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Re: [ontolog-forum] FW: FW: CfP 11/16/2015: Knowledge-Based AI Track at

To: "[ontolog-forum]" <ontolog-forum@xxxxxxxxxxxxxxxx>
From: Thomas Johnston <tmj44p@xxxxxxx>
Date: Sat, 19 Sep 2015 16:05:30 +0000 (UTC)
Message-id: <292119333.193930.1442678730134.JavaMail.yahoo@xxxxxxxxxxxxxx>
OK Leo. Here's my re-post, to the forum, of what I've posted earlier to you. 

For others, the topic I'm concerned with in these postings is lexical semantics -- the semantics of sub-sentential expressions. Also, I have begun reprising some of my ancient notes on this topic, and they may be difficult to follow because over three decades of work in lexical semantics have taken place since I wrote them. And so there may be terminology I use that needs clarification. Also, my current research in this field is at a rudimentary level, and so there may be developments that, once I am aware of them, will point out the error of my ways.

Contributions from others in this forum with interests in lexical semantics are most welcome.

And so, what I wrote earlier was this:

-----
Leo,

Thank you for the overview of distributional semantics which, in fact, I was unaware of. Also for the references you provide. 

The first thing that comes to mind is that the lexical use patterns which these statistical techniques will certainly reveal / have revealed need a theory, an explanation. Recently, I have gone back to fairly extensive unpublished material which I wrote in the 70's and 80's. Combining it with my current research and notes, I have a corpus of work which I provisionally think might form the basis of such a theory. 

Currently, I'm trying to figure out how much of Gardenfors' new book, The Geometry of Meaning, has already anticipated my work on such a theory. Unless you have already concluded (as I nearly have) that his conceptual spaces won't carry all the weight he puts on them, you might find this book of his interesting.

I learned my compositionality lessons from Jerry Fodor's extended development and defense of the Language of Thought. But what still fascinates me is the psychological phenomenon of a child's progression from pointing and naming to his construction of elementary sentences. It seems to me to be one of the miracles/mysteries of human intellectual achievement. I look forward to an ANN account of compositionality, from which point of view Fodor's symbol-based LOT will be seen as an abstract description of what neural networks do, and which will begin the process of removing the mystery from this miracle.

But the semantic forces which account for the statistical patterns discussed in your references are still what interest me the most. I can get into the literature starting from those references, of course; but if there is anything else you know of that is specifically concerned with a theory of lexical meaning (and lexical meaning change), please let me know.

Thanks once again.

Tom

-----

(There is one more catch-up post I will publish to the forum, and then we're all starting from the same page.)




On Friday, September 18, 2015 7:50 PM, "Obrst, Leo J." <lobrst@xxxxxxxxx> wrote:


Thomas,
 
[I originally posted this just to you, but we have agreed to share our exchange and invite others into the discussion.]
 
As you undoubtedly know, recently there’s has been the emergence of so-called “distributional semantics” these days in computational linguistics/NLP. This is based on corpus linguistics, i.e., large-scale statistical, but light-weight “knowledge-based” or formal linguistic/semantic methods.
 
Distributional semantics:  words as “meaning” the contexts/collocations they can occur in, what I consider kind of Witgenstein 2 (Investigations, not Tractatus) in nature.
 
Some folks are trying to combine distributional semantics with more formal compositional semantics, the latter of which has not focused primarily on lexical semantics, but rather on the composition of words into higher forms and their semantic  interpretations, i.e., going back to Montague in the late 1960s.  E.g.,  see [1, 2]. Also, for a good overview of lexical theories, see [3]. For a new type-based approach, see [4].
 
However, there are potentially some useful emerging approaches in ontology research, i.e., quality (or value) spaces, and so-called semantic reference spaces/ranges, especially [5-6]. We are using this in our current clinical care healthcare ontology research (forthcoming), which can combine quantitative and qualitative quality value spaces, so that, e.g., nominal qualities (“named” qualities; think of “low/medium/high X”) can be mapped into a quantitative range, though imprecisely, given that you have some ordering on the regions. I am myself thinking of something similar to this for so-called “semantic fields”, i.e., that one can begin to think of these spaces and their points/regions as “drifting” over time.
 
