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NL-KR Digest Volume 15 No. 03
NL-KR Digest Mon Jan 22 07:56:08 PST 1996 Volume 15 No. 3
Today's Topics:
CFP: KR'96 Wkshp Relevance in KR and Reasoning, Nov 96, Boston
CFP: CONTEXT-97 Modeling and Using Context, Feb 97, Rio de Janeiro
Position: mathematical/computational linguists, Tuebingen
CFP: Data Mining and Knowledge Discovery, New Journal
Position: Post-doc in plan recognition, Monash
Announcement: TWLT11 Twente Wkshp Dialogue Mgmt., Jun 96, Enschede
* * *
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Date: Sun, 14 Jan 1996 19:51:41 -0500 (EST)
From: Russell Greiner <greiner@scr.siemens.com>
To: NCGUR@UCCMVSA.UCOP.EDU, Vision-List@TELEOSRESEARCH.COM,
Subject: CFP: KR'96 Wkshp Relevance in KR and Reasoning, Nov 96, Boston
KR'96 Pre-Conference Workshop on
Relevance in Knowledge Representation and Reasoning
3-4 November, 1996
Boston, Massachusetts
C A L L F O R P A P E R S
http://www.research.att.com/orgs/ssr/people/levy/rrr-cfp.html
Essentially all reasoning systems use a corpus of information to reach
appropriate conclusions. For example, deductive systems use initial
theories (possibly encoded as predicate calculus statements) from
which they draw conclusions, probabilistic systems use prior
distributions (possibly encoded as a Bayesian network) to compute
event probabilities, and abductive processes produce explanations
based on both background theories and observations.
With too little information, these systems clearly cannot work
correctly. Surprisingly, too *much* information is also problematic,
as it too can cause significant degradation in system performance. It
is therefore critical to determine what information is irrelevant, to
know what can be ignored or downplayed when considering a specific
task (e.g., a specific query, or distribution of queries, to the
system, or a specific observation to be explained). In some cases,
ignoring irrelevant information is needed in order to draw the correct
conclusions.
There are many forms of irrelevance. In some contexts, the initial
theory may include more information than the task requires, or
information at a level of granularity that is more detailed than
necessary. Here, the system may perform more effectively if it
ignores or deletes certain irrelevant facts or if it ignores certain
distinctions made in the representation. Another flavor of
irrelevance arises during the course of reasoning: A reasoning process
can ignore certain intermediate results, once it has established that
they will not contribute to the eventual answer.
This workshop follows the very eclectic 1994 Relevance Symposium,
which investigated the notion of relevance across various fields of
Artificial Intelligence and Computer Science. The current workshop,
however, will focus on the use of relevance in knowledge
representation and reasoning, specifically, on understanding different
forms of irrelevance, and exploiting this "relevance information" to
improve the performance of reasoning systems. Submissions are
requested in areas relating to relevance in KR&R, including, but not
limited to, the following:
o Speeding up inference using relevance reasoning.
o Relevance in probabilistic reasoning.
o Relevance in explanation.
o Relationships between relevance and belief revision and updates.
o Relevance reasoning as a basis for abstraction and reformulation.
o Using relevance of information to enable drawing appropriate
conclusions.
o Applications of relevance reasoning.
o Reasoning about relevance of information, and foundations of
relevance reasoning.
Submission Information
=====================
Authors wishing to present a paper should submit an extended abstract
of at most 5000 words. Accepted participants will be invited to
submit full papers for the workshop proceedings, which will be
distributed to the workshop participants. Persons wishing to attend
the workshop and not to present papers should submit a 1--2 page
research summary that includes a list of relevant publications.
Authors are encouraged to submit PostScript versions of their paper by
email to either Russ Greiner (greiner@scr.siemens.com) or Alon Levy
(levy@research.att.com). Authors unable to submit by email should send
4 copies of their paper to the address below. All submissions should be
received by July 8, 1996. Please be sure
to include e-mail address, telephone number and mailing address of
the principal author. In case of multiple authors, please indicate
which authors wish to participate. Notification of acceptance or
rejection will be mailed to the principal author by August 16, 1996.
Camera-ready copies of papers accepted for inclusion in the
proceedings will be due September 17, 1996.
Address for hardcopy submissions:
Russell Greiner
Siemens Corporate Research, Inc
755 College Road East
Princeton, NJ 08540-6632
Important Dates
==============
- Submissions due: July 8, 1996.
