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Neuron Digest Volume 13 Number 11
Neuron Digest Monday, 7 Mar 1994 Volume 13 : Issue 11
Today's Topics:
Human Memory: BBS Call for Commentators
Neural Computation BibTeX database available
donations to bibliography server
FUZZY + Neural nets?
ANNs for market prediction
CMU-Pitt Center for the Neural Basis of Cognition
PhD and Masters Programs at the Oregon Graduate Institute
UK PhD studentships at Leeds, England
papers on time and neural networks
JAIR article
Shakespeare and Neural Nets
Send submissions, questions, address maintenance, and requests for old
issues to "neuron-request@psych.upenn.edu". The ftp archives are
available from psych.upenn.edu (130.91.68.31) in pub/Neuron-Digest or by
sending a message to "archive-server@psych.upenn.edu".
----------------------------------------------------------------------
Subject: Human Memory: BBS Call for Commentators
From: Stevan Harnad <harnad@Princeton.EDU>
Date: Mon, 31 Jan 1994 20:52:35 -0500
Below is the abstract of a forthcoming target article by:
MS Humphreys, J Wiles & S Dennis
on:
TOWARD A THEORY OF HUMAN MEMORY: DATA STRUCTURES AND ACCESS PROCESSES
This article has been accepted for publication in Behavioral and Brain
Sciences (BBS), an international, interdisciplinary journal providing
Open Peer Commentary on important and controversial current research in
the biobehavioral and cognitive sciences.
Commentators must be current BBS Associates or nominated by a current
BBS Associate. To be considered as a commentator for this article, to
suggest other appropriate commentators, or for information about how to
become a BBS Associate, please send email to:
harnad@clarity.princeton.edu or harnad@pucc.bitnet or write to:
BBS, 20 Nassau Street, #240, Princeton NJ 08542 [tel: 609-921-7771]
To help us put together a balanced list of commentators, please give
some indication of the aspects of the topic on which you would bring
your areas of expertise to bear if you were selected as a commentator.
An electronic draft of the full text is available for inspection by
anonymous ftp according to the instructions that follow after the abstract.
____________________________________________________________________
TOWARD A THEORY OF HUMAN MEMORY:
DATA STRUCTURES AND ACCESS PROCESSES
Michael S. Humphreys, Department of Psychology
Janet Wiles, Departments of Psychology and Computer Science
Simon Dennis, Department of Computer Science
University of Queensland
QLD 4072 Australia
mh@psych.psy.uq.oz.au
KEYWORDS: amnesia, binding, context, data structure, lexical
decision, memory access, perceptual identification, recall,
recognition, representation.
ABSTRACT: A theory of the data structures and access processes of
human memory is proposed and demonstrated on 10 tasks. The two
starting points are Marr's (1982) ideas about the levels at which
we can understand an information processing device and the standard
laboratory paradigms which demonstrate the power and complexity of
human memory. The theory suggests how to capture the functional
characteristics of human memory (e.g., analogies, reasoning, etc.)
without having to be concerned with implementational details. Ours
is not a performance theory. We specify what is computed by the
memory system with a multidimensional task classification which
encompasses existing classifications (e.g., the distinction between
implicit and explicit, data driven and conceptually driven, and
simple associative (2-way bindings) and higher order tasks (3-way
bindings). This provides a broad basis for new experimentation.
Our formal language clarifies the binding problem in episodic
memory, the role of input pathways in both episodic and semantic
(lexical) memory, the importance of the input set in episodic
memory, and the ubiquitous calculation of an intersection in
theories of episodic and lexical access.
- --------------------------------------------------------------
To help you decide whether you would be an appropriate commentator for
this article, an electronic draft is retrievable by anonymous ftp from
princeton.edu according to the instructions below (the filename is
bbs.humphreys). Please do not prepare a commentary on this draft.
Just let us know, after having inspected it, what relevant expertise
you feel you would bring to bear on what aspect of the article.
The file is also retrievable using archie, gopher, veronica, etc.
- -------------------------------------------------------------
To retrieve a file by ftp from an Internet site, type either:
ftp princeton.edu
or
ftp 128.112.128.1
When you are asked for your login, type:
anonymous
Enter password as queried (your password is your actual userid:
yourlogin@yourhost.whatever.whatever - be sure to include the "@")
cd /pub/harnad/BBS
To show the available files, type:
ls
Next, retrieve the file you want with (for example):
get bbs.humphreys
When you have the file(s) you want, type:
quit
These files can also be retrieved using gopher, archie, veronica, etc.
