gmane.comp.ai.conceptual-graphs

[] What is the role of an upper level ontology?

John F Sowa — 2013-05-19T18:51:52

The following slightly edited note to Ontolog Forum summarizes
an ongoing thread about the topic in the subject line.

Anyone who may be interested in the topic can extract any phrase
quoted below, enclose it in quotes, and use any search engine
to find the original note (and thread) in the Ontolog archive.

Another useful resource is the proceedings of the KI2003 Workshop
on Reference Ontologies and Application Ontologies.  The articles
are now 10 years old, but they are still good position papers
on the various issues.  Most of the topics they discussed are
still ongoing R & D issues today:

http://sunsite.informatik.rwth-aachen.de/Publications/CEUR-WS/Vol-94/

John Sowa

-------- Original Message --------
Date: Sun, 19 May 2013
To: ontolog-forum-TYD3xnkLNKlCLzx1llviGw< at >public.gmane.org

My main point is that any upper-level ontology that claims to be
broadly applicable should avoid detailed axioms.  It should be
as neutral as possible with respect to any or all ontologies that
have proved to be useful for any practical purpose.

For complex reasoning, more detailed axioms are needed.  They can be
stored in a library of reusable modules that can be combined to form
more specialized ontologies or microtheories as needed.

WF

Yes.  Fallible theories that are known to be "not quite right"
can still be very useful.  Example:  Newtonian mechanics.  The
upper levels should contain the terms Mass, Energy, and Momentum,
but the detailed axioms should be contained in specialized modules.

Note that the more detailed modules are likely to have different
identity conditions for terms with the same spelling.  For a
lexical hierarchy like WordNet, it's important to relate all
terms with the same spelling, but it's also important to have
conventions for distinguishing different senses or microsenses.

JMc

For example, a lock is part of a door, and a door is part of a house.
But a lock is not normally considered part of a house.  Hydrogen is
part of water, and water may be part of a cooling system.  But
hydrogen is not considered part of the cooling system.

Ingvar Johansson analyzes and discusses these and other examples.
He observes that there is always some reason why the part relation
is not transitive, and it can be represented with a triadic part
relation.  See http://hem.passagen.se/ijohansson/function2.PDF

HP

WF

I agree that it's a good ontology for ncoic.org, and it's more general
than many specialized ontologies.  But it is less than universal.

HP

Yes.  But it is essential to accommodate legacy systems and anything
that might be developed in the future.  Ignoring them is not an option.

MW

That is true.  But some philosophers hope to use mereology as a basis
for defining many similar relations.  Membership is one of them.

HAK

This example and proposed solution are similar to the examples that IJ
cited, quoted, and analyzed.  I would also recommend other papers that
analyze these and related issues:  http://hem.passagen.se/ijohansson/

For example, see http://hem.passagen.se/ijohansson/information7.pdf

This article has a good analysis of many issues that have been debated
in Ontolog Forum.  Among them are the treatment of time, single vs.
multiple inheritance, and realist speech vs. conceptual speech.

Johansson has not given up all hope of developing a good upper level
ontology, but he has found serious flaws (or at least limitations
and exceptions) in the current proposals.

My recommendation is to consider a universal upper ontology as
a goal for further research.  For practical applications, any
or all ontologies that have been useful should be accommodated.

John

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[] GKR< at >IJCAI 2013 Second Call for Papers

Madalina Croitoru — 2013-03-04T13:35:48

==============================GKR< at >IJCAI 2013 SECOND CALL FOR 
PAPERS===================================

THE THIRD IJCAI INTERNATIONAL WORKSHOP ON GRAPH STRUCTURES FOR KNOWLEDGE 
REPRESENTATION AND REASONING

======================================================================================================

Graph-based knowledge representation and reasoning is a growing area of 
research, with more and more important contributions appearing over the 
last few years.