Thanks,
Leo
 
[1] Lewis, M., & Steedman, M. 2013. Combining Distributional and Logical Semantics. Transactions of the Association for Computational Linguistics, 1, 179-192. https://tacl2013.cs.columbia.edu/ojs/index.php/tacl/article/view/93.
[2] Baroni, M., Bernardi, R., & Zamparelli, R. 2014. Frege in space: A program of compositional distributional semantics. Linguistic Issues in Language Technology, 9. http://csli-lilt.stanford.edu/ojs/index.php/LiLT/article/download/6/5.
[3] Geeraerts, Dirk. 2009. Theories of Lexical Semantics. Oxford University Press.
[4] Asher, Nicholas. 2011.  Lexical Meaning in Context: A Web of Words. Cambridge: Cambridge University Press. 2011.
[5] Probst, F. 2007. Semantic Reference Systems for Observations and Measurements. PhD dissertation, U. Muenster, Germany. http://ifgi.uni-muenster.de/~probsfl/publications/PROBST-Thesis-SemanticReferenceSystemsForObservationsAndMeasurements.pdf.
[6] Probst, F. 2008.  Observations, measurements and semantic reference spaces. Applied Ontology 3 (2008) 63-89.
 
 
 
From: ontolog-forum-bounces@xxxxxxxxxxxxxxxx [mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx] On Behalf Of Thomas Johnston
Sent: Tuesday, September 15, 2015 11:42 PM
To: [ontolog-forum] <ontolog-forum@xxxxxxxxxxxxxxxx>
Subject: Re: [ontolog-forum] FW: CfP 11/16/2015: Knowledge-Based AI Track at 2016 FLAIRS
 
Leo,
 
The description of knowledge-based vs "statistics"-based AI is an entry point into so much that I am interested in. Perhaps the distinction will eventually cease to be a distinction between the association of ontologies with the former but not with the latter. Perhaps the distinction will eventually become one between software systems which are given human-developed ontologies, and software systems which abstract their own ontologies from the patterns they discover by naming those patterns and then developing additional patterns by playing with set-theoretic quasi-random combinations of those named patterns.
 
And the way we play these set-theoretic games in our heads, I have suspected for a long time, is by means of background processes in which Venn-diagram-like representations of those labelled patterns are what is actually manipulated, at close to the neural level. (This is a bit like Gardenfors, but also quite a bit unlike him.)
 
I suspect this is far too brief, and also far too off the beaten academic path, to be more than vaguely suggestive, if even that. The interests that it hints at are (i) my interest in lexical semantics, vs. what I see as a one-sided concentration on the semantics of statements on the part of philosophers especially; and (ii) my interest in diachronic semantics, i.e. in how the semantic web that is embodied in the neurochemical web of our brains evolves over time, as it obviously does.
 
I'm tempted to just erase this. But I feel among friends here, and so I've decided that it doesn't matter if this sounds foolish. And if there are others here to whom this is not completely non-sensical, I'd enjoy hearing from you, and especially hearing about the "core bibliographies" relevant to this stuff that you are currently working with.
 
Regards,
 
Tom 
 
 
On Tuesday, September 15, 2015 12:27 AM, "Obrst, Leo J." <lobrst@xxxxxxxxx> wrote:
 
 
FYI.
 
-----Original Message-----
From: Christian Hempelmann [mailto:C.Hempelmann@xxxxxxxxx]
 
FLAIRS Knowledge-Based AI Track
 
Special Track at FLAIRS-29, Key Largo, Florida USA
 
In cooperation with the Association for the Advancement of Artificial
Intelligence
 
Key Largo, Florida, USA
May 16 - 18, 2016
 
Paper submission deadline: November 16, 2015.
Notifications: January 18, 2016.
 
Camera-ready version due: February 22, 2016.
 
All accepted papers will be published as FLAIRS proceedings by the AAAI.
 
Call for Papers
 
What is Knowledge-Based AI?
After an early dominance in AI, especially in NLP, approaches based on
engineered knowledge-resources such as rule bases and ontologies modeling
(part of) the world, the statistical winter set in in the 1980s. Fueled by
increased computing power, statistics-based replacements for modeling the
world, including machine-learning and neural networks, lead to early
successes before they hit their ceiling and resulted in algorithmic arms
races. To get AI out of these trenches and back into mobile warfare,
knowledge-based methods have not only been being paid  lipservice to in
the many "semantic" revolutions, but actual applications have been built,
often with complementary methodologies that paired statistical and
knowledge-based solutions.
The scope of the track includes research, proof-of-concept and industry
applications in the area of knowledge-based AI, i.e. systems whose
functionality is informed by computational knowledge resources
(ontologies, lexicons, semantic networks and/or knowledge bases). While
the knowledge-based AI is often juxtaposed to the statistics-based AI, we
see the contrast as unnecessarily exclusionary, in that systems combining
the intuitive directness of knowledge representation with the efficiency
of statistics-based computation have distinct advantages.
 