- ----------
Where the above procedure is not available there are two fileservers:
ftpmail@decwrl.dec.com
and
bitftp@pucc.bitnet
that will do the transfer for you. To one or the
other of them, send the following one line message:
help
for instructions (which will be similar to the above, but will be in
the form of a series of lines in an email message that ftpmail or
bitftp will then execute for you).
JANET users without ftp can instead utilise the file transfer facilities
at sites uk.ac.ft-relay or uk.ac.nsf.sun. Full details are available on
request.
- -------------------------------------------------------------
------------------------------
Subject: Neural Computation BibTeX database available
From: Nici Schraudolph <schraudo@salk.edu>
Date: Tue, 01 Feb 1994 00:04:05 -0800
I've made a database of BibTeX entries for all articles published in the
first five volumes of the journal Neural Computation; it's available by
anonymous ftp from mitpress.mit.edu (18.173.0.28), file NC.bib.Z in the
pub/NeuralComp directory.
Share and enjoy,
- - Nici Schraudolph.
------------------------------
Subject: donations to bibliography server
From: Lutz Prechelt <prechelt@ira.uka.de>
Date: Tue, 01 Feb 1994 15:08:12 +0100
A colleague of mine here at University of Karlsruhe is currently
building a large bibliographic database that is available free of
charge on the internet.
It currently contains about 210000 entries from various fields of
computer science (mostly parallel processing, graphics, theoretical
computer science, computational geometry, human computer interaction)
Although there are several thousand entries on Artificial Intelligence topics,
connectionism is not covered very well yet (Neural Computation's contents
are present and some personal bibliographies).
To extend this database by at least some basic information about
neural network and other connectionist research, it would be fine if
somebody could donate bibliographies on these topics which are
(almost) comprehensive in some respect.
In particular, I think it would be a very good start to have complete
contents of NIPS, IJCNN, and Neural Networks (and perhaps, other journals
such as Complex Systems).
If anybody is able and willing to donate such bibliographies,
please send me email.
BibTeX format would be best, but refer or other parsable formats are OK, too.
For information on the bibliography service, send mail with a single line
containing the word 'help' in the body to bibserv@ira.uka.de
[ The query service is still in a test stage and is not yet available to
people located outside email domain '.de' (Germany)
due to resource restrictions.
The bibliographies themselves, however, are available for anonymous ftp
from ftp.ira.uka.de:/pub/bibliography ]
Lutz
Lutz Prechelt (email: prechelt@ira.uka.de) | Whenever you
Institut fuer Programmstrukturen und Datenorganisation | complicate things,
Universitaet Karlsruhe; 76128 Karlsruhe; Germany | they get
(Voice: ++49/721/608-4068, FAX: ++49/721/694092) | less simple.
------------------------------
Subject: FUZZY + Neural nets?
From: ignacio@casip.ugr.es
Date: Tue, 01 Feb 1994 19:09:22 +0200
Hello :
I am working in fuzzy logic for control problem. I read some paper that try
to combine the adavantages of neural and fuzzy to solve control problem, using
the structure proposed by C.Lee .Diferent author followed this idea (Kosko,
H.Surmann ...)
I would like to know how i could get tool to work in this subject
Thanks in advances
Ignacio Rojas
Universidad Granada,Spain
Dep.Electronica y Tecnologia
de Computadores
e-mail : ignacio@casip.ugr.es
------------------------------
Subject: ANNs for market prediction
From: BHASKAR DASGUPTA ALIAS BD <B.DASGUPTA@fs3.mbs.ac.uk>
Date: 02 Feb 1994 18:49:22 -0000
Hiya all,
I am facing a problem and I would appreciate any help.
I have 36 neural networks forecasting one period ahead movements in
stock prices in 18 countries. Now, I want to create a portfolio, in
which, depending on the maximum return predicted, the system is going
to invest in / or withdraw from particular markets. Now, I also have
several constraints such as x% investment in one market, y% maximum
in emerging markets, z% in bonds, equities and cash etc. etc.
I have formulated the LP model for this, but the problem is that I
have approximately 1400 portfolios to construct. So, assuming that I
spend about 30 minutes on one portfolio using LINDO PC, the mind
boggles at the total amount of time that I would have to spend on the
entire lot. So not wanting my mind to be boggled :-<, I have decided
to ask to assistance of this group.
