A Precise Definition of Knowledge – Knowledge Representation as a Means to Define the Meaning of Meaning Precisely
A Precise Definition of Knowledge
Knowledge 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, ordinality, cardinality,…
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
Heurist.me (Carey G. Butler) 
Question:
“When we start talking about exchange of that knowledge (e.g. via the resonance) does the term ‘precisely’ hold?”
Answer:
Precision is not necessarily a part of any exchange of knowledge. Even partially shared dynamics and morphology resonates in unison to some degree.
It is an attribute of my definition, because the definition is precise.
We must not forget how knowledge, wisdom, insight and understanding (even experience) relate to each other.
Knowledge and understanding form a complete contrapositive harmonic field that is fundamental. There are deeper levels of meaning for both, but that is a different discussion.
Knowledge takes on agency and understanding takes on communion in their shared morphological and dynamical domain.
Wisdom and insight build another completely different one just as fundamental (Insight takes on agency and wisdom takes on communion).
Sep 4, 2014 at 12:51 am
Question:
Now about “knowledge can be precisely defined’:”
“In your decription (the list and their precisions) the term ‘knowledge’ is precisely defined. It is your definition.”
“If this affirmation includes also knowledge itself I’m struggling with the term ‘precisely’.”
“In my perception ‘awareness’ and ‘meaning’ (and thus meaning of meaning = knowledge) include a personal aspect (human or software) because is uses prior knowledge. (BTW there is the question of how to start from a blank sheet here). If this is so then the term “precisely” might refer to individual internal knowledge.”
Answer:
Meaning builds, in all of its multitude of forms, unique and specific signatures of structure and resonance just like atoms and molecules do. Nothing ‘personal’ was a part of their morphology and resonance either.
These signatures precede our own consciousness, but not consciousness itself. We have simply not seen before what has always been there from the beginning. It has very much to do with how we were looking, but that’s an answer to a different question.
I think the problem lies with understanding what understanding is. (Correct me if I’m wrong in this regard.)
Understanding is the integration of knowledge into oneself.
We are literally ‘eating’ or inserting the dynamics and morphology into our own consciousness!
The degree to which we share those dynamics and morphology is the extent to which we ‘understand’ each other.
Insight and wisdom are completely different concepts too. I’ll explain them below in my answer to your last question.
Sep 4, 2014 at 12:50 am
Question:
“What is knowledge then (and the list)”
“Observation: The 3 bold items seem to be the key statements of your definition of knowledge. The other elements are precisions on the bold topic above. But presenting it like this doesn’t show that clearly.”
“‘These requisites of awareness’ shouldn’t I read here ‘These requisites of knowledge’ or ‘This awareness’?”
Answer:
The requisites of awareness are the prerequisites for knowledge.
Sep 4, 2014 at 12:49 am
Question:
“The last phrase is a very good one ‘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!’ and would have a better position earlier in the text.”
“The same holds for the part of the next paragraph (Real knowledge …. increasing precision!).”
“You can look at an ontology, or what is commonly labeled ‘knowledge graph’, ‘semantic network’ etc as just another stream of data. Handled in you chain of processes like any other stream of data (acquisition, collation, …).’
“If you look at the definition of ontology the key phrase is “consensual description of a domain”. Nothing more.”
Answer:
That is a qualified and contrived definition. Why must we accept it? It belongs to a paradigm that has shown to be only capable of synthetic intelligence (AI).
I know I’m alone right now in my knowledge, but it won’t stay that way. People who are silently understanding me without the courage to speak out in solidarity with me are reading this right now.
There will come a time when even the subscribers to the incomplete paradigm of Artificial Intelligence will say ‘We’ve always known we had an incomplete metaphysics to back us up.’
This isn’t about intelligence for those who finance the industry of AI anyway, they have even bigger fish to fry… our sovereignty and freedom.
Until that day, I will stand as the only voice for reason… at least until others are honest with themselves and join me.
Sep 4, 2014 at 12:48 am
Question:
“You know I don’t like ontologies, so this is not a defense of them.”
“Observation: These two paragraphs feel like an aggression to ontologies, or at least an aspect of them, that you do not mention. I think you should, else the reader must have that knowledge in order to understand what you are refuting.”
“E.g. ‘incapable of generating the purpose of even its own inception’. Is that something what is said to be necessary? For an ontology, for knowledge?”
Answer:
An ontology is like a set. An ontology requires a purpose for it to make sense. An ontology without a purpose is like a set without an equation to define it. Membership within a set without a purpose is useless. The crucial question is who’s determining their membership?
The conventional use and understanding shows clearly how ontologies are useful, but their purpose is implicitly defined by us or an algorithm (us again).
The reality is that an ontology is ‘homeless’ without an epistemology to share its ‘domain’ with. It becomes more than a named set. It is knowledge.
Sep 4, 2014 at 12:46 am
Question:
(Quoting me) Things, concepts and other things exist without me knowing them (or have forgotten). Including their properties, connections.
“I fully agree with that.”
“If I take your reference to perspective from the chat”
(quoting me) (Perspective: how we look at knowledge depends to a very large extent upon how we see), then perspective doesn’t exist for the things I’m not aware of. Right? I might have forgotten things and their perspective(s), though.”