The workshop welcomes contributions that:

[] Archives for the Philosophy and History of Soft Computing

John F Sowa — 2013-02-27T15:37:46

The attachment announces a new online journal devoted to Archives
for the Philosophy and History of Soft Computing.

Most of the founders belong to the fuzzy systems community, but
they are broadening their scope to interdisciplinary studies
that focus on issues that relate technology and the humanities.

John Sowa

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[] Sapir-Whorf Hypothesis

John F Sowa — 2013-02-26T13:10:52

Following is a slightly edited note to Ontolog Forum about the way
the structures of different languages influence thought.  The first
URL in this note points to a TED talk on the subject.

At the end is a reference to the research article written by
the speaker.  The full paper is 56 pages long, but that includes
a lot of data and the list of 126 different languages in the study.

-------- Original Message --------
From: John F Sowa
To: ontolog-forum-TYD3xnkLNKlCLzx1llviGw< at >public.gmane.org

On 2/26/2013 5:22 AM, Hassan Aït-Kaci wrote:

Thanks for the pointer. Keith Chen is a good speaker, and he presented
the hypothesis and the results very well.  I recommend it.

Relationship to ontology:  Many of us have found that a 4D ontology
for spacetime is more useful for representing and reasoning about
certain kinds of relationships than a 3+1 D ontology.

In effect, English is a strongly 3+1 D language that forces every
statement to be situated on a time line.  But Chinese is more
of a 4D language that ignores the time line unless there is
a specific need to make the time reference explicit.

These issues are relevant to both the influence of different natural
languages on thought and the influence of different kinds of ontology
on methods for knowledge representation and reasoning.

Some observations about the talk:

   1. Keith did not claim that language constrains thought, but
      that it influences thought in a way that could be overcome
      by a conscious decision.

   2. He is not doing this study by himself.  He has been collaborating
      with colleagues at Yale in both linguistics and economics.

   3. He did not do data mining by blindly searching for correlations.

   4. Instead, he followed good scientific methodology: (1) formulate
      the hypothesis, (2) check it on some easy to find data, and then
      (3) test it on detailed data that could confirm it or refute it.

John
_____________________________________________________________________
http://faculty.som.yale.edu/keithchen/papers/LanguageWorkingPaper.pdf

The Effect of Language on Economic Behavior: Evidence from Savings
Rates, Health Behaviors, and Retirement Assets

M. Keith Chen

Yale University, School of Management and Cowles Foundation

Abstract:  Languages differ widely in the ways they encode time.
I test the hypothesis that languages that grammatically associate
the future and the present foster future-oriented behavior. This
prediction arises naturally when well-documented effects of language
structure are merged with models of intertemporal choice. Empirically,
I find that speakers of such languages save more, retire with more
wealth, smoke less, practice safer sex, and are less obese. This
holds both across countries and within countries when comparing
demographically similar native households. The evidence does not
support the most obvious forms of common causation. I discuss
implications for theories of intertemporal choice.

1 Introduction

Languages differ in whether or not they require speakers to
grammatically mark future events.  For example, a German speaker
predicting rain can naturally do so in the present tense, saying:
_Morgen regnet es_ which translates to 'It rains tomorrow'. In
contrast, English would require the use of a future marker like
'will' or 'is going to', as in: 'It will rain tomorrow'.

In this way, English requires speakers to encode a distinction
between present and future events, while German does not.  Could
this characteristic of language influence speakers’ intertemporal
choices? ...

Specifically, I adopt a criterion which distinguishes between
languages which Dahl (2000) calls “futureless”, and those which are
not. Dahl defines “futureless” languages as those which do not require
“the obligatory use [of grammaticalized future-time reference] in
(main clause) prediction-based contexts”....

6.1.1 Skepticism of the Weak Sapir-Whorf Hypothesis

While many studies support at least a weak form of the SWH, there are
a number of scholars who argue that on balance, the idea that cognition
is shaped by language is misguided. Most prominently, in his seminal
work _Syntactic Structures_ (1957), Chomsky argues that humans have
an innate set of mechanisms for learning language, and that this
constrains all human languages to conform with a “universal grammar”.