What is the GOAL of the track?
To showcase recent knowledge-based theories, methodologies, and
applications in AI and to foster new approaches of this kind, also those
paired with statistical and machine-learning approaches.
 
Who might be interested?
The scope of the track includes research, proof-of-concept and industry
applications in the area of knowledge-based AI, i.e. systems whose
functionality is informed by computational knowledge resources
(ontologies, lexicons, semantic networks and/or knowledge bases). While
the knowledge-based AI is often juxtaposed to the statistics-based AI, we
see the contrast as unnecessarily exclusionary, in that systems combining
the intuitive directness of knowledge representation with the efficiency
of statistical approximation have distinct advantages.
What kind of studies will be of interest?
Papers and contributions are encouraged for any work relating to
Knowledge-Based AI. Topics of interest may include (but are in no way
limited to):
              € ontologies
              € spreading activation networks
              € lexicon acquisition
              € knowledge integration
              € applications in knowledge-based AI
              € hybrid probabilistic/machine-learning & knowledge-based systems
Note: We invite original papers (i.e. work not previously submitted, in
submission, or to be submitted to another conference during the reviewing
process).
 
Submission Guidelines
Interested authors should format their papers according to AAAI formatting
guidelines. The papers should be original work (i.e., not submitted, in
submission, or submitted to another conference while in review). Papers
should not exceed 6 pages (4 pages for a poster) and are due by November
16, 2015. For FLAIRS-29, the 2016 conference, the reviewing is a double
blind process. Fake author names and affiliations must be used on
submitted papers to provide double-blind reviewing. Papers must be
submittcoued as PDF through the EasyChair conference system, which can be
accessed through the main conference web site
(http://www.flairs-29.info/). Note: do not use a fake name for your
EasyChair login - your EasyChair account information is hidden from
reviewers. Authors should indicate the [your track name] special track for
submissions. The proceedings of FLAIRS will be published by the AAAI.
Authors of accepted papers will be required to sign a form transferring
copyright of their contribution to AAAI. FLAIRS requires that there be at
least one full author registration per paper.
Please, check the website http://www.flairs-29.info/ for further
information.
 
Conference Proceedings
Papers will be refereed and all accepted papers will appear in the
conference proceedings, which will be published by AAAI Press.
 
Organizing Committee
              € Christian F. Hempelmann, Texas A&M University-Commerce,
              € Gavin Matthews, NTENT.com,
              € Max Petrenko, NTENT.com,
 
Program Committee
              € Christian F. Hempelmann, Texas A&M University-Commerce,
              € Elena Kozerenko, Russian Academy of Sciences,
              € Gavin Matthews, NTENT.com,
              € Leo Obrst, MITRE,
              € Max Petrenko, NTENT.com,
              € Victor Raskin, Purdue University,
              € Julia M. Taylor, Purdue University,
              € Tony Veale, University College Dublin,
              € Yorick Wilks, University of Sheffield & IHMC, Florida,
              € Michael Witbrock, VP for Research, Cycorp.
 
Further Information
Questions regarding the Knowledge-Based AI Special Track should be
addressed to the track co-chairs:
              € Christian F. Hempelmann, Texas A&M University-Commerce,
              € Gavin Matthews, NTENT.com, gmatthews@xxxxxxxxx
              € Max Petrenko, NTENT.com, mpetrenko@xxxxxxxxx
 
Questions regarding Special Tracks should be addressed to Zdravko Markov,
Conference Chair: William (Bill) Eberle, Tennessee Technological
University, USA (WEberle@xxxxxxxxxx)
Program Co-Chairs: Zdravko Markov, Central Connecticut State University,
Ingrid Russell, University of Hartford, USA (irussell@xxxxxxxxxxxx)
Special Tracks Coordinator: Vasile Rus, The University of Memphis, USA
 
Conference Web Sites
Paper submission site: follow the link for submissions at
FLAIRS-29 conference web page: http://www.flairs-29.info/
Florida AI Research Society (FLAIRS): http://www.flairs.com
 
Christian F. Hempelmann, PhD | Assistant Professor of Computational
Linguistics
Department of Literature and Languages
Texas A&M University-Commerce
P.O. Box 3011 | Commerce, TX 75429-3011
Tel. 903.468.5291 | Fax: 903.886.5980 | www.tamuc.edu
The Texas A&M University System
 
_______________________________________________
Dr. Leo Obrst                The MITRE Corporation, Information Semantics
lobrst@xxxxxxxxx        Cognitive Science & Artificial Intelligence, CCG
Voice: 703-983-6770  7515 Colshire Drive, M/S H317
Fax: 703-983-1379      McLean, VA 22102-7508, USA
 
 


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