HyperPlex
High-Precision Query-Response
Knowledge Repository
© Hyper Realm Consulting 2000-2010 © kenablersys 2010, to 201...
WE Information / Knowledge Seekers

2

 Want answers to Our

questions or queries
 For that we need a good
query facilit...
Kinds of Queries
 Are many and
 The expected
responses are also
many
 Here we are
considering queries
that are:
HyperPl...
Typical Questions
1. Is Washington a city,
state, university,
person or an object?
2. How is electrical
current different
...
More Questions & Expectations
 How is A different form B &
Why?
 What is the cause of X and
what are the conditions for ...
So what we need is:

6

 A dynamic knowledge

builder cum server or
repository with
 A High-Precision
Query Facility
 G...
What or Who has the capability we need?
1. Books &
Books just have text and graphics
Libraries?
2. Human
Experts?

Humans,...
Books & Libraries?

Yes, they served us well,
But we had to work hard
HyperPlex (c) 2000-2014 All rights reserved

8

 Th...
Human Experts?

9

 Professors,
 Consultants,
 Doctors,
 Lawyers
 Experts
 Yes, they have knowledge
 So far the bes...
Query Elicitation by Human Experts

10

 Good at finding out
 What the information seeker is looking for
 With minimum ...
Unfortunately…
 Human Experts are
 Not many
 Even those few are not accessible
 When one needs
 Particularly to the m...
Computers, Portals, & Search Engines?
 Recognize only the letters of a word
 Google, Bing,
and process them (coarsely)
W...
The problem is with MEANING

13

 Meaning is too complex
 Five factors are involved
 Machines, including software,
cann...
Certain aspects of MEANING can be
 Dealt with mechanically
 That is, without human or artificial
intelligence or underst...
Words seen as just strings of letters
 Most search engines have
 Single field for query &
 No way to qualify query term...
Too many hits of uncertain relevance
 Search Engines give far
too many responses

 Relevance ranking
criteria are
 Not ...
Single Field for query
Query:

17

________________________________

1. Most search engines JUST provide a single field fo...
Semantic Web, KIF, RDF, OWL
Universal Network Language UNL
 Have recognized the need
for dealing with meaning
 Though th...
Top Semantic Web Applications
 The latest available for 2010 at
 http://readwrite.com/2010/12/29/top_10_se
mantic_web_pr...
Winners of 2013 Sem Web Challenge

http://www.elsevier.com/about/
press-releases/science-andtechnology/winners-of-the-2013...
A Superior Possibility: HyperPlex
HyperPlex is a
 High-Precision
 Query-Response
 Knowledge
Repository
Feasible & viabl...
Precise Answers can only come from,
 Precise Queries

 The encoded knowledge

 So, HyperPlex has a
facility for

 Must...
HyperPlex builds on RDF
 HyperPlex uses
 Subject-Predicate-Object Structure of
knowledge representation of
 RDF--Resour...
Knowledge Structures &
Parameters of Precision
 Each of Subject, Predicate & Object of RDF

 Needs machine readable
 Ty...
HyperPlex is about High-Precision Q&A
Query Dialog
Box

HyperPlex
Query
AutoComplete

Knowledge
Seekers
HyperPlex (c) 2000...
One + Three Field Query
1+3 Field Query Box
Gen
Sub

Pred

Obj

HyperPlex (c) 2000-2014 All rights reserved

26

 Struggl...
High-Precision 1+3 Field Query
Gen
Sub

Pred

Obj

Gen: A common field
Subject, Predicate & Object
3 special fields for --...
Rapid Shortlisting of
Subject Predicate & Object Options
1+3 Field Query
Box
Gen
Sub

Pred

Field
parameters

Obj

Shortli...
High-Precision Knowledge Authoring

29

Text, graphics, video & speech in
computers IS NOT Knowledge

Not machine
processa...
RDF & UNL Also Represent Knowledge

30

1.But NOT with sufficient precision in our humble opinion
Special typing & micro2....
Meaning & Understanding of text
 There are many meanings of
these words but no
agreement on them
 Understanding is a hum...
Restricted meaning of meaning is used
1. In Semantic Web, RDF,
UNL etc.,
2. And also in HyperPlex
3. In both cases the S-P...
HyperPlex Summary

1. High Precision Q-R
Query-Response is the
key
2. 1+3 FQ is something
special and unique

HyperPlex (c...
Status and Plans
 Claim: An improvement over Protégé
and Google, Yahoo in precision &
relevance --- ckeck it out
 HyperP...
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HyperPlex --- High Precision Query-Response Knowledge Repository PDF

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A good source of knowledge should be able to provide RELEVANT, up-to-minute, and authentic High Precision Answers to QUERIES. For that a High-Precision QUERY-RESPONSE facility is crucial.