Taken in strong form, a universal grammar would largely eliminate the
scope for language to affect cognition. In _The Language Instinct_
(1994), Pinker argues exactly this: that humans do not think in the
language we speak in, but rather in an innate “mentalese” which
precedes natural language. He concludes that: “there is no scientific
evidence that languages dramatically shape their speakers’ ways of
thinking”. While a rich literature since 1994 has disputed this claim,
support for the SWH remains an hotly debated topic...

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Re: [] Prolog + CHR (Constraint Handling Rules)

John F Sowa — 2013-02-22T18:33:04

I received an offline note about the ClioPatria Semantic Web server,
which is written in Prolog and enables Prolog to do reasoning with
and about Semantic Web data:

    http://cliopatria.swi-prolog.org/help/whitepaper.html

This software is freely available, and it could be combined with other
Prolog-based tools.

John

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[] Ubuntu for tablets

John F Sowa — 2013-02-21T14:35:15

According to various market estimates, Smartphones based on the Android
OS from Google had a 68% market share in 2012 vs 20% for Apple.

Since Android is based on the Linux kernel, it was easy for the
developers of the popular Ubuntu version of Linux to make Ubuntu
run on top of Android.

But now they have taken the next logical step -- provide an Android-like
front end to Ubuntu that will run on any form factor:  Smartphones,
tablets, PCs, and TVs.  They also provide software that makes it easy
for vendors to convert Android apps to Ubuntu apps.

Since a tablet or PC has a larger screen than a phone, Ubuntu enables
multiple Smartphone apps to run concurrently in separate windows on
a larger screen.  See

    http://www.ubuntu.com/devices/tablet

Commercial developers are beginning to get into the Ubuntu market for
Smartphones.  That should help promote competition.   For more info,
type "ubuntu for tablets" to your favorite search engine.

John

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[] Prolog + CHR (Constraint Handling Rules)

John F Sowa — 2013-02-20T20:50:15

Following is a set of 90 slides about using Prolog + CHR to support
large-scale applications in finance:

    http://dtai.cs.kuleuven.be/CHR/files/Elston_SecuritEase.pdf

Prolog is a powerful platform for developing intelligent systems,
but it has fallen out of fashion as newer fads have sprung up.
But as this presentation shows, it is a highly scalable platform
that can support major applications.

The Experian credit bureau is a very large corporation, which uses
Prolog to check everybody's credit worthiness.  They use it so heavily
that they bought Prologia, the company founded by Alain Colmerauer,
who implemented the first version of Prolog.

But Experian is also a secretive company that doesn't tell anybody
what they do or how they do it.  Nevertheless, their size is a strong 
argument for the power of Prolog (and related technology).

The CHR notation compiles into Prolog:

    http://www.swi-prolog.org/man/chr.html

Acknowledgment: Thanks to Adrian Walker (in cc list above) for
sending me a copy of the presentation on Prolog + CHR.

John



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[] References on neuroscience and cognitive linguistics

John F Sowa — 2013-02-18T14:21:05

The Human Connectome Project is carrying out a detailed mapping
of the connections in the brain as a basis for further study and
for various attempts to simulate the human brain.

A BBC science correspondent volunteered to have the full 45 minute
scan, of which only 50 have been carried out so far. Following is
his description of the experience with some colored pictures of the
wiring in his brain:

http://www.bbc.co.uk/news/science-environment-21487016

For more pictures and more detail, see the project home page:

http://www.humanconnectomeproject.org/

The discussion is keyed to the various parts of the brain. I presented
a quick overview with some pictures and terminology in Section 1 of
my talk for ICCS in January (Slides 3 to 19):

http://www.jfsowa.com/talks/relating.pdf

Section 3 of that talk is based on publications by René Thom,
Wolfgang Wildgen, and Jean Petitot. See slide 20 for URLs.
Following are the slides from a talk by Wildgen in 2006:

http://www.slideserve.com/mariah/emergence-of-semantic-and-syntactic-complexity-in-language-wolfgang-wildgen

