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Dletta / conceptGraph

Conceptual Graphs inspired by J F Sowa
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Join the chat at https://gitter.im/conceptGraph/Lobby

Conceptual Graphs inspired by John F Sowa.

Create Concept Graphs and Schemas, that can call functions and access databases to create answer graphs.

Best enjoyed with some white papers along side.

Theory straight from John F. Sowa's Paper titled Conceptual Graphs for a Data Base Interface July 1976 All credit for the Theory of Conceptual Graphs goes to Sowa amongst many other great minds before him, who believe in a better, more human-like computer interaction. We truly stand on the shoulders of giants.

Query Algorithm

Answer Graph Criterias to check for:

  1. w is a well formed CG
  2. w is true if the data base is correct
  3. The entire query graph q is covered by a join from w
  4. For every concept in q that has a value, the corresponding concept in w has the same value.
  5. For every concept in q that had a question mark, the corresponding concept in w has a value.

Algorithm A <Conceptual Graphs, pg.349>

Algorithm B <Conceptual Graphs, pg.349>

Algorithm C

  w: = q;
  while ( there is a preferred join j with w)  // seems to imply we have a list of joins
    do begin
      w: = result of performing j with w; //need function to do a join, also a score function
      while (there is a source conept a in w &&
            a does not have a value &&
            a does not have a question mark &&
            the target of a has a question mark)
        do place a question mark on a; //propagation
      while (there is a target concept b in w &&
             b has a question mark &&
             all sources of b have values)
        do get a value for b from it's access procedure (function); // reasoning
     if (there are no question marks left in w and all of q has been covered
         by some join)
         then begin:
          print answer; // result
          stop
          end
    end.

So as preparation of running a query through algorithm c we need to find possible joins and rank them per explanation in paper.

Given a set of possible joins s1 ... sn, score each graph by

Also need to consider a function that can return true if something is a subsort of a specific concept type.

Also indices for each type of concept or target or source links, if performance issues occur for searching the schematic universe.

prompting points (might not need this) are whenever it cannot find a join but a question mark remains on a quant('A')

The join function:

reference to concepts in common loop through join, giving you the concepts you want matching find concept person in graph2 find concept2 of join in graph1 and graph2 and merge them together

To-Dos

CHAT JF: Terms & Contexts JD: good idea, keep chat separate Next Steps The construction of a document should be in javascript first

Contexts

Contextual Logic References:

Implementations:

Algorithms:


(COI?) { 
  for (Rules) {
    if ∃x is ∈ of COI such that x ∈
  }
}

Power Context Family

Situation / Propositions

Situations & Propositions are types of contexts.

Obligation vs. Permission vs. Prohibition

Forming the bases of contracts

Bayesian / Probabilistic Context?

Language Generation & Mapping

Utterance Paths

The sequence of nodes and arcs that are traversed in mapping a graph to a sentence is called the utterance path.

Marked Forms

For emphasis,however,most languages permit optional inversions,such as the following English sentence in OSV form:

"His new-found friend he took with him to the park."

Such forms, which break the normal pattern of the language, are marked forms as opposed to the normal, unemphatic, unmarked forms.

Marked Forms as HTML

It is possible to now describe relations accurately

Lexical Vector Representations from Concepts

Descriptions:

Representations:

  1. Formalization of the basic unit of knowledge: the concept.
  2. Information extraction from a linguistic re-source into a set of concepts.
  3. Lexical association: term ↔ concept.
  4. Definition of a term as a composition (mix- ture) of concepts, allowing partial or com-plete disambiguation.

A term is said ambiguous if it is composed by more than one concept.

Lexicons

According to Sowa, there are three variations of factors for lexicons:

Which can be expressed in canonical graphs.

Sowa describes:

Knowledge Engineering

1. Indentify the Task

Determine what knowledge must be represented in order to connect problem instances to answers i.e. the PEAS Process:

- Performance Measure (be safe, maximize profits, obey laws)
- Environment (urban streets, weather, customers)
- Actuators: Used to measure the continuous and discrete process variables. 
- Sensors: Used to measure the continuous and discrete process variables.

In our case, PEAS can be:

  1. Assemble the Relevant Knowledge
//      especially in a particular kind of language or branch of study.
var AxiomTerm = new Thing ('Term Axiom', 'axiom', uuidv4());

∀x∃y RFP(x) - Create(y, x) ∧ Company(y) ∨ → ↔ ¬ 

RFP → Thing 

// [RFP]-()-[Create]-()-[Company]

query: RFP:['#125']

algoC to find , join -> [RFP:'125']-(obj)-[CREATE]-(agent)-[Company:'?']
// Get company  fetch node '125' from gun and traverse create edge and return target of edge

[Person: {Sue, Liz}]-agent-[Dance]

gun.get('Person').get(Sue).put({label:'sue',agent:{label:'dance'}})

var concept = {label:'', function:'', value:''}

gun.set({concept:'', ''}  )

function Thing (label, type, uuid, arcs, value) {
  this.label = label;
  this.type = type; //graph axiom/context, concept, relation
  this.uuid = uuid;
  this.arcs = arcs;
  this.value = value;
  this.concept = []; //concept array for axioms
  this.relation = [];

thing => storage => Object.assign(new Thing(), data) 

  // Term Axiom
//      Term: a word or phrase used to describe a thing or to express a concept, 
//      especially in a particular kind of language or branch of study.
// Language = HTML

var AxiomTerm = new Thing ('Term Axiom', 'axiom', uuidv4());

  Term → ... Translate(Concept)

  HTML                  Javascript

  Javascript        Javascript

  Term → ... Translate(Concept)

  Translate(Javascript) ↔ AxiomTerm Translate(Javascript)

  I have <div class="person" />
  I have Concept('Person')
  I have Relation({source: Concept, target: Term})
  I have Relation({source: Term, target: Term})

  Translate Person

  Blog post
  4 overviews of the latest blog post?

  Context(Overview)
   context(blogpost1)
   context(footer)
   context(sidemenu)

  [BlogPost]-has-[Title] Title-(is)-Link Title-is-HTML(h1)
  [List]-has-ListItem List-html-ul'?' Listitem-html-li:'?' [DOM]-has-List ListItem-childOf-List List-parentOf-ListItem

  object-attr-innerHTML='dididididid'
  DOM-has-object

  listed(linked(title(blog)))

  context(list) translate HTML ? // <ul><li><a href="https://github.com/Dletta/conceptGraph/blob/master/SDF">Blog Post Title</a></li></ul>

/*
  <li class="vcard"> [vcardContainer:uuid]
  <span class="adr">
    <span class="street-address">665 3rd Street</span>
    <span class="locality">San Francisco</span>
    <span class="postal-code">94107</span>
    <span class="region">California</span>
  </span>
  </li>
*/

  vcard [Person:'Jake']-(arg)-[Retrieve]-(res)-[vcard:object]
  Bio

  var add = new Thing('Sum Axiom', 'axiom', uuidv4());

  [] - () - [] - () - []

  [CompanyContext]-(agent)-[Create]-(obj)-[PRF]
  [Company]-attr-[Name]
  [Company]-attr-[Address]
  [Entity]-attr-[Name]  
  Thing:RFP
  Join [Company]<[Entity] ∀x∃y Entity(x) ∧ has(x,y) ∧ Name(y);    ∨ → ↔ ¬ 

  language?
  'context'
  uuid
  contract Company(uuid,context) ↔ Company(uuid,context)


  git clone https://github.com/amark/gun.git
cd gun
docker build -t myrepo/gundb:v1 .
docker run -p 8765:8765 myrepo/gundb:v1

Runs on 18.222.4.31.