So the particular questions are. (1) is it possible to get a GA to
carry out the same type of exercise as is possible using an LP
(linear programming) model ? (2) If yes, which GA software,
(preferably free, definitely MSDOS or windows) (3) Is there anyone
else doing the same thing in the wide world outside? (4) I heard
about a GA software called as Evolution Machine in Germany. I just
cannot get the ftp to work to get the software, any help on this,
i.e. has anyone got any information whether this software exists on
any other ftp? (5) is there any software which can help me automate
this process in Linear Programming, preferably free, but then the
world is not perfect, so perhaps low cost ones?
I would be eternally grateful for any kind of help. I shall be
posting this SOS to other groups, so apologies if you get this more
than once.
Cheers
BD
Manchester Business School
England.
------------------------------
Subject: CMU-Pitt Center for the Neural Basis of Cognition
From: "James L. McClelland" <jlm@crab.psy.cmu.edu>
Date: Thu, 03 Feb 1994 11:27:41 -0500
+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Carnegie Mellon University and the University of Pittsburgh
Announce the Creation of
the Center for the Neural Basis of Cognition
The Center is dedicated to the study of the neural basis of cognitive
processes, including learning and memory, language and thought,
perception, attention, and planning; to the study of the development
of the neural substrate of these processes; to the study of disorders
of these processes and their underlying neuropathology; and to the
promotion of applications of the results of these studies to artificial
intelligence, technology, and medicine. The Center will synthesize the
disciplines of basic and clinical neuroscience, cognitive psychology,
and computer science, combining neurobiological, behavioral, computa-
tional and brain imaging methods.
+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Faculty Openings in the Center
The Center seeks faculty and research scientists whose work relates to
the mission stated above. Recruiting is beginning immediately, and
will continue for several years. Appointments can be at any level and
will be coordinated with one or more departments at either university.
Coordinating departments include Biological Sciences, Computer Science,
and Psychology at Carnegie Mellon and the departments of Behavioral
Neuroscience, Neurobiology, Neurology, Psychiatry and Psychology at the
University of Pittsburgh. Other affiliations may be possible.
Candidates should send an application to either of the Co-Directors of
the Center, listed below. The application should include a statement
of interest indicating how the candidate's work fits the mission of the
center and suggesting possible departmental affiliations, as well as a
CV, copies of publications, and three letters of reference. Both uni-
versities are EEO/AA Employers.
James L. McClelland Robert Y. Moore
Department of Psychology Center for Neuroscience
Baker Hall 345-F Biomedical Science Tower 1656
Carnegie Mellon University University of Pittsburgh
Pittsburgh, PA 15213 Pittsburgh, PA 15261
+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
------------------------------
Subject: PhD and Masters Programs at the Oregon Graduate Institute
From: John Moody <moody@chianti.cse.ogi.edu>
Date: Fri, 04 Feb 1994 15:50:07 -0800
Fellow Connectionists:
The Oregon Graduate Institute of Science and Technology (OGI) has
openings for a few outstanding students in its Computer Science
and Electrical Engineering Masters and Ph.D programs in the areas
of Neural Networks, Learning, Signal Processing, Time Series,
Control, Speech, Language, and Vision.
Faculty and postdocs in these areas include Etienne Barnard, Ron
Cole, Mark Fanty, Dan Hammerstrom, Hynek Hermansky, Todd Leen, Uzi
Levin, John Moody, David Novick, Misha Pavel, Joachim Utans, Eric
Wan, and Lizhong Wu. Short descriptions of our research interests
are appended below.
OGI is a young, but rapidly growing, private research institute
located in the Portland area. OGI offers Masters and PhD programs
in Computer Science and Engineering, Applied Physics, Electrical
Engineering, Biology, Chemistry, Materials Science and Engineering,
and Environmental Science and Engineering.
Inquiries about the Masters and PhD programs and admissions for
either Computer Science or Electrical Engineering should be addressed
to:
Margaret Day, Director
Office of Admissions and Records
Oregon Graduate Institute
PO Box 91000
Portland, OR 97291
Phone: (503)690-1028
Email: margday@admin.ogi.edu
The final deadline for receipt of all applications materials for
the Ph.D. programs is March 1, 1994, so it's not too late to apply!
Masters program applications are accepted continuously.