Following is an article by Wildgen in 2009:

http://www.helsinki.fi/varieng/journal/volumes/03/wildgen/

But the first three chapters of Wildgen's 1994 book are still the
best introduction for the motivation and development. Fortunately,
he posted them on his web site:

1. Meaning and reality
http://www.fb10.uni-bremen.de/homepages/wildgen/pdf/MeaningandReality.pdf

2. A critical review of some proposals for a semantics using image
and process schemata
http://www.fb10.uni-bremen.de/homepages/wildgen/pdf/CriticalReviewofProcessSemantics.pdf

3. Process and image schemata in the lexicon and in basic syntax
http://www.fb10.uni-bremen.de/homepages/wildgen/pdf/LexiconandBasicSyntax.pdf

These issues about relating continuous images to discrete patterns
of words and phrases in language are still highly controversial.
Following is the table of contents for a collection of articles
by various researchers on cognitive linguistics:

http://benjamins.com/#catalog/books/lis.19/toc

The first article is by Langacker, who is skeptical about the need
for continuity in linguistic representations. It also contains
articles by Thom and Petitot. The book costs 110 euros, but you
can browse through excerpts on Google books.

Summary: The research by Thom, Wildgen, and Petitot is still work
in progress, but it has a great deal of potential. Section 4 of the
slides I presented are based on an implementation by Arun Majumdar.
It has produced some very promising results in an application
for one of the VivoMind contracts.

Furthermore, this computational method requires much, much less
computation than a full simulation of the wiring in the brain.

John

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[] Architectural considerations in ontology development

John F Sowa — 2013-02-13T16:10:36

As my publications show, I often discuss philosophical issues
and relate them to software design and development.  But it's
important to recognize when and whether a distinction is relevant.

Following is a slightly edited version of a note to Ontolog Forum.

John Sowa

-------- Original Message --------
Subject: Re: Architectural considerations in ontology development
Date: Wed, 13 Feb 2013 10:56:17 -0500

...

There is a serious question of which philosophical distinctions
are relevant to an ontology and whether they belong at the *top*
level or the *bottom* levels.


That distinction can be critical for some applications and irrelevant
for others.  Many people (and computer applications) can get along very
well without ever thinking about or using those distinctions.


Those are also important philosophical issues.  But applications
that make different choices should be able to communicate with and
interoperate with other applications that ignore those distinctions.

In particular, legacy systems that have no explicit ontology aren't
going away.  Any ontology-based system that can't interoperate with
legacy systems will be relegated to a special-purpose niche.

I keep mentioning Amazon.com as a company that must interoperate with
every supplier and customer in the world.  Therefore, they require
an ontology that ignores all distinctions about products except
those that are relevant to buying, selling, shipping, and billing.

Summary: The distinctions an ontology requires are determined by its
purpose.  Making distinctions that are irrelevant to the purpose can
decrease its generality and interoperability.  Therefore, the quality
of an ontology should be measured by its *relevant* distinctions.

John


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[] Research directions

John F Sowa — 2013-02-12T16:30:10

In my books and papers, I like to show how the latest and greatest R & D
is related to historical developments over the past few millennia.

In the following note to Corpora list, I quote some examples and
summarize the issues in the last two paragraphs.

John

-------- Original Message --------
Subject: Re: [Corpora-List] Broader linguistic resources
Date: Tue, 12 Feb 2013 11:05:57 -0500
To: corpora-afly1vuFV30< at >public.gmane.org

On 2/12/2013 8:55 AM, Dominic P Rout wrote:

That question reminds me of a thread from last week (Feb 5).
The subject line was "New techniques in text processing":

Amac Herdagdelen asked:

Phil Gooch replied:

Adam Kilgarriff replied:

An excerpt from Adam's paper:

An excerpt from the Chambers & Jurafsky paper:

Adam's paper describes important methods for analyzing corpora.
They belong in the toolkit of anyone who processes large volumes
of NL texts.

