Concept Maps & Knowledge Encoding

Concept Maps &Knowledge Encoding

Putcha V. Narasimham

Knowledge Enabler Systems

06 JAN 14Concept Maps & Knowledge Encoding 1

KEY SECTIONS & TOPICSSection 1

Graphic Representation

Concepts, Ovals

Relations or Links, Arrow lines

Section 2

Principles of Concept Modeling

Monads, Dyads, Triads

Examples: Mother, Child, Motherhood, Impact, Commerce, System, Reasoning

Section 3

Knowledge Encoding

Essential nature of concepts

Human & machine compatibility

Concept expression and communication

Knowledge encoding and processing, HyperPlex

Appendix: Formal Concept Analysis


GRAPHIC REPRESENTATION OF CONCEPTSSECTION 1


WHAT ARE CONCEPT MAPS

Graphical or Visual

Representations of concepts (in ovals)

And their relations (arrow lines with labels)

Concept 1

Concept 2 Concept 5

Concept 3

Concept 4

Relation 4

Relation 1

Relation 3

Relation 2


CONCEPT MAPS WITH BLOCK ARROWS

Concepts in ovals

And their relations in Block Arrows

Concept 1

Concept 2Concept 5

Concept 3

Concept 4

Relation 4

Relatio

n 1

C


WHAT CONCEPT MAPS ARE NOT

Topic Maps

Very close;

Associations are not labeled

Occurrences are added

ISO standard for knowledge Interchange

Mind Maps

Hierarchy of concepts

Ontology—very close

Biological or Artificial Neural Networks

Images of brain


ORIGIN OF CONCEPT MAPS

Invented in 1972

By Novak & Cañas et al

To enable children to build concepts of science

At Cornell University

In collaboration with Florida Institute for Human and Machine Cognition

http://cmap.ihmc.us/publications/researchpapers/originsofconceptmappingtool.pdf


http://cmap.ihmc.us/publications/researchpapers/originsofconceptmappingtool.pdf

ELEGANT FOR HUMANS & MACHINES

Graphic Concept Maps

Help clear

Visualizing, expression and communication

By humans

More importantly

The principles of Concept Maps also help

Precise representation of knowledge

For Machine Processing


PRINCIPLES OF CONCEPT MODELINGSECTION 2


WHAT IS CONCEPT?

An idea or a thought

A set of related thoughts

A concept is an idea, something that is conceived in the human mind--Wikipedia

These are colloquial definitions or meanings

See separate PPT for Fundamentals of Thinking, Brain, Mind & Consciousness for details


http://en.wikipedia.org/wiki/Concept

CONCEPTS ARE FORMED IN MIND ABOUT

1. Entities, existing or imagined objects

2. Phenomena

3. Sensations,

4. Emotions

5. Actions

6. Relations among 1….5

What and where is MIND? NOT discussed here

We will discuss simple and complex concepts using 1…5 and 6

Linking Concepts

Stan

d-a

lon

e

1….5


STAND-ALONE CONCEPT --- MONAD

It can be defined directly without reference to any other concept

Self-sufficient

Some nouns are monads

And some are NOT

Monads

Have their own properties

ManNeuron

Mountain

06 JAN 14Concept Maps & Knowledge Encoding

12

TWO FUNDAMENTAL BUILDING BLOCKS

Defined in the previous slide

Can be a Subject or Object

In Subject-Predicate-Object structure of RDF standard

Has many sub-types

Is also a concept

Connects two concepts

Shows their relation

Also called predicate

Has many sub-types

Stand-alone

Concept Monad

Linking

Concept

And Mutually Exclusive

1306 JAN 14Concept Maps & Knowledge Encoding

LINKING CONCEPT: A LABELED ARROW

That is the form used in the original proposal

It is mistaken as a pointer

Block arrow shows that LINK is a solid, full-fledged object

Concept 1

Concept 3

Relation 1

Relation 2

Concept 2


CONCEPT MAP OF CONCEP MAP

Concept Map is a graphical representation of

A compound concept

In terms of monads (or Nodes) & Links

This is the basis of

UML Class & Composition Diagrams

Semantic Web &

RDF Resource Description Framework

Concept

Stand-alone

ConceptMonad

Linking

Concept


Is it a class or composition

diagram?

RECIPROCAL RELATION

Every BINARY relation has direction

Every relation R1 has a reciprocal R2

R1 & R2 may be the same (symmetrical)

A is friend of B &

B is friend of A

Different (asymmetrical)

P is father of Q

But Q cannot be father of P

Monad Concept 2

Monad Concept 1

Ha

s re

latio

n

R1

with

Ha

s re

latio

n

R2

with


DYAD—INVOLVES TWO CONCEPTS

Neither can be defined by itself

Child is NOT just small man (boy) or woman (girl)

Mother is NOT just any woman

The two concepts arise together

Necessary for each otherChild

Mother


Mutually dependent

DYADS—MOTHER & CHILD AND RELATION

Concept Type

Mother is a woman who Dyad

Gives birth to Relation

A child (male or female) DyadChild

Mother


DYAD —IMPACT IS A PHENOMENON

What happens when

TWO bodies

At least one of which is moving

Come into contact with the other

Moving or stationary Body 2

Moving Body 1

IMPACT


TRIAD—RELATES TWO OR MORE CONCEPTS

Motherhood

A total concept of a woman giving birth to a child and nurturing the child

Ch

ild

Mo

ther

Motherhood


Is childhood a reciprocal concept?