- Notification of acceptance August 16, 1996.
- Final version due September 17, 1996.
- Workshop dates November 3-4, 1996.
Program Chairs:
============== Russ Greiner (Siemens Corporate Research, greiner@scr.siemens.com)
Alon Levy (AT&T Bell Laboratories, levy@research.att.com)
Program Committee:
=================
Adnan Darwiche (Rockwell)
Jim Delgrande (Simon Frasier University)
Daphne Koller (Stanford University)
Gerhard Lakemeyer (University of Bonn)
Alberto Mendelzon (University of Toronto)
Devika Subramanian (Rice University)
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To: comp-ai-nlang-know-rep@moderators.univ-lyon1.fr
From: brezil@laforia.ibp.fr (Brezillon Patrick)
Subject: CFP: CONTEXT-97 Modeling and Using Context, Feb 97, Rio de Janeiro
Date: Mon, 15 Jan 1996 10:24:51 +0000
CALL FOR PAPERS
International and Interdisciplinary Conference
on Modeling and Using Context
(CONTEXT-97)
Rio de Janeiro (Brasil),
February 4-6, 1997
(a postscript version of the CFP is available at
www-laforia.ibp.fr and cdps.umcs.maine.edu/Context)
OBJECTIVE
The importance of the notion of context is now widely
acknowledged, as evidenced by the numerous workshops,
symposia and seminars on context held in 1995. The goal
of this conference is to bring together researchers
working on the notion of context from different points
of view and in a variety of disciplines.
In formal approaches, several formalizations of context
have been proposed.
In Computational Linguistics, context is a central notion
both to understand and produce text.
Knowledge-based systems now are designed and developed to
work collaborate with users in performing a task. This
shift in the expert-system paradigm implies that a system
must deal with notions as cooperation, explanation and
incremental knowledge acquisition. Context can thus play
an important role. Cognitive Scientists have long been
debating on the general meaning and the significance of
context in the environment. Cognitive systems engineering
has always recognised that cognition does not exist without
a context.
The use of context across domains implies that each
researcher may benefit of the experience of others. It is
hoped that this exchange of ideas will provide some answers
to questions that remain open.
TOPICS OF INTEREST
Formalization of context, Modeling of context, Descriptions
of context and analysis of influence on performance, Use of
context in: applications, artificial intelligence, cognitive
science, decision support systems, HCI, ITS,logic programming,
management, natural language, psychology, etc.
SCHEDULE:
Papers received: September 30th, 1996
Author notification: October 30th, 1996
Final papers received: December 1st, 1996
Conference: February 4-6, 1997
Participants will be selected on the basis of submitted
papers (10 pages maximum) by three referees at least.
Papers must include in the first page: title, author's
name(s), affiliation, complete mailing address, phone
number, fax number, e-mail, an abstract of 300 words
maximum, and up to five keywords. Submissions must be sent to
the Chairperson of the Programme Committee (at the address
given below) by surface mail (i.e., paper in four copies),
postscript version uuencoded, Word5.1 document attached to
an e-mail (via Eudora on Mac Intosh).
The Proceedings of the conference will be published by an
International Publisher.
WORKSHOP AND TUTORIAL PROPOSALS
According to proposals and the number of participants interested,
we may consider to have workshops and tutorials the two days
prior the conference. Please, contact the Chairperson of the
Programme Committee for more details and proposals.