But the paper by Chambers & Jurafsky shows how issues that were
popular 30 years ago can be revived as "cutting edge" research today.
The important difference is that the old hand-coded scripts can now
be derived by new methods of "deep learning".

For an example of a narrative structure by Chambers & Jurafsky, see
Figure 6 of http://acl.eldoc.ub.rug.nl/mirror/P/P08/P08-1090.pdf

For structures in kidnap, bombing, attack, and arson, see
http://www.stanford.edu/~jurafsky/acl2011-chambers-templates.pdf

The moral of this story is that research directions are heavily
influenced by available technology. With new technology, research
questions from decades ago (or even millennia ago) can be revived
and addressed with new methods.

The implication for education is that research techniques can become
obsolete, but fundamental questions never become obsolete.  Sometimes
the most fruitful research can be inspired by old questions that were
abandoned because the available technology was inadequate.

John Sowa

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Re: [] Big Data Logic

John F Sowa — 2013-02-05T13:29:16

I agree.

As I said in my earlier note, I believe that adopting Datalog
by the DAML project would have made a major contribution toward
supporting both RDBs and graph DBs based on RDF or other notations.

But the semantics is fundamental. Tim B-L's original proposal
contained a highly expressive version of logic called SWeLL
(Semantic Web Logic Language), which would have provided a
unified semantics for all the components.

Unfortunately, SWeLL was dropped. What happened is that each
component developed its own semantics, and each of them combined
the core logic with "features" that relate to the syntax, the
environment, and various ways of using each component.

What creates the complexity is the mixture of "design patterns".
For a survey of design patterns and the complexity created by
mixing them, see http://www.jfsowa.com/talks/kdptut.pdf

Slides 7, 8, and 9 give an example of Cyc as applied to the
Cleveland Clinic. I think that's a good application of Cyc,
but the mixtures of design patterns created something that is
very difficult for anybody (theoreticians and practitioners)
to understand.

It's the mixture of design patterns that "might give some
Datalog folks heartburn." Although the base logic might be
common to all, the mixtures make them incompatible.

John

Re: [] Big Data Logic

Rich Morin — 2013-02-04T16:48:19


Thanks for the links on Datalog; I'll add them to my resource list!

I should caution, however, that Datomic's flavor of Datalog is a bit
like Clojure's flavor of Lisp.  It keeps (most of) the critical ideas,
but adds and takes away details to Rich Hickey's taste.

For example:

  *  Everything (including rules, queries, schemas, transactions,
     etc) is encoded as data structures.

  *  Functions can be written (eg, in Clojure or Java), stored in
     Datomic, and evaluated as part of queries or transactions.

Seems very cool to me, but might give some Datalog folks heartburn...

-r

 -- 
http://www.cfcl.com/rdm            Rich Morin
http://www.cfcl.com/rdm/resume     rdm-go8te9J4rpw< at >public.gmane.org
http://www.cfcl.com/rdm/weblog     +1 650-873-7841

Software system design, development, and documentation



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Re: [] Big Data Logic

Jack Park — 2013-02-03T19:54:39

What a nice link: Clojure and Datomic. Here are what seem reasonable
starting points into Datalog:

http://en.wikipedia.org/wiki/Datalog
http://docs.racket-lang.org/datalog/
http://www.ccs.neu.edu/home/ramsdell/tools/datalog/datalog.html
http://db.cs.berkeley.edu/papers/datalog2011-dedalus.pdf

I've been lately building my knowledge structures in Apache Solr,
given that it includes a UIMA plugin, and lots of other "cool tools".
Indeed there is a project starting as a rational reconstruction of
Watson with that platform. It will be interesting to see if the
JCascalog code can fit in, along with conceptual graphs.