TRIAD—AVIATION

Aviation

A relation between

Mode of travel by air and

The passengers & cargo

Pla

nes

Pass

enge

rs

Aviation


MORE THAN A TRIAD --- COMMERCE

Bu

yer

Selle

r

Money

Goods / Services


MORE THAN A TRIAD --- SYSTEM

Envi

ron

men

t

Interrelated & interacting

Consists of


Elem

entsConsists of

Is a part of Is a part of

HOW ABOUT “REASONING”

This came up in the discussions during

The IEEE Seminar on Semantic Networks at Muffakhram JahCollege of Engineering and Technology, Hydrabad

on 14 DEC 13

1. It falls under item 5 Actions

2. In humans, the action is mental

3. Expression of 2 is in some natural language

4. Reasoning involves application of rules of logic

5. To observations, statements, conclusions

6. It is more than a triad

7. Send your concept map to [email protected]

06 JAN 14

Concept Maps & Knowledge Encoding 24

KNOWLEDGE ENCODING USING CONCEPT MAPSSECTION 3


THE ESSENTIAL NATURE OF CONCEPTS

Essentially the Concept Maps seem to exist in

Human minds or

Text & speech or

Computers

To represent & process knowledge

The exact form

Of concept maps in

Humans & Machines varies

But recognition of the essential nature of knowledge is profound


HUMAN EXPRESSION & COMMUNICATION

Expression is explicit statement for communication

Can be observed & interpreted

Expressions can be physiological changes, gestures, utterances, speech, linguistic, mathematical, graphic..

If standard conventions, grammar, lexicon are followed

The expressions clearly communicate the concepts

Some negotiation may be necessary to disambiguate


HUMAN & MACHINE COMPATIBILITY

Concept Maps graphically represent knowledge

Using Nodes & Links

For use by humans

The explicit

Information & data

Relating to Nodes & Links

Is also well-suited for machine processing


See

Data & Information: Knuth’s Definitions

CONCEPT MAPS FOR MACHINE PROCESSING

The explicit Nodes & Links of Concept Maps

Help knowledge representation for

Humans & Machines

Information is in the micro-structures of templates of Nodes & Links

Data are in

The populated Nodes & Links +

The specific configurations of populated Nodes and Links


See

HyperPlex

HIGH PRECISION QUERY-RESPONSE

By defining microstructures of Nodes and Links

We can encodemany more details of concepts precisely

All those details can be precisely EVALUATED to generate specific responses for action

Not like thousands of hits of search engines

See HyperPlex


See

HyperPlex

FORMAL CONCEPT ANALYSIS

So far we have used linguistic description of concepts

Traditional Logic is applied to concept analysis

Rudolf Wille’s proposal of Concept Lattices & Formal Concept Analysis in 1982 is generally accepted as very significant

See the Appendix on this

06 JAN 14


LINKS TO REFERENCES CITED

http://www.slideshare.net/putchavn/knuths-definitions-of-data-and-information-04-mar13

http://www.slideshare.net/putchavn/hyper-plex-high-precision-queryresponse-knowledge-repository-pdf

06 JAN 14


SUMMARY & CONCLUSION

Concept Maps are simple and profound for

Knowledge representation, communication and processing

Both in humans & machines

KIF, RDF & UNL are some standards for encoding knowledge in machines

HyperPlex is our proposal for high precision query-response


FORMAL CONCEPT ANALYSIS & CONCEPT LATTICESAPPENDIX


PRECISION OF CONCEPT (MATH)

http://en.wikipedia.org/wiki/Accuracy_and_precision

This is informative but applies to quantitative measurement

See the notes below

This does not apply to concept

Formal Concept Analysis is a branch of mathematics

Deals with concepts and context in terms of Objects, their attributes and interrelations between them

06 JAN 14


http://en.wikipedia.org/wiki/Accuracy_and_precision

FORMAL CONCEPT ANALYSIS (INFORMATION SCIENCE)

a principled way of deriving a concept hierarchy or formal ontology from a collection of objects and their properties.

Each concept in the hierarchy represents the set of objects sharing the same values for a certain set of properties; and

each sub-concept in the hierarchy contains a subset of the objects in the concepts above it

Fits with INTRA Class Diagram of OOAD

06 JAN 14


http://en.wikipedia.org/wiki/Principle

http://en.wikipedia.org/wiki/Ontology_(computer_science)

http://en.wikipedia.org/wiki/Mathematical_object

http://en.wikipedia.org/wiki/Property_(philosophy)

http://en.wikipedia.org/wiki/Subset

TENTATIVE VIEW OF PRECISION OF CONCEPT

Precision of a

concept is NOT

fineness of

concept but its

distinction from

similar concepts

of the class

It is best to apply Formal Concept Analysis and Concept Lattices

The class-subclass hierarchy of OOAD is sound and applicable

PRECISION of CONCEPT may be taken as 1/n TENTATIVELY, where nis the number of all sub-classes of the concept class

06 JAN 14


A COMPREHENSIVE AND EXCELLENT SOURCE

INTRODUCTION TO FORMAL CONCEPT ANALYSIS (2008)

RADIM BˇELOHL´AVEK

Department of Computer Science PalackyUniversity, Olomouc

It is highly mathematical

Needs to be studied for modeling and software development

06 JAN 14


ORDERED SETS

http://logcom.oxfordjournals.org/content/12/1/137.short

http://golem.ph.utexas.edu/category/2013/09/formal_concept_analysis.html

schroeder, ordered sets, first

chapter.pdf - Louisiana Tech

University

Schröder, Bernd S. W. 1966-

Ordered sets : an introduction


http://logcom.oxfordjournals.org/content/12/1/137.short

http://golem.ph.utexas.edu/category/2013/09/formal_concept_analysis.html

http://www2.latech.edu/~schroder/books/schroeder, ordered sets, first chapter.pdf