+++++++++++++++++++++++++++++++++++++++++++++++++++++++
Oregon Graduate Institute of Science & Technology
Department of Computer Science and Engineering
& Department of Electrical Engineering and Applied Physics
Research Interests of Faculty in Adaptive & Interactive Systems
(Neural Networks, Signal Processing, Control, Speech, Language, and Vision)
Etienne Barnard (Assistant Professor):
Etienne Barnard is interested in the theory, design and implementation
of pattern-recognition systems, classifiers, and neural networks.
He is also interested in adaptive control systems -- specifically,
the design of near-optimal controllers for real- world problems
such as robotics.
Ron Cole (Professor):
Ron Cole is director of the Center for Spoken Language Understanding
at OGI. Research in the Center currently focuses on speaker-
independent recognition of continuous speech over the telephone
and automatic language identification for English and ten other
languages. The approach combines knowledge of hearing, speech
perception, acoustic phonetics, prosody and linguistics with neural
networks to produce systems that work in the real world.
Mark Fanty (Research Assistant Professor):
Mark Fanty's research interests include continuous speech recognition
for the telephone; natural language and dialog for spoken language
systems; neural networks for speech recognition; and voice control
of computers.
Dan Hammerstrom (Associate Professor):
Based on research performed at the Institute, Dan Hammerstrom and
several of his students have spun out a company, Adaptive Solutions
Inc., which is creating massively parallel computer hardware for
the acceleration of neural network and pattern recognition
applications. There are close ties between OGI and Adaptive
Solutions. Dan is still on the faculty of the Oregon Graduate
Institute and continues to study next generation VLSI neurocomputer
architectures.
Hynek Hermansky (Associate Professor);
Hynek Hermansky is interested in speech processing by humans and
machines with engineering applications in speech and speaker
recognition, speech coding, enhancement, and synthesis. His main
research interest is in practical engineering models of human
information processing.
Todd K. Leen (Associate Professor):
Todd Leen's research spans theory of neural network models,
architecture and algorithm design and applications to speech
recognition. His theoretical work is currently focused on the
foundations of stochastic learning, while his work on Algorithm
design is focused on fast algorithms for non-linear data modeling.
Uzi Levin (Senior Research Scientist):
Uzi Levin's research interests include neural networks, learning
systems, decision dynamics in distributed and hierarchical
environments, dynamical systems, Markov decision processes, and
the application of neural networks to the analysis of financial
markets.
John Moody (Associate Professor):
John Moody does research on the design and analysis of learning
algorithms, statistical learning theory (including generalization
and model selection), optimization methods (both deterministic and
stochastic), and applications to signal processing, time series,
and finance.
David Novick (Assistant Professor):
David Novick conducts research in interactive systems, including
computational models of conversation, technologically mediated
communication, and human-computer interaction. A central theme of
this research is the role of meta-acts in the control of interaction.
Current projects include dialogue models for telephone-based
information systems.
Misha Pavel (Associate Professor):
Misha Pavel does mathematical and neural modeling of adaptive
behaviors including visual processing, pattern recognition, visually
guided motor control, categorization, and decision making. He is
also interested in the application of these models to sensor
fusion, visually guided vehicular control, and human-computer
interfaces.
Joachim Utans (Post-Doctoral Research Associate):
Joachim Utans's research interests include computer vision and
image processing, model based object recognition, neural network
learning algorithms and optimization methods, model selection and
generalization, with applications in handwritten character recognition
and financial analysis.
Lizhong Wu (Post-Doctoral Research Associate):
Lizhong Wu's research interests include neural network theory and
modeling, time series analysis and prediction, pattern classification
and recognition, signal processing, vector quantization, source
coding and data compression. He is now working on the application
of neural networks and nonparametric statistical paradigms to
finance.
Eric A. Wan (Assistant Professor):
Eric Wan's research interests include learning algorithms and
architectures for neural networks and adaptive signal processing.
He is particularly interested in neural applications to time series
prediction, adaptive control, active noise cancellation, and
telecommunications.
