Copy Link
Add to Bookmark
Report
NL-KR Digest Volume 05 No. 27
NL-KR Digest (11/11/88 20:17:15) Volume 5 Number 27
Today's Topics:
Inherit through net
query on matching of knowledge representation structures
HPSG??
Machine Learning, K.R. and CogSci Grad programs?
ai colloquia
Generation and Recognition of Affixational Morphology (Unisys Seminar)
[mitch@chalet.aca.mcc.com (Linda Mitchell): Speaker Announcement]
From CSLI Calendar, November 10, 4:8
Visiting position in Natural Language Understanding
Submissions: NL-KR@CS.ROCHESTER.EDU
Requests, policy: NL-KR-REQUEST@CS.ROCHESTER.EDU
----------------------------------------------------------------------
Date: Thu, 3 Nov 88 11:27 EST
From: Siping Liu <siping@b.cs.wvu.wvnet.edu>
Subject: Inherit through net
In frame knowledge representation systems, knowledge
can be inherited through the tree-style world hierarchies.
i.e., each world has only one parent world.
The question is: if the intersection of the confined problem
spaces for two (or more) brother worlds is not empty, why can not
they have a common child world with the intersection as its
problem space ?
BTW, the question is raised when I am thinking how to fit ATMS
(Assumption-based Truth Maintenance System) into a frame system.
------------------------------
Date: Thu, 3 Nov 88 15:49 EST
From: LEWIS@cs.umass.EDU
Subject: query on matching of knowledge representation structures
Can anyone point me to some references on matching of subparts of
frame-based knowledge representation structures? Essentially what I'm
interested in is equivalent to finding some/all/the biggest of the
isomorphic subgraphs of two directed graphs, except that edges and vertices
are labeled, and there are restrictions on what labels are allowed to match.
For additional fun, there might be weights on the edges and vertices as
well, and you might not just be interested in large-sized isomorphic
subgraphs, but in maximal scoring ones.
Still more interesting would be if anything has been done on the case where
you can inferences to the structures before matching, so that you actually
have to search a space of alternative representations, as well as comparing
them.
Suggestions? If text content matching had been a bigger application of NLP
in the past, there'd be a bunch of stuff on this, but as it is, I suspect that
vision or case based reasoning people may have done more on this.
Best,
David D. Lewis ph. 413-545-0728
Computer and Information Science (COINS) Dept. BITNET: lewis@umass
University of Massachusetts, Amherst ARPA/MIL/CS/INTERnet:
Amherst, MA 01003 lewis@cs.umass.edu
USA
UUCP: ...!uunet!cs.umass.edu!lewis@uunet.uu.net
------------------------------
Date: Tue, 8 Nov 88 14:52 EST
From: James.Price.Salsman@cat.cmu.edu
Subject: HPSG??
Folks,
I've been folowing the discussion intently. I know what
GPSG is, but I have never come across HPSG -- could someone
give me a introductory and a difinative reverence?
Also, how are all of you production-based linguists doing
with the popularity surge in connectionist computation?
How do you account for the large amount of ungrammatical
conversation that takes place?
--
:James P. Salsman (jps@CAT.CMU.EDU)
------------------------------
Date: Tue, 8 Nov 88 15:57 EST
From: hadj@sbcs.sunysb.edu
Subject: Machine Learning, K.R. and CogSci Grad programs?
I am looking for computer science graduate programs which
are strong in the areas of Machine Learning and Knowledge
Representation. Also, programs in Cognitive Science are of
particular interest.
Please e-mail any suggestions, and I can post a summary.
Thanks in advance,
-mike hadjimichael. hadj@sbcs.sunysb.edu
{philabs, allegra}!sbcs!hadj hadj%sbcs.sunysb.edu@sbccvm.bitnet
< departmentofcomputersciencesunystonybrookstonybrooknyoneonesevenninefour >
------------------------------
Date: Thu, 3 Nov 88 14:35 EST
From: Steven Zenith <mcvax!inmos!zenith@uunet.UU.NET>
occam user group
* artificial intelligence *
special interest group
CALL FOR PAPERS
1st technical meeting of the OUG AISIG
ARTIFICIAL INTELLIGENCE
AND
COMMUNICATING PROCESS ARCHITECTURE
17th and 18th of July 1989, at Imperial College, London UK.