Jack

On Sun, Feb 3, 2013 at 10:42 AM, Rich Morin <rdm-go8te9J4rpw< at >public.gmane.org> wrote:

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Re: [] Big Data Logic

Rich Morin — 2013-02-03T18:42:31


FWIW, the Datomic database also uses Datalog:

  http://www.datomic.com/
  http://www.datomic.com/videos.html

Its designer (Rich Hickey) is also the creator of Clojure.

-r

 -- 
http://www.cfcl.com/rdm            Rich Morin
http://www.cfcl.com/rdm/resume     rdm-go8te9J4rpw< at >public.gmane.org
http://www.cfcl.com/rdm/weblog     +1 650-873-7841

Software system design, development, and documentation



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Re: [] Big Data Logic

John F Sowa — 2013-02-03T13:43:57

Thanks for those pointers.

Cascalog looks like a good adaptation of Datalog to Hadoop.

In the early 1980s, Ted Codd came across Prolog, and his immediate
reaction was "I wish I had invented that."

Datalog is essentially a subset of Prolog that is designed for
processing a database.  It has a much cleaner notation for logic
than the SQL WHERE clause or SPARQL.  It also avoids the nonlogical
features of NULL values in SQL or the filters of SPARQL.

If the DAML project had adopted Datalog as their primary notation
back in 2005, they would have a foundation with equal support for
relational and/or graph databases.  I believe it could have been
rapidly adopted by mainstream IT eight years ago.

People who don't know logic never liked Prolog.  They keep designing
rule-based languages with an English-like front end.  Back in the
1990s, Norbert Fuchs and his students developed ACE as an English-like
front end to Prolog.  Adapting ACE to Datalog or Cascalog is simple.

John

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Re: [] Big Data Logic

Jack Park — 2013-02-03T06:13:27

Two interesting links which appear to be related are these:
http://nathanmarz.com/blog/introducing-cascalog-a-clojure-based-query-language-for-hado.html
and
https://github.com/nathanmarz/cascalog

Jack

On Sat, Feb 2, 2013 at 8:09 AM, John F Sowa <sowa-pmV1UhJe4grR7s880joybQ< at >public.gmane.org> wrote:

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[] Big Data Logic

John F Sowa — 2013-02-02T16:09:19

Following is a slightly edited version of my response to a thread
on Ontolog Forum.

John Sowa

-------- Original Message --------
On 2/1/2013 3:49 PM, Barkmeyer, Edward J wrote:

I enjoyed the final comment:

Martin Weber

Re Big Data:  The following web site, devoted to data mining, asked the
readers to predict when the term 'Big Data' will fall out of fashion:

http://www.kdnuggets.com/2012/09/what-will-replace-big-data-when.html

The poll predicted 2014 as the median date.

If you change terminology fast enough, you get an illusion of progress.

John

-----Original Message-----
From: Weber, Martin S
Sent: Friday, February 01, 2013 2:46 PM
Subject: Big Data Logic Stack?

Last time, I mentioned that some big data stacks actually are now using 
logic representation and/or query languages.

Two examples for this:
a) the datomic database which uses a datom as the atomic unit of storage.

 From http://www.infoq.com/articles/Datomic-Information-Model :

The other part where logic comes in in 'big data' database stacks, is 
with Cascalog. I'm just reading a Big Data book which completely focuses 
on JCascalog (you might know it from Jena for instance) as the querying 
language. Datomic also uses cascalog as its native query mechanism 
(which doesn't have to be bound to the database at all, so you can do 
ad-hoc queries, too, using the cascalog logic in your business logic).

Cascalog in turns is an adoption of datalog, drawing from its prolog 
heritage.

So there you go, logic facts both at the datum level (in the case of
datomic) as well as on the query level (with cascalog).

State of the art: finally begin using yesterday's techniques.