STEERING COMMITTEE
Chandrasekaran B. (Ohio State Univ., USA)
Clancey W. (IRL, USA)
Giunchiglia F. (IRST, Italy)
Hayes P. (Beckman Institute, USA)
Lenat D. (MCC, USA)
Sowa J. (Binghamton Univ., USA)
Steels L. (V.U.B., Belgium)
PROGRAMME COMMITTEE (*: to be confirmed)
Abu-Hakima S. (NRC, Canada)
Akman V. (Bilkent Univ., Turkey)
Boy G. (Eurisco, France)
Breuker J. (Univ. of Amsterdam, The Netherlands)
Edmondson W. (Univ. of Birmingham, UK)
Ejkova I. (Russian Acad. of Sciences, Russia)
* Finin T. (Univ. of Maryland at Baltimore, USA)
* Gasser L. (Univ. of Southern California, USA)
Gilbert N.(Univ. of Surrey, UK)
Guha R. (USA)
* Hayes-Roth B. (Stanford Univ., USA)
* Hollender M. (Univ. of Kassel, Germany)
Hollnagel E. (OECD, Norway)
Hovy E. (USC/ISI, USA)
Humphreys P. (London School of Economics, UK)
Kodratoff Y. (Univ. of Paris 11, France)
Lefevre T. (AIT, Thailand)
Maybury M.T. (Mitre Corp., USA)
Mizoguchi R. (Osaka University, Japan)
* Moore J. (Univ. of Pittsburgh, USA)
Nardi B. (Apple Computer, USA)
* Neches R. (USC/ISI, USA)
Paris C. (Univ. of Brighton, UK)
Paton R. (Univ. of Liverpool, UK)
Pomerol J.-Ch. (Univ. Paris 6, France)
Serafini L. (IRST, Italy)
Suthers D. (Univ. of Pittsburgh, USA)
Turner R. (Univ. of Maine, USA)
* Van Hentenrick P. (Brown University, USA)
Young R. (North Carolina State Univ., USA)
* Zukerman I. (Monash Univ., Australia)
ORGANIZATION COMMITTEE
Cavalcanti Marcos (Univ. of Rio de Janeiro, Brasil)
Naveiro Ricardo (COPPE, Brasil)
Chair of the Programme Committee:
Brezillon Patrick
LAFORIA-IBP, Box 169,
University Paris VI,
4, Place Jussieu
F-75252 PARIS Cedex 05
France
Tel: (33 1) 44 27 70 08
Fax: (33 1) 44 27 70 00
E-mail: brezil@laforia.ibp.fr
Chair of the Organization Committee:
Cavalcanti Marcos
COPPE/UFRJ (F109)
CP 68507
21945-970 Rio de Janeiro
Brazil
Tel/Fax: (+55 21) 590-8817
Email : marcos@pep.ufrj.br
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To: comp-ai-nlang-know-rep@uunet.uu.net
From: tg@arbuckle.sfs.nphil.uni-tuebingen.de (Thilo Goetz)
Subject: Position: mathematical/computational linguists, Tuebingen
Date: 15 Jan 1996 12:20:17 GMT
The Division of Computational Linguistics in the Dept. of
Linguistics at the University of Tuebingen, Germany is
searching for a
1. a computational linguist with research experience in the
implementation of constraint-based grammar formalisms,
particularly of HPSG. Programming experience in Prolog is
required.
2. a mathematical/computational linguist or computer
scientist with research experience in feature logics and the
mathematical foundations of logic programming.
The successful candidates would be expected to take up their
positions as soon as possible. The positions are at the rank of
"Wissenschaftlicher Mitarbeiter" (salary on the German
payscale of BAT IIa; minimum of 70 000 DM per year).
The initial contract would be until December 31st, 1996, with
the possibility of renewal for maximally five years.
Applications should include CV and an outline of research
experience and interests. Names and addresses of references
would be helpful. Applications should be sent by mail or
email to the address below.
Applications received by February 2nd, 1996 will receive full
consideration.
Prof. Erhard W. Hinrichs
Seminar fuer Sprachwissenschaft, Abt. Computerlinguistik
Eberhard-Karls Universitaet Tuebingen
Kleine Wilhelmstr. 113
D-72074 Tuebingen, Germany
hinrichs@sfs.nphil.uni-tuebingen.de
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Date: Mon, 15 Jan 96 13:34:11 PST
From: datamine@aig.jpl.nasa.gov (Data Mining Journal)
To: nl-kr@snyside.sunnyside.com
Subject: CFP: Data Mining and Knowledge Discovery, New Journal
New Journal Announcement:
Data Mining and Knowledge Discovery
an international journal
http://www.research.microsoft.com/research/datamine/
Published by Kluwer Academic Publishers
Advances in data gathering, storage, and distribution technologies have far
outpaced computational advances in techniques for analyzing and understanding
data. This created an urgent need for a new generation of tools and
techniques for automated Data Mining and Knowledge Discovery in Databases
(KDD). KDD is a broad area that integrates methods from several fields
including statistics, databases, AI, machine learning, pattern recognition,
machine discovery, uncertainty modeling, data visualization, high performance
computing, management information systems (MIS), and knowledge-based systems.