Keynote speakers will include
* Prof. Iann Barron *
"Inventor of the transputer"
The conference organising committee includes:
Dr.med.Ulrich Jobst Ostertal - Klinik fur Neurologie und
klinische Neurophysiologie
Dr. Heather Liddell, Queen Mary College, London.
Prof. Dr. Y. Paker, Polytechnic of Central London
Prof. Dr. L. F. Pau, Technical University of Denmark.
Prof. Dr. Bernd Radig, Institut Fur Informatik, Munchen.
Prof. Dr. David Warren Bristol University.
Conference chairmen:
Dr. Mike Reeve Imperial College, London
Steven Ericsson Zenith INMOS Limited, Bristol (Chairman OUG AISIG)
Topics include:
The transputer and a.i. Real time a.i
Applications for a.i. Implementation languages
Underlying kernel support Underlying infrastructure
Toolkits/environments Neural networks
Papers must be original and of high quality. Submitted papers
should be about 20 to 30 pages in length, double spaced and single
column, with an abstract of 200-300 words. All papers will be
refereed and will be assessed with regard to their quality and
relevance.
A volume is being planned to coincide with this conference to be
published by John Wiley and Sons as a part of their book series on
Communicating Process Architecture.
Papers must be submitted by the 1st of February 1988. Notification
of acceptance or rejection will be given by March 1st 1989.
Final papers (as camera ready copy) must be provided by April 1st
1989.
Submissions to be made to either:
Steven Ericsson Zenith Mike Reeve
INMOS Limited, Dept. of Computing,
1000 Aztec West, Imperial College,
Almondsbury, 180 Queens Gate,
Bristol BS12 4SQ, London SW7 2BZ,
UNITED KINGDOM. UNITED KINGDOM.
Tel. 0454 616616 x513 Tel. 01 589 5111 x5033
email: zenith@inmos.uucp email: mjr@doc.ic.ac.uk
Regional Organisers:
J.T Amenyo Ctr. Telecoms Research, Columbia University,
Rm 1220 S.W. Mudd, New York, NY 10027-6699.
Jean-Jacques Codani INRIA, Domaine de Voluceau - Rocquencourt,
B.P.105-78153 Le Chesnay Cedex, France.
Pasi Koikkalainen Lappeenranta University of Technology,
Information Technology Laboratory,
P.O.BOX 20, 53851 Lappeenrantra, Finland.
Kai Ming Shea Dept. of Computer Science,
University of Hong Kong, Hong Kong.
Dr. Peter Kacsuk Multilogic Computing, 11-1015 Budapest,
Csalogaiy u. 30-32. Hungary.
------------------------------
Date: Fri, 4 Nov 88 10:49 EST
From: Ron Loui <loui@wucs1.wustl.edu>
Subject: ai colloquia
COMPUTER SCIENCE COLLOQUIUM
Washington University
St. Louis
4 November 1988
TITLE: Why AI needs Connectionism? A Representation and Reasoning Perspective
Lokendra Shastri
Computer and Information Science Department
University of Pennsylvania
Any generalized notion of inference is intractable, yet we are capable of
drawing a variety of inferences with remarkable efficiency - often in a few
hundered milliseconds. These inferences are by no means trivial and support a
broad range of cognitive activity such as classifying and recognizing objects,
understanding spoken and written language, and performing commonsense
reasoning. Any serious attempt at understanding intelligence must provide a
detailed computational account of how such inferences may be drawn with
requisite efficiency. In this talk we describe some work within the
connectionist framework that attempts to offer such an account. We focus on
two connectionist knowledge representation and reasoning systems:
1) A connectionist semantic memory that computes optimal solutions to an
interesting class of inheritance and recognition problems extremely
fast - in time proportional to the depth of the conceptual hierarchy. In
addition to being efficient, the connectionist realization is based on an
evidential formulation and provides a principled treatment of exceptions,
conflicting multiple inheritance, as well as the best-match or
partial-match computation.