Of course the knowledge also must be stored with equally High-Precision in machine -processable form. For that a high precision knowledge authoring which is different from "creating text" is necessary.

Both the above facilities are available in HyperPlex.

Now you can get precise and valid answers to questions like: How is A different from B and Why? When and Why is P mistaken as Q? How to detect and correct?

This goes beyond what KIF, RDF, UNL have come up with so far. Join us to complete HyperPlex and DEPLOY IT.

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HyperPlex --- High Precision Query-Response Knowledge Repository PDF

  1. 1. HyperPlex High-Precision Query-Response Knowledge Repository © Hyper Realm Consulting 2000-2010 © kenablersys 2010, to 2014 All rights reserved.
  2. 2. WE Information / Knowledge Seekers 2  Want answers to Our questions or queries  For that we need a good query facility Knowledge Seekers For PDF version click the link below http://www.slideshare.net/putchavn/hyper-plex-high-precision-knowledge-authoring-queryresponse-system-06mar13 HyperPlex (c) 2000-2014 All rights reserved 04 JAN 14
  3. 3. Kinds of Queries  Are many and  The expected responses are also many  Here we are considering queries that are: HyperPlex (c) 2000-2014 All rights reserved 3  Serious,  Precise,  Complex,  deep! Like.. 04 JAN 14
  4. 4. Typical Questions 1. Is Washington a city, state, university, person or an object? 2. How is electrical current different from voltage? HyperPlex (c) 2000-2014 All rights reserved 4 3. Since convex lenses are used for sight correction in presbyopia and hyperopia are they the same? If NOT, what is the difference and why does it arise? 04 JAN 14
  5. 5. More Questions & Expectations  How is A different form B & Why?  What is the cause of X and what are the conditions for X to occur or NOT to occur?  What is NOT P but may be mistaken as P and Why? HyperPlex (c) 2000-2014 All rights reserved 5 Attributes of Answers  Precise  Relevant,  Latest and  Correct / Authentic 04 JAN 14
  6. 6. So what we need is: 6  A dynamic knowledge builder cum server or repository with  A High-Precision Query Facility  Giving Answers with specific attributes HyperPlex (c) 2000-2014 All rights reserved Q&A Let’s see what we have 04 JAN 14
  7. 7. What or Who has the capability we need? 1. Books & Books just have text and graphics Libraries? 2. Human Experts? Humans, YES they have knowledge and interactive capability to deliver responses 3. Search Engines? So far, these are like 1 but are improving with Semantic Web Technologies HyperPlex (c) 2000-2014 All rights reserved 04 JAN 14 7
  8. 8. Books & Libraries? Yes, they served us well, But we had to work hard HyperPlex (c) 2000-2014 All rights reserved 8  The seeker has to be a skilled scholar  To find right information 04 JAN 14
  9. 9. Human Experts? 9  Professors,  Consultants,  Doctors,  Lawyers  Experts  Yes, they have knowledge  So far the best to deliver answers to queries HyperPlex (c) 2000-2014 All rights reserved 04 JAN 14
  10. 10. Query Elicitation by Human Experts 10  Good at finding out  What the information seeker is looking for  With minimum probing  In natural languages / body language  Then they present But this may NOT be true with every human expert & it may NOT uniform  Most relevant units of information  Closely matching the needs of information seeker HyperPlex (c) 2000-2014 All rights reserved 04 JAN 14
  11. 11. Unfortunately…  Human Experts are  Not many  Even those few are not accessible  When one needs  Particularly to the millions of information seekers 11 Alternatives?  They are growing, as are topics HyperPlex (c) 2000-2014 All rights reserved 04 JAN 14
  12. 12. Computers, Portals, & Search Engines?  Recognize only the letters of a word  Google, Bing, and process them (coarsely) Wolfram Alpha,  Their meaning is NOT addressed  Information  Subjectively useful to SKILLED users Retrieval  Statistics determine Relevance, Precision & Reliability of hits---NOT Systems meaning of queries HyperPlex (c) 2000-2014 All rights reserved 04 JAN 14 12