------------------------------
Subject: UK PhD studentships at Leeds, England
From: E S Atwell <eric@scs.leeds.ac.uk>
Date: Sat, 05 Feb 1994 13:35:51 +0000
*****************************************************************************
** PLEASE POST ON YOUR FINAL-YEAR Ugrad AND MSc BULLETIN BOARD / NEWSGROUP **
*****************************************************************************
THE UNIVERSITY OF LEEDS
Centre for Computer Analysis of Language And Speech (CCALAS)
PhD RESEARCH SCHOLARSHIPS
The University of Leeds has up to 5 Research Scholarships for full-time PhD
study available for take up by UK students in October 1994. The scholarships
cover academic fees at the UK rate and a maintenance grant of #4,950 a year.
CLOSING DATE FOR APPLICATIONS: 11 MARCH 1994.
To join the CCALAS research centre, you will need a BSc/BA (ideally First
Class Honours) in Artificial Intelligence, Computer Science, Education,
Engineering, English, Linguistics, Modern Languages, Philosophy, Psychology or
a related discipline; and interest in corpus-based computational linguistics.
Informal enquiries about research opportunities in CCALAS may be made to:
Eric Atwell, tel 0532 335761, fax 0532 335468, email eric@scs.leeds.ac.uk ;
or Clive Souter, tel 0532 335460, email cs@scs.leeds.ac.uk ; or Peter Roach,
tel 0532 335759, fax 0532 335749, email peterr@psychology.leeds.ac.uk
Application forms may be obtained from the Research Degrees and Scholarships
Office (UK Studentships), The University, Leeds LS2 9JT, tel 0532 335771
****************************************************************************
COMPUTATIONAL LINGUISTICS RESEARCH AT LEEDS UNIVERSITY
Computer Analysis of Language And Speech is a thriving research area, at Leeds
as well as nationally and internationally. We are still a long way from
general, robust systems that can fully `understand' Natural Languages such as
English. However, it is possible to identify specific subproblems or `niche'
applications where current theory and technology can be applied usefully.
Several research funding agencies support research in this interdisciplinary
area, including the Science and Engineering Research Council (SERC), Economic
and Social Research Council (ESRC), Ministry of Defence (MoD), Department of
Trade and Industry (DTI), British Council, and Higher Education Funding
Councils (HEFCs) special initiatives such as Knowledge Based Systems
Initiative (KBSI) and New Technologies Initiative (NTI). Leeds University
researchers have an excellent track record in winning research grants from
these sources, and will continue to seek external research funding; the
University is also contributing internal support.
CCALAS is a focus for researchers from a range of departments at Leeds
University, providing a `critical mass' of expertise and sharable resources
for research over a broad range of fundamental and application-oriented topics
involving the computer analysis of language and speech. CCALAS members offer
postgraduate research supervision and taught course modules leading to the
degree of MSc, MA, MPhil, or PhD. CCALAS members are also involved in
externally-funded Research and Development projects, and welcome PhD students
with research interests linked to these larger projects.
CCALAS covers a broad range of computer corpus- and dictionary-based research
including:
computers in lexicography (Atwell, Cowie, Roach, Setter, Souter),
corpus annotation (Arnfield, Atwell, Bull, Ghali, Hughes, Roach, Souter),
corpus collocation analysis (Howarth, Cowie, Davidson),
grammar-based reasoning (Mott, Silver),
grammatical inference (Arnfield, Atwell, Demetriou, Hanlon, Hughes, Jost,
Souter, Tarver, Ueberla),
handwriting recognition (Atwell, Boyle, Hanlon),
language and linguistics teaching (Atwell, Davidson, Hunter, Roach, Shivtiel),
probabilistic parsing (Atwell, Hogg, Jost, O'Donoghue, Souter),
speech act theory (Holdcroft, Millican, Wallis, Wynne),
speech recognition (Atwell, Kirby, Lockhart, Mair, Sergant, Roach, Ueberla),
speech synthesis (Moore, Roach, Scully),
text generation (Cole, Grierson, Tawalbeh),
word-sense semantic disambiguation and tagging (Atwell, Demetriou, Jost).
****************************************************************************
Leeds University has over 15,000 students and 2,000 academic and research
staff, making it one of the largest in Britain. Leeds is half-way between
London and Edinburgh, linked by rail, motorway and air to the rest of the UK
and Europe. It is the 20th largest city in the European Community, with the
excellent arts, sport and other social facilites expected of a growing,
multi-cultural metropolis; but it is also close to four National Parks. More
background information on CCALAS, the University, and Leeds and its environs
can be found in the University Postgraduate Prospectus.
------------------------------
Subject: papers on time and neural networks
From: grumbach@inf.enst.fr
Organization: Ecole Nationale