Regards,
-Martin

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[] Relating Language to Perception, Action, and Feelings

John F Sowa — 2013-01-30T17:59:17

Following are the slides for the talk at ICCS:

    http://www.jfsowa.com/talks/relating.pdf

After the presentation, I made some major revisions.
See the outline below, which summarizes the changes.

John
_____________________________________________________

Relating Language to Perception, Action, and Feelings

by Arun K. Majumdar and John F. Sowa

  1. Neural foundations for language

     Two new slides, #7 and #17.

  2. Discrete and continuous representations

     Some minor revisions, but no new slides.

  3. Catastrophe theoretical semantics

     Major revisions and clarifications.  New sides #30, #42.

  4. Cognitive morphodynamics

     Major revisions and several new slides.

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[] The 3rd CUBIST Workshop CfP

Polovina, Simon — 2013-01-30T13:31:50

The 3rd CUBIST Workshop
In conjunction with ICFCA 2013 (21 - 24 May 2013, Dresden, Germany)

CUBIST (Combining and Uniting Business Intelligence with Semantic Technologies) is an EU-funded research project that investigates the combination of semantic technologies for harvesting and persisting data from a variety of data sources (both unstructured and structured) and FCA-based visual analytics for exploring and analysing the data in a meaningful way.

This workshop provides a forum for both research and practice for CUBIST-related research topics and technologies in order to facilitate interdisciplinary discussions. Related topics are:
* Business intelligence over unstructured and structured data
* Semantically enabled ETL processes
* Semantics of data cubes
* Triple stores as "information warehouses"
* Ontology-based data warehouse design
* Formal concept analysis for business intelligence
* Semantically enabled visual analytics
* Qualitative data analysis.

The proceedings will be published on-line (CEUR-proceedings).

Submission Procedure: Electronic version of full paper complete with authors' affiliations should be submitted through the conference electronic submission system.

Papers are limited to 10 pages in Springer's LNCS format and are to be submitted via EasyChair at www.easychair.org/conferences/?conf=cubistws13<http://www.easychair.org/conferences/?conf=cubistws13>

Important dates
Submission deadline: March 22, 2013
Reviews sent out: April 19, 2013
Final paper submission: May 3, 2013
Proceedings published: May 21, 2013

Manuscripts must be prepared with LaTeX or Microsoft Office and should follow the Springer format available at http://www.springer.de/comp/lncs/authors.html.

Simon

Dr. Simon Polovina
Senior Lecturer in Business Computing, Department of Computing
Principal Investigator: www.cubist-project.eu
Conceptual Structures Research Group, Communication and Computing Research Centre
Sheffield Hallam University, Cantor Building, 153 Arundel St, Sheffield, UK S1 2NU
Tel: +44 (0)114 225 6825; Web: www.polovina.me.uk


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[] Knowledge graphs

John F Sowa — 2013-01-19T20:51:42

Following is a slightly edited note that I sent to Ontolog Forum.

-------- Original Message --------
Subject: [ontolog-forum] Knowledge graphs by Google and Facebook
Date: Sat, 19 Jan 2013 10:46:30 -0500
From: John F Sowa

We have had some discussion about schema.org as a kind of minimal
ontology sponsored by Google, Bing, and Yahoo!  But there are much
larger ontology-like graphs that Google, Facebook, and others have
been developing.

Last May, Google announced their "Knowledge Graph", aspects of which
have been appearing on the right-hand sides of their search results.
Their catch phrase is "things, not strings":

http://googleblog.blogspot.co.uk/2012/05/introducing-knowledge-graph-things-not.html

In December, Google announced that their graph has grown from 3.5
billion "facts" to 18 billion facts in seven months.  But the number
of "things" mentioned in those facts grew at a slower pace --
from 500 million "objects" to 570 million "entities":

http://news.cnet.com/8301-1023_3-57557055-93/googles-knowledge-graph-tripled-in-size-in-seven-months/

Last week, Mark Zuckerberg introduced Facebook's Graph Search:

http://news.cnet.com/8301-1023_3-57564611-93/what-should-google-do-about-facebook-graph-search/

  From that article,

In logic, we would call those simple "filters" relations.  The advanced
"filters" are controlled English that could be translated to logical
expressions.