KDD refers to a multi-step process that can be highly interactive and
iterative. It includes data selection/sampling, preprocessing and
transformation for subsequent steps. Data mining algorithms are then used
to discover patterns, clusters and models from data. These patterns and
hypotheses are then rendered in operational forms that are easy for people
to visualize and understand. Data mining is a step in the overall KDD
process. However, most published work has focused solely on
(semi-)automated data mining methods. By including data mining explicitly
in the name of the journal, we hope to emphasize its role, and build bridges
to communities working solely on data mining.
Our goal is to make Data Mining and Knowledge Discovery a flagship journal
publication in the KDD area, providing a unified forum for the KDD research
community, whose publications are currently scattered among many different
journals. The journal will publish state-of-the-art papers in both the
research and practice of KDD, surveys of important techniques from related
fields, and application papers of general interest. In addition, there will
be a pragmatic section including short application reports (1-3 pages), book
and system reviews, and relevant product announcements.
Please visit the journal's WWW homepage at:
http://www.research.microsoft.com/research/datamine/
to obtain further information, including:
- A list of topics of interest,
- full call for papers,
- instructions for submission,
- contact information, subscription information, and
- ordering a free sample issue.
Editors-in-Chief: Usama M. Fayyad
================ Jet Propulsion Laboratory,
California Institute of Technology, USA
Heikki Mannila
University of Helsinki, Finland
Gregory Piatetsky-Shapiro
GTE Laboratories, USA
Editorial Board:
============== Rakesh Agrawal (IBM Almaden Research Center, USA)
Tej Anand (AT&T Global Information Solutions, USA)
Ron Brachman (AT&T Bell Laboratories, USA)
Wray Buntine (Thinkbank Inc, USA)
Peter Cheeseman (NASA AMES Research Center, USA)
Greg Cooper (University of Pittsburgh, USA)
Bruce Croft (University of Mass. Amherst, USA)
Dan Druker (Arbor Software, USA)
Saso Dzeroski (Jozef Stefan Institute, Slovenia)
Oren Etzioni (University of Washington, USA)
Jerome Friedman (Stanford University, USA)
Brian Gaines (University of Calgary, Canada)
Clark Glymour (Carnegie-Mellon University, USA)
Jim Gray (Microsoft Research, USA)
Georges Grinstein (University of Lowell, USA)
Jiawei Han (Simon Fraser University, Canada)
David Hand (Open University, UK)
Trevor Hastie (Stanford University, USA)
David Heckerman (Microsoft Research, USA)
Se June Hong (IBM T.J. Watson Research Center, USA)
Thomasz Imielinski (Rutgers University, USA)
Larry Jackel (AT&T Bell Labs, USA)
Larry Kerschberg (George Mason University, USA)
Willi Kloesgen (GMD, Germany)
Yves Kodratoff (Lab. de Recherche Informatique, France)
Pat Langley (ISLE/Stanford University, USA)
Tsau Lin (San Jose State University, USA)
David Madigan (University of Washington, USA)
Ami Motro (George Mason University, USA)
Shojiro Nishio (Osaka University, Japan)
Judea Pearl (University of California, Los Angeles, USA)
Ed Pednault (AT&T Bell Laboratories, USA)
Daryl Pregibon (AT&T Bell Laboratories, USA)
J. Ross Quinlan (University of Sydney, Australia)
Jude Shavlik (University of Wisconsin - Madison, USA)
Arno Siebes (CWI, Netherlands)
Evangelos Simoudis (IBM Almaden Research Center, USA)
Andrzej Skowron (University of Warsaw, Poland)
Padhraic Smyth (Jet Propulsion Laboratory, USA)
Salvatore Stolfo (Columbia University, USA)
Alex Tuzhilin (NYU Stern School, USA)
Ramasamy Uthurusamy (General Motors Research Laboratories, USA)
Vladimir Vapnik (AT&T Bell Labs, USA)
Ronald Yager (Iona College, USA)
Xindong Wu (Monash University, Australia)
Wojciech Ziarko (University of Regina, Canada)
Jan Zytkow (Wichita State University, USA)
If you would like to receive information from Kluwer on this journal,
and to receive a free sample issue by mail, please fill out the
form attached below, and e-mail it to datamine@aig.jpl.nasa.gov
Please use the following in SUBJECT field: REQUEST for SAMPLE J-DMKD
... Please do NOT remove keywords following '___', simply fill in provided
... fields and return as is. This form will be processed automatically.