2) A connectionist system that represents knowledge in terms of multi-place
relations (n-ary predicates), and draws a limited class of inferences based on
this knowledge with extreme efficiency. The time taken by the system to draw
conclusions is proportional to the length of the proof, and hence,
optimal. The system incorporates a solution to the "variable binding" problem
and uses the temporal dimension to establish and maintain bindings.
We conclude that working within the connectionist framework is well motivated
as it helps in identifying interesting classes of limited inference that can
be performed with extreme efficiently, and aids in discovering constraints
that must be placed on the conceptual structure in order to achieve extreme
efficiency.
host: Ronald Loui
________________________________________________________________________________
1988-89 AI Colloquium Series (through February)
Sep 16 Michael Wellman, MIT/Air Force
"The Trade-off Formulation Task in Planning under
Uncertainty"
30 Kathryn Laskey, Decision Science Consortium
"Assumptions, Beliefs, and Probabilities"
Nov 4 Lokendra Shastri, University of Pennsylvania
"Why AI Needs Connectionism? A Representation and Reasoning
Perspective"
11 Peter Jackson, McDonnell Douglas
"Diagnosis, Defaults, and Abduction"
18 Eric Horvitz, Stanford University
Dec 2 Mark Drummond, NASA Ames
Feb 3 Fahiem Bacchus, University of Waterloo
10 Dana Nau, University of Maryland
________________________________________________________________________________
------------------------------
Date: Fri, 4 Nov 88 22:44 EST
From: finin@PRC.Unisys.COM
Subject: Generation and Recognition of Affixational Morphology (Unisys Seminar)
AI SEMINAR
UNISYS PAOLI RESEARCH CENTER
John Bear
SRI International
Generation and Recognition of Affixational Morphology
Koskenniemi's two-level morphological analysis system can be improved
upon by using a PATR-like unification grammar for handling the
morphosyntax instead of continuation classes, and by incorporating the
notion of negative rule feature into the phonological rule
interpreter. The resulting system can be made to do generation and
recognition using the same grammars.
1:00 am - November 7, 1988
R&D Conference Room
Unisys Paoli Research Center
Route 252 and Central Ave.
Paoli PA 19311
-- non-Unisys visitors who are interested in attending should --
-- send email to finin@prc.unisys.com or call 215-648-7446 --
------------------------------
Date: Wed, 9 Nov 88 09:50 EST
From: Kent Wittenburg <HI.WITTENBURG@MCC.COM>
Subject: [mitch@chalet.aca.mcc.com (Linda Mitchell): Speaker Announcement]
HUMAN INTERFACE LAB SEMINAR
John Bear, IBM Germany and SRI International
GENERATION AND RECOGNITION OF AFFIXATIONAL MORPHOLOGY
Abstract: A major contribution to computational morphology
in recent years has come from a two-level finite state ap-
proach to the analysis and generation of the morphology
of natural languages. The source for this approach is
Kimmo Koskenniemi's dissertation work in Finland. Many
others, including Lauri Karttunen, Ron Kaplan, and Mar-
tin Kay of Xerox PARC have elaborated on the original
model. The Kimmo approach is characterized by a phono-
logical rule component based on finite-state transduction
where lexical and surface levels represent the two tapes of
the transducer. A second level of information is mor-
phosyntactic information where, for example, one would state
that a language such as English allows plural affixes to
follow noun roots but not verbs. In the Kimmo model, mor-
phosyntactic information is stated as a set of continuation
classes, again a finite state model. In this talk it will
be argued that the morphosyntactic component is better
represented as a unification grammar. The particular imple-
mentation of the author's has used a unification grammar
for the morphosyntax component similar to the PATR
system developed at SRI. A second extension of the
author's to the original Kimmo system involves incor-
porating the negative rule features into the pho-
nological rule interpreter. The resulting system can be
made to do generation and recognition of words using the
same grammars.
Where: Microelectronics and Computer Technology Corporation
Balcones Research Center
3500 West Balcones Center Drive
HI Conference Room - 2.806
When: Friday, November 11, 1:30 P.M.