The Facebook graph is a giant graph DB, and their version of controlled
English is far more readable and writable than SQL or SPARQL.

Google's collection of documents is much, much larger and far less
structured than Facebook's graph.  It would be much harder to support
DB queries of the kind that Facebook processes.

However, Google maps does support some NL-like queries.  For example,
type "from grand central to penn station" to Google.  I was surprised
that Google's Knowledge Graph did not post any side information
about "grand central" or "penn station" as named entities.

Instead, the first hit was a USA Today site that gave directions
on how to go by subway or by taxi:

http://traveltips.usatoday.com/grand-central-station-penn-station-13435.html

Then I clicked on Google maps, which gave directions on how to go
by walking or by driving.  However, I doubt that most people who
might ask that question would have a car at GCT.

Then I tried Bing.com, for which the first hit was by ehow:

http://www.ehow.com/how_6163210_grand-penn-station-new-york.html

This page gave four options:  walking, taxi, subway, and bus.

Then I clicked on Bing Maps.  It asked a rather odd question:

When I clicked on #1, Bing told me that it would take 39 hours
and 39 minutes to drive from Grand Central *Market* in Glendale
to Penn Station in New York.

If you just type "grand central" to Bing, the first hit is
Grand Central Terminal in New York.  It also lists a more famous
Grand Central Market in downtown LA before the one in Glendale.
But Bing Maps seems to have different preferences from their
main search engine.

In any case, these examples show the amount and kind of background
knowledge that is needed to represent "common sense".  Even those
multi-billion dollar corporations have trouble finding and organizing
the information in a way that can answer "simple" questions.

John

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[] Fwd: Prolog+CG 2.0.16 released

John F Sowa — 2013-01-19T13:18:48

Forwarding

-------- Original Message --------
From: Ulrik Sandborg-Petersen <ulrikp-GBFWfhuOQpx/SzgSGea1oA< at >public.gmane.org>

Dear CG List,

As many of you know, I am the current maintainer of Adil Kabbaj's
Prolog+CG version 2.0.

I have just released version 2.0.16, with release notes below.  You can
download via:

http://prologpluscg.sourceforge.net/download.html

This release is the version Peter Øhrstrøm, Steinar Thorvaldsen, Thomas
Ploug, and I used for the experiments reported on at ICCS 2013.  I have
just not gotten around to releasing the code until now.

Best wishes,

Ulrik Sandborg-Petersen





Release notes for Prolog+CG

Release 2.0.16
==============

Changes over 2.0.15 include:

- The minimum required Java version is now 1.6, instead of 1.5.

- A bug was fixed in Concept.java.

- The primitive goal shuffle(L1,L2)" was added.  L1 must be a list,
   and L2 must be a free variable. If these conditions are satisfied,
   the goal always ends with success, and L2 is a permutation of L1,
   i.e., the order of L1's elements is shuffled.  L2 is a copy of L1.

- A problem was fixed on Mac OS X whereby the .dmg image might fail to
   open on Mac OS X 10.5 if it was created on Mac OS X 10.4.

- The Applet version used to have a problem by which it messed up the
   program's order totally when doing an asserta or assertz, since they
   did not result in a recompile of the program, as they should. This
   has been fixed.

- The Mac App bundle were updated to better reflect modern-day
   systems. The App bundle now runs on Mac OS X 10.6 (Snow Leopard)
   through 10.8 (Mountain Lion). Perhaps also 10.5, although this has
   not been tested.

- The Mac .dmg image now has a link to your Applications folder, and
   also hides all documentation in a Documentatiob subfolder.


Enjoy!

Ulrik Sandborg-Petersen




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