... If you do not wish to complete a field, please LEAVE BLANK.
... Subject should be: REQUEST for SAMPLE J-DMK
... mail completed form, including keywords in CAPS to
... datamine@aig.jpl.nasa.gov
...
___ REQUEST FOR FREE SAMPLE ISSUE OF DATA MINING AND KNOWLEDGE DISCOVERY
___
___ NAME:
___ EMAIL:
___ AFFILIATION:
___ POSTAL_ADDRESS_LINE1:
___ POSTAL_ADDRESS_LINE2:
___ POSTAL_ADDRESS_LINE3:
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___ CITY:
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___ END_FORM: do not edit this line, anything below it is discarded.
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Date: Wed, 17 Jan 1996 09:34:53 +0000 (GMT)
From: ingrid@bruce.cs.monash.edu.au (Ingrid Zukerman)
Subject: Position: Post-doc in plan recognition, Monash
To: comp-ai-nlang-know-rep@uunet.uu.net
Postdoctoral position in Plan Recognition
Monash University
(Melbourne, Australia)
Project Description
-------------------
In this project we propose to design and implement a system for
performing plan recognition in realistic domains. To this effect, we
propose to consider two separate but inter-related aspects of plan
recognition: (1) modeling dynamic, complex domains; and (2) designing
and implementing algorithms for performing plan recognition using
these domain models. In addition, we propose to de-couple the plan
recognition mechanism from the objective of the system. This will
support the construction of agents that apply their plan recognition
skills to achieve different objectives, e.g., helping or hindering a
user, or simply achieving their own goals.
The lack of a concise representation of the domain implies that it is
not feasible to hand-code such a representation. Hence, the envisioned
system must apply machine learning techniques to encode the domain
knowledge. The use of these techniques will also support adaptive
behaviour, which is required to model a dynamic domain. The system
will receive as input logs of actions performed by the users of the
system, and also partial observations of the state which include
information about the objective(s) eventually attained by these
users. The output will be a representation of sequences and/or sets of
actions which usually lead to different goals in the domain. This
representation will reflect the actions commonly performed by users
and the goals that are commonly attained, rather than a mathematical
and complete relation between actions and goals. Hence, this
representation is particularly suitable for plan recognition.
The features of the domains at hand indicate that these domains must
be modeled by means of a probabilistic mechanism that is capable of
representing hidden states, such as Hidden Markov Models (HMMs) or
Probabilistic Recursive Transition Networks (PRTNs). HMMs have been
recently used in machine translation and speech
understanding. However, they lack the expressive power of PRTNs, which
are required in order to encode Probabilistic Context Free
Grammars. In this project, we intend to investigate formalisms of this
class, and to design and implement inductive learning algorithms for
the selected formalism.
Most plan recognition mechanisms developed to date perform forward
chaining of plan operators. This inference process is not suitable for
the domains at hand, where plan operators alone are not sufficient to
model the domain adequately. Thus, plan recognition algorithms which
can use the domain models in this project will be developed. It is
envisioned that these mechanisms will take into consideration the
extent to which the observed actions match the Markov Models or PRTNs
generated in the domain modeling stage. The predictive power of these
algorithms will be tested by evaluating the accuracy of the goals they
predict at different points in the sequences of actions performed by
users of the system. At a later stage, these algorithms will be
incorporated into intelligent agents which can either assist a user,
hinder the user or execute plans of their own.
Requirements
------------
The suitable applicant should have a solid mathematical background, be
proficient in inductive learning techniques, and know C and
Lisp. Knowledge of plan recognition techniques is desirable.
Conditions
----------
Position: Research Fellow, Level A.
Salary range: AUS$37,345-$40,087.
Length of contract: initial appointment for 1 or 2 years,
renewable for up to 3 years.
Funding source: Australian Research Council
Start of contract: March 1, 1996 (or as soon as possible after that date)
The City of Melbourne
---------------------
Melbourne is a city of about 3 million people, many of whom have come
from other countries, giving the city a distinctive cosmopolitan
character. The climate is temperate, with typical daily maximum
temperatures ranging from a winter low of about 13C to a summer high
of around 35C. The metropolitan area of Melbourne is served by a
generally acceptable public transport network of trains, trams and
buses.