  13. 13. The problem is with MEANING 13  Meaning is too complex  Five factors are involved  Machines, including software, cannot address  Many aspects of meaning  Even approximately See the PPT Semantic Web: The Need, Basics and Benefits HyperPlex (c) 2000-2014 All rights reserved 04 JAN 14
  14. 14. Certain aspects of MEANING can be  Dealt with mechanically  That is, without human or artificial intelligence or understanding  That’s the scope of Semantic Web, RDF, OWL or UNL  But they have NOT done much HyperPlex (c) 2000-2014 All rights reserved 14  Something more meaningful can still be done  HyperPlex can precisely answer the typical queries considered 04 JAN 14
  15. 15. Words seen as just strings of letters  Most search engines have  Single field for query &  No way to qualify query terms  Terms like “Of, From, By, when” are ignored  Only occurrences of words are considered HyperPlex (c) 2000-2014 All rights reserved 15  Synonyms, or equivalents are NOT recognized  No aspects of meaning of words are addressed 04 JAN 14
  16. 16. Too many hits of uncertain relevance  Search Engines give far too many responses  Relevance ranking criteria are  Not open & cannot be defined by the user HyperPlex (c) 2000-2014 All rights reserved  Search results could be irrelevant & misleading  Information seeker needs  To personally search again  To find relevant response 04 JAN 14 16
  17. 17. Single Field for query Query: 17 ________________________________ 1. Most search engines JUST provide a single field for query 2. Most Information Seekers CAN GIVE supplementary information to make their queries precise 3. But most search engines don’t accept 2 & 4. Can’t use that additional information HyperPlex (c) 2000-2014 All rights reserved Advanced Search exists but is not good enough 04 JAN 14
  18. 18. Semantic Web, KIF, RDF, OWL Universal Network Language UNL  Have recognized the need for dealing with meaning  Though they cannot capture full significance of meaning  They promise meaning centric applications HyperPlex (c) 2000-2014 All rights reserved 18  World Wide Web standards exist since 2000, 2004, 2011  Let’s see recent  Top Semantic Web applications 04 JAN 14
  19. 19. Top Semantic Web Applications  The latest available for 2010 at  http://readwrite.com/2010/12/29/top_10_se mantic_web_products_of_2010#awesm=~oqQ9 9xQoEriPqg  No products with  High-precision knowledge encoding & query response HyperPlex (c) 2000-2014 All rights reserved 19  Meaning is central to  Queries & Relevant Responses  Now machines can mechanically make sense of  Suitably encoded knowledge / content 04 JAN 14
  20. 20. Winners of 2013 Sem Web Challenge http://www.elsevier.com/about/ press-releases/science-andtechnology/winners-of-the-2013semantic-web-challengeannounced-at-the-internationalsemantic-web-conference-heldin-sydney HyperPlex (c) 2000-2014 All rights reserved 20  Indicate that  Proposed HyperPlex has identified  A critical gap in Semantic Web & is  Filling it 04 JAN 14
  21. 21. A Superior Possibility: HyperPlex HyperPlex is a  High-Precision  Query-Response  Knowledge Repository Feasible & viable 21  We know & understand meaning  HyperPlex DOES NOT claim to Know or understand meaning  But it structures & parameterizes knowledge sufficiently  To make sense of queries & give precise meaningful answers HyperPlex (c) 2000-2014 All rights reserved 04 JAN 14
  22. 22. Precise Answers can only come from,  Precise Queries  The encoded knowledge  So, HyperPlex has a facility for  Must be fine-grained &  Must have the same  High-Precision Query formulation  Knowledge structures &  But that’s NOT all  Used in query HyperPlex (c) 2000-2014 All rights reserved  Parameters of precision 04 JAN 14 22
  23. 23. HyperPlex builds on RDF  HyperPlex uses  Subject-Predicate-Object Structure of knowledge representation of  RDF--Resource Description Framework  It is suitable but NOT sufficient  So, HyperPlex has added  Knowledge types & parameters HyperPlex (c) 2000-2014 All rights reserved 23  HyperPlex Goes beyond RDF to add  Expressive power &  Precision to  Encoded Knowledge 04 JAN 14