Host: Kent Wittenburg, Kent@mcc.com
------------------------------
Date: Thu, 10 Nov 88 11:38 EST
From: Emma Pease <emma@csli>
Subject: From CSLI Calendar, November 10, 4:8
NEXT WEEK'S TINLUNCH
Reading: "E-Type Pronouns in 1987"
by Irene Heim
Discussion led by Fernando Pereira
(pereira@ai.sri.com)
November 17
We will discuss Irene Heim's draft "E-Type pronouns in 1987." This
paper considers the question of whether there are good reasons to
prefer DRT or situation-theoretic treatments of bound anaphora to an
older approach, due to Evans, Cooper, and others, for which she coins
the term "E-type analysis." In an E-type analysis, a pronoun is
represented in LF as a term of the form f(v1,...,vn) where f is a
function made salient in the context and the vi are variables
associated to quantified expressions on which the pronoun depends.
Farmers, donkeys, paychecks, sage plants, spare pawns, and other
famous characters of semantics play excellent roles in a plot with
many unexpected turns.
____________
NEXT WEEK'S CSLI SEMINAR
The Resolution Problem for Natural-Language Processing
Weeks 8: Some Aspects of the Connectionist Approach
to Ambiguity Resolution
David Rumelhart
(der@psych.stanford.edu)
November 17
I will try to sketch the "connectionist program" for linguistic
information processing. In particular, I will challenge the idea of a
fixed lexicon and rather suggest how "word meanings" might be
"synthesized" as required by the contexts in which they occur. I will
offer slightly different instantiations of this idea---one of them
primarily due to Kowamoto and one due to McClelland and St. John. I
will also, time permitting, sketch the rather different connectionist
approach represented by the work of Gary Cottrel (among others).
____________
SYMBOLIC SYSTEMS FORUM
Logic and Information in Symbolic Systems
Jon Barwise and John Etchemendy
Friday, 11 November, 3:15
Sweet Hall, room 026 (basement)
Many cognitive scientists, though not all, take cognition to be
intrinsically symbolic. In particular, they view inference as symbol
manipulation. However, another view is that inference is the
extraction of information. How do these two views fit together?
The two of us are currently engaged in a project with SSP major
Alan Bush to build a computer system, Hyperproof, that allows the user
to reason by manipulating information, not symbols. The question is,
how can one get one's hands on information? To find out, come to our
talk.
Next week, 18 November, the Symbolic Systems Internship Forum will
be held: in it, each student and faculty sponsor will discuss how the
summer project went. This forum is open to the public and will be of
special interest to: (1) students interested in obtaining Symbolic
Systems Internships and (2) faculty interested in having interns.
------------------------------
Date: Tue, 8 Nov 88 13:37 EST
From: Graeme Hirst <gh@ai.toronto.edu>
Subject: Visiting position in Natural Language Understanding
VISITING POSITION IN NATURAL LANGUAGE UNDERSTANDING
UNIVERSITY OF TORONTO
ARTIFICIAL INTELLIGENCE GROUP
(DEPARTMENT OF COMPUTER SCIENCE)
A one-year visiting position, for a post-doc or more senior person, is
available for 1989-90 in the University of Toronto A.I. group in the
area of natural language understanding and computational linguistics.
The visitor would carry a 50% teaching load (one half-course per
semester), participate in the research group activities, and possibly
supervise MSc theses.
The Toronto AI group includes 7.5 faculty, 2 research scientists, and
approximately 40 graduate students. The natural language subgroup
includes one faculty member (Graeme Hirst) and about ten graduate
students and associates.
For more information, contact Graeme Hirst, preferably by e-mail.
Graeme Hirst
Department of Computer Science
University of Toronto
Toronto, CANADA M5S 1A4
E-mail: gh@ai.toronto.edu or .ca
gh@ai.utoronto.bitnet
Phone: 416-978-8747 (Tues, Thurs, Fri) or 416-284-3360 (Mon and Wed)
--
\\\\ Graeme Hirst University of Toronto Computer Science Department
//// uunet!utai!gh / gh@ai.toronto.edu / 416-978-8747
------------------------------
End of NL-KR Digest
*******************