“What is written in this paragraph gives the global idea of what you want to tell, I think, but the phrasing brings up apparent inconsistencies at least for me.”
Answer:
Knowledge to you is your perspective.
Perspectivity is a precursor of awareness.
Self and other is fundamental and manifests itself even at the quantum level. This is not my opinion, rather a result from experimentation and research.
Sep 4, 2014 at 12:43 am
Question:
“In the first case (semantics)”
(Quoting me) 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.
“I see sort of chicken-egg situation here. If things have no clear meaning, how can the meaning of meaning (knowledge) exist and have structure and dynamics?”
Answer:
If it were a chicken and egg situation, I would say that both arose together, but it isn’t about that artificially created conundrum for me.
Structure, resonance and dynamics are inherent and unique in all that knowledge is.
Sep 4, 2014 at 12:42 am
Question:
“Give me your definition of truth value please.”
“Knowledge is true or false, justified or not: OK with that. But I cannot see why this is so because of your definition of knowledge (meaning of meaning) as indicated by the word because. Couldn’t this be independent?”
Answer:
Truth value is a type of dynamics which is shared between entities. If the entities participate in any shared domain, then truth for them is found in the dynamics they share. Truth (intrinsically) is a field. Truth shares a contrapositional relationship to fiction which together build a complete harmonic structure capable of discerning truth value within a KR (knowledge representation). I also call them ‘groks’ (in honor of Robert Heinlein).
Sep 4, 2014 at 12:40 am
Question:
if the knowledge’s structure is solely coming from what is provided, I cannot see how detection of missing knowledge is triggered.”
“unless it is combined with other existing knowledge”
Answer:
As the information accumulates patterns emerge. The patterns show inconsistency. Let’s take indeterminacy as an example. I will then move to an omission and obfuscation/lying from there.
Every kind of indeterminacy shares one or more harmonics with all others. It’s signature is unmistakable no matter where it occurs. This is true of any data. The same harmonic signatures can be known. It’s almost exactly like a chemical molecule (even compounds).
The holarchy of the signatures are arranged in increasing orders and express themselves as this same signature at a different ‘octaves’ sort of like how water running down the drain in your sink resembles a hurricane.
Omissions leave gaps in those spectral signatures.
Obfuscation and hiding produces partially distorted spectral signatures.
Lying produces partially inverted spectral signatures.
Sep 4, 2014 at 12:38 am
Question:
“Reliability + consistency is now OK. Your phrasing made my link these terms to the conceptualization of our world, not to the process.”
Answer:
Knowledge’s structure is never supposed, rather comes completely from the data and in the data’s own terms. There is no need to create ontologies for the data, because the data provides them itself.
It may help if we chose an example.
Sep 4, 2014 at 12:35 am
Question:
“hidden + missing K: I can imagine that if the structure K is supposed to have is known, then hidden and missing K become obvious. But what if the structure is unknown? (or in reality more complex – fractals e.g. when thinking about granularity here)”
Answer:
Knowledge that is hidden will show to have gaps in its structure that are partially covered [concealed]. Knowledge that is missing reveals itself by gaps that are not concealed. If the KR is done correctly, nothing can be hidden without being noticed at some level. The same is true about missing knowledge.
Perspective: how we look at knowledge depends to a very large extent upon how we see.
‘Knowledge’ without an FOV [Field of View] is a precursor to knowledge for those who lack one.
Sep 4, 2014 at 12:34 am
Question:
“I got that. But still have a hard time to imagine something behind the term structure.”
Answer:
Is my distinction between what an intrinsic and extrinsic property are clear? what they are. It depends upon that knowledge.
Meta-fields occupy higher levels of the holarchy. Hyper-fields occupy the intra- inter- and extra-spectral domains.
Reliability means that you arrive at a harmony between what the data is giving you is being represented.
Consistently means that no matter how the data is being parsed, you get the same results. Even if indeterminacy is part of the data.
Essentially infinity (or several of them) and any kind of ambiguity (even logical) are treated in a consistent way.
Sep 4, 2014 at 12:32 am
Question:
“structure: I don’t know what to think here. Can you give an example?”
“vocabulary: Seem to indicate that it’s all about text.
Right? because the information it creates from the data”
“information = data + structure”
“They could represent an individual symbol, punctuation, morpheme,lexeme, word, emotion, perspective, or some other unit of information in the data.”
Answer:
Collecting, organizing, summarizing.
Think of these concepts as ‘enzymes’.
It’s a given that the data stream exhibits some coherence. Data is only collected from a stream that’s coherent in terms of itself. If a structure comes along that the ‘enzymes’ recognize, it will be summarized.
The video shows a holarchical acquisition of the data. Patterns are differentiated by their spectra. There are many harmonic fields working concurrently. Ultimately, the output of one level provides the input for a higher level unless they have reached their highest level.
Sep 4, 2014 at 12:29 am
I’ve published the video about 18 hours ago. Please go to https://www.youtube.com/watch?v=IUEwSmDzpMs to see it.
I’m posting important questions and my answers to them below.
It can also be found on Vimeo in HD:
Sep 4, 2014 at 12:26 am