  24. 24. Knowledge Structures & Parameters of Precision  Each of Subject, Predicate & Object of RDF  Needs machine readable  Typing (category) &  Special microstructures (meta tags) for each type  HyperPlex has added them  To encode & process meaning with precision HyperPlex (c) 2000-2014 All rights reserved 24 Still HyperPlex does not claim to know or understand meaning 04 JAN 14
  25. 25. HyperPlex is about High-Precision Q&A Query Dialog Box HyperPlex Query AutoComplete Knowledge Seekers HyperPlex (c) 2000-2014 All rights reserved A Software Suite for K Building & Delivery Data & Information 04 JAN 14 25
  26. 26. One + Three Field Query 1+3 Field Query Box Gen Sub Pred Obj HyperPlex (c) 2000-2014 All rights reserved 26  Struggled with typical search engines and  added what they lack High-Precision comes from One General + 3 Special Fields 04 JAN 14
  27. 27. High-Precision 1+3 Field Query Gen Sub Pred Obj Gen: A common field Subject, Predicate & Object 3 special fields for -- RDF Triple HyperPlex (c) 2000-2014 All rights reserved 27 As you fill-in Gen, HyperPlex Autocompletes the other 3 Typing + microstructures of S, P & O help matching & drilling down to more details 04 JAN 14
  28. 28. Rapid Shortlisting of Subject Predicate & Object Options 1+3 Field Query Box Gen Sub Pred Field parameters Obj Shortlist of more relevant & precise options HyperPlex HyperPlex (c) 2000-2014 All rights reserved 28  Query & Response are interleaved  Response is refined by choosing autocompleted options of different fields  The parameters are many & fine-grained 04 JAN 14
  29. 29. High-Precision Knowledge Authoring 29 Text, graphics, video & speech in computers IS NOT Knowledge Not machine processable That content has to be rewritten more finely for machine processing Knowledge Authoring Then high-precision Query & Response The need are possible HyperPlex (c) 2000-2014 All rights reserved 04 JAN 14
  30. 30. RDF & UNL Also Represent Knowledge 30 1.But NOT with sufficient precision in our humble opinion Special typing & micro2. structures for HyperPlex has High-Precision encoding of knowledge HyperPlex (c) 2000-2014 All rights reserved That is our IP. We can license it Semi automated 04 JAN 14
  31. 31. Meaning & Understanding of text  There are many meanings of these words but no agreement on them  Understanding is a human ability to act on the meaning of text  It is out side the scope of machines and software 31  We consider a restricted meaning of meaning for humans & machines  Well-formulated text prompts certain actions  Such action is the meaning of that text See the PPT Semantic Web: The Need, Basics and Benefits HyperPlex (c) 2000-2014 All rights reserved 04 JAN 14
  32. 32. Restricted meaning of meaning is used 1. In Semantic Web, RDF, UNL etc., 2. And also in HyperPlex 3. In both cases the S-P-O structure & meta tags 4. Represent knowledge 5. There are defined ways of acting on 3 HyperPlex (c) 2000-2014 All rights reserved  HyperPlex has many types of Subject, Predicate & Object  And each has many parameters  So, it is possible to encode many details of knowledge in machine readable form  And get precise response 04 JAN 14 32
  33. 33. HyperPlex Summary 1. High Precision Q-R Query-Response is the key 2. 1+3 FQ is something special and unique HyperPlex (c) 2000-2014 All rights reserved 33 3. High-precision encoding or Authoring of knowledge is the foundation for the Q-R 4. Special Structures and Micro-structures make this possible 04 JAN 14
  34. 34. Status and Plans  Claim: An improvement over Protégé and Google, Yahoo in precision & relevance --- ckeck it out  HyperPlex is the intellectual property of joint project partners  Non-exclusively licensed  It is under implementation HyperPlex (c) 2000-2014 All rights reserved 34 Confidential Information will be disclosed under non-disclosure agreement Think Let’s Talk 04 JAN 14

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