Knowledge is a very common and widely used word but it is hard to find a comprehensive and precise definition of knowledge---particularly in the context of humans and machines. Same is the case of "meaning" which is related to "knowledge". Here is a proposal of definition of knowledge and a knowledge builder server HyperPlex initiated during 90s and formulated in the present form in 2008. We claim that HyperPlex has high expressive power and precision than KIF, RDF and UNL. Links are provided to pdfs and ppts on slideshare. Please take a look and leave a comment. Thanks

1. Knowledge
Representation & Processing
Putcha V. Narasimham
Knowledge Enabler Systems
putchavn@yahoo.com

2. This is Section 3 of
Semantic Web:
Dealing with Knowledge & Meaning
Putcha V. Narasimham
Knowledge Enabler Systems
putchavn@yahoo.com

3. • Knowledge Rep & Processing
What is Knowledge is NOT
22 JAN 14
Knowledge is NOT
 Data & information
NOR
 The Contents of:


http://www.slideshare.net/putchavn/concept-mapsknowledge-encoding and

Knuth’s definitions of data and
information

http://www.slideshare.net/putchavn/knuthsdefinitions-of-data-and-information-04-mar13
 Books, Dictionaries,
Encyclopedias ?
 Files, Databases?
This builds on
Concept Maps & Knowledge Encoding
3

4. What Knowledge is
Knowledge Rep & Processing
1. How about people, DBMS, Search Engines, do they have
22 JAN 14
knowledge?
2. Yes, they have knowledge
 Why do we say yes for 1 and
 NO for books, files & databases
 What is the difference?
 See the following explanation and the proposed definition
4

5. Entities, NOT media, have Knowledge
Essentially data
& information
Knowledge Rep & Processing
Stimuli
22 JAN 14
Environment
response
Essentially data
& information
has
ability
To Receive, Hold,
Process and or create
data / Information &
deliver them
That is Knowledge
5

6. Knowledge: Proposed Definition
Knowledge Rep & Processing

22 JAN 14

Knowledge is the ability of an entity
to respond
To Hold, Process
To Stimuli
Expressions of
Knowledge are D & I
But D & I are not K
To deliver D & I
and or create
data / Information
Queries of specified types within a Domain
See http://www.slideshare.net/putchavn/knuths-definitions-of-data-andinformation-proposed-definition-of-knowledge-03-mar13
6

7. Knowledge Representation
Knowledge Rep & Processing

22 JAN 14
Based on the definitions





of data & information
and knowledge
Knowledge
representation is a way
of encoding the content
so that:
Computer and its software can



Manipulate that content
To generate responses
That a good knowledge source
would generate
Encoding & processing gives
that ability i.e., knowledge to
computers & software
7

8. Knowledge Representation Standards

Knowledge Rep & Processing

22 JAN 14



Knowledge Interchange Format KIF
Resource Description Framework RDF
Universal Network Language UNL
Perhaps more
Their basic principles appear to be
similar

Our proposed
HyperPlex




Has more
Expressive Power &
Precision
Open to checkingg
See http://www.slideshare.net/putchavn/knuths-definitions-of-data-and-information-proposeddefinition-of-knowledge-03-mar13
8

9. HyperPlex for Meaningful Query-Response
Knowledge Rep & Processing

22 JAN 14



Now you may take a look at
our HyperPlex (link in next slide)
It is a High Precision
Knowledge Authoring and
Query-Response System
Based on Concept Maps with
Nodes and Links having well
defined microstructures




As a result HyperPlex is capable
of encoding, decoding and
processing
Knowledge with high-precision
It addresses and deals with
What we call meaning to the
extent the meaning is encoded
using the microstructures
9

10. Knowledge Rep & Processing
Link to HyperPlex
22 JAN 14
PDF:
http://www.slideshare.net/putchavn/hyper-plex-highprecision-knowledge-authoring-queryresponse-system06mar13
There is PPT also on slideshare
http://www.slideshare.net/putchavn/hyper-plex-high-precision-queryresponseknowledge-repository-pdf
10

11. Conclusion
Knowledge Rep & Processing

22 JAN 14

Could not find clear
& usable definitions
of Knowledge and
meaning
Particularly those
valid in human and
machine contexts



A definition of knowledge (first proposed
in 2000) is explained
It enables encoding knowledge for
machine processing
KIF, RDF, and UNL which evolved around
2000 are similar but (we believe) lack
expressive power & precision of our
HyperPlex
11