The Department of Computer Science at Monash University
-------------------------------------------------------
The Department of Computer Science at Monash University (Clayton
Campus) is part of the Faculty of Computing and Information
Technology, which is the largest computing education organization in
Australia, with more than 3000 students, and about 100 academic and 30
support staff in eight departments.
Monash University's Clayton campus is located on a spacious (101
hectare) landscaped site in the suburb of Clayton, 20 Km. south-east
of the central business district of Melbourne.
Enquiries
---------
Enquiries may be made by email to ingrid@cs.monash.edu.au or
annn@cs.monash.edu.au.
Applications
------------
Deadline for applications is February 1st or until position is filled.
Applicants should send a curriculum vitae, including the names of at
least two references, by e-mail to ingrid@cs.monash.edu.au or
annn@cs.monash.edu.au. If e-mail is impossible, hard-copies may be
mailed to:
Ingrid Zukerman or Ann Nicholson
Department of Computer Science
Monash University
Clayton, VICTORIA 3168
AUSTRALIA
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To: comp-ai-nlang-know-rep@uunet.uu.net
From: a.nijholt@pi.net
Subject: Announcement: TWLT11 Twente Wkshp Dialogue Mgmt., Jun 96, Enschede
Date: Sun, 21 Jan 96 14:32:26 PDT
FIRST ANNOUNCEMENT
Twente Workshop on Language Technology 11
Dialogue Management in Natural Language Systems
June 19-21, 1996
Twente University of Technology
Enschede, the Netherlands
Organizers:
S. Luperfoy (MITRE)
G. Veldhijzen van Zanten (IPO)
J. Schaake (Twente)
H. Bunt (ITK)
A. Nijholt (Twente)
Aims of TWLT11
The theme of TWLT 11 is dialogue management. Why do
we want to organize a workshop on this particular theme?
We feel that dialogue management is a key issue in natural
language information systems. In the past many attempts
have been made to develop natural language interfaces to
computer systems. These systems tried to completely
understand and disambiguate the user's utterances and act
upon the wishes that the user expressed. It turned out,
however, that complete understanding and disambiguating
of natural language utterances is a extremely complex
tasks and it is doubtful if even humans can do it. Therefore,
currently, natural language systems are built that are less
ambitious on the linguistic side, but compensate for this by
engaging in a dialogue. This way, the system can ask the
user for help in the understanding and disambiguation of
that which he or she intended to convey. The management
of such a dialogue, however, is not a trivial problem.
Several important questions come to mind: how can we
monitor whether the dialogue is progressing efficiently?
How much and what kind of feedback should the system
give on what it has understood so far? When? How can the
dialogue be controlled? What is the role of initiative in
dialogues? These and many more issues must be
addressed before we can hope to produce dialogue
systems that operate in way that is acceptable to a large
class of users. Therefore, dialogue management in natural
language systems is an important scientific and
technological issue.
Several internationally well known researchers will be asked
to present their research during this workshop. The papers
presented at this workshop will become part of proceedings
which will be available during the workshop. Presentation of
papers is by invitation only. Contact anijholt@cs.utwente.nl.
Preliminary (incomplete) list of invited speakers TWLT11
Jan Alexandersson (Germany) Anders Baekaard (Danmark)
Robbert-Jan Beun (Neths) Harry Bunt (Neths)
Jennifer Chu Carrol (USA) Wieland Eckert (Germany)
Elizabeth Hinkelman (Germany) Susann Luperfoy (USA)
Elisabeth Maier (Germany) David Novick (USA)
Parlevink (Neths) Latifa Taleb (France)
David Traum (Switzerland) Gert Veldh.v.Zanten (Neths)
Anne Vilnat (France) Wayne Ward (USA)
Sandra Williams (GB)
Participation and Registration
To register send a note to the organizing secretariat. Email
is preferred. In the next months WWW-pages will be
provided with more information about program, registration
and participation. The regular registration fee is Dfl.
300,-.
This includes lunches, proceedings, refreshments during
the breaks and an informal reception. Please register
before May 20. For more information contact the workshop
organizing secretariat, mrs. Alice Hoogvliet-Havercate:
hoogvlie@cs.utwente.nl.
End of NL-KR Digest
*******************
