition of what changes when we change our
world or something about ourselves. It does so, because even our own
perspective is included in the representation. It can even reveal to us
when elements are missing or hidden from our view!
It's important to remember that
knowledge representation is not an end, rather a means or process
that makes explicit to us everything we already do with what we come to
be aware of. A knowledge representation must be capable of representing
knowledge such that it, like a book or other artifact, brings awareness
of that knowledge to us. When we do it right, it actually perpetuates
our understanding by providing a means for us to recognize, interpret
(understand) and utilize the how and what we know as it relates to
itself and to us. In fact –
knowledge representation even makes it possible to define knowledge precisely!What Knowledge is not!Knowledge
is not very well understood so I'll briefly point out some of the
reasons why we've been unable to precisely define what knowledge is
thus far. Humanity has made numerous attempts at defining knowledge.
Plato taught that justified truth and belief are required for something
to be considered knowledge. Throughout the history of the theory of
knowledge (epistemology), others have done their best to add to Plato's
work or create new or more comprehensive definitions in their attempts
to 'contain' the meaning of meaning (knowledge). All of these efforts
have failed for one reason or another.
Using truth value and
justification as a basis for knowledge or introducing broader
definitions or finer classifications can only fail. I will now provide a small set of examples of why this
is so.
Truth value is only a value that knowledge may attend. Knowledge can be true or false, justified or unjustified, because
knowledge is the meaning of meaning.
What about false or fictitious knowledge? Their perfectly valid
structure and dynamics are ignored by classifying them as something else
than what they are. Differences in culture or language make even make
no difference, because the objects being referred to have meaning that
transcends language barriers.
Another problem is that knowledge
is often thought to be primarily semantics or even ontology based! Both
of these cannot be true for many reasons. In the first case (semantics):
There already exists knowledge structure and dynamics for objects we cannot or will not yet know.
The same is true for objects to which meaning has not yet been
assigned,such as ideas, connections and perspectives that we're not yet
aware of or have forgotten. Their meaning is never clear until we've
become aware of or remember them.
In the second case (ontology):
collations that are fed ontological framing are necessarily bound to
memory, initial conditions of some kind and/or association in terms of
space, time, order, context, relation,... We build whole catalogs,
dictionaries and theories about them! Triads, diads, quints, ontology
charts, neural networks, semiotics and even the current research in
linguistics are examples.
Even if an ontology or set of them attempts to represent intrinsic meaning, it can only do so in a descriptive (extrinsic) way.An
ontology, no matter how sophisticated, is incapable of generating the
purpose of even its own inception, not to mention the purpose of objects
to which it corresponds!The knowledge is not coming
from the data itself, it's always coming from the observer of the data –
even if that observer is an algorithm!Therefore
ontology-based semantic analysis can only produce the artifacts of
knowledge, such as search results, association to other objects,
'knowledge graphs' like Cayley,.. Real knowledge precedes, transcends
and includes our conceptions, cognitive processes, perception,
communication, reasoning and is more than simply related to our capacity
of acknowledgment.
In fact knowledge cannot even be completely systematized, it can only be interacted with using ever increasing precision!What is knowledge then?• Knowledge is what awareness does.•
Awareness of some kind and at some level is the only prerequisite for
knowledge and is the substrate upon which knowledge is generated.
• Awareness coalesces, interacts with and perpetuates itself in all of its form and function.
•
Awareness which resonates (shares dynamics) at, near, or in some kind
of harmony (even disharmony) with another tends to associate
(disassociate) with that other in some way.
• These requisites of awareness hold true even for objects that are infinite or indeterminate.
• This is why knowledge, the meaning of meaning, can be precisely defined and even provides its own means for doing so.
•
Knowledge is, pure and simply: the resonance, structure and dynamics of
awareness as it creates and discovers for and of itself.•
Awareness precedes meaning and provides the only fundamentally necessary
and sufficient basis for meaning of meaning expressing itself as
knowledge.
• Knowledge is the dialog between participants in awareness – even if that dialog appears to be only one-way, incoherent or incomplete.
•
Even language, mathematics, philosophy, symbolism, analogy, metaphor
and sign systems can all be resolved to this common denominator found at
the foundation of each and every one of them.
More information about the objects seen:The
objects on the surface of the pyramid correspond to basic structures
denoting some of the basic paradigms that are being used to mine data
into information and then collate that information into knowledge. You
may notice that their basic structures do not change, only their content
does.
These paradigms are comprised of contra-positional fields that harmonize with each other so closely that they build complete harmonic structures. Their function is similar to what proteins and enzymes do in our cells.
#Knowledge #Wisdom #Understanding #Learning #Insight #Semantics #Ontology #Epistemology #Philosophy #PhilosophyOfLanguage #PhilosophyOfMind #Cognition #OrganicIntelligence #ArtificialIntelligence #OI #AI #Awareness https://www.academia.edu/8066040/A_Precise_Definition_of_Knowledge_-_Knowledge_Representation_as_a_Means_to_Define_the_Meaning_of_Meaning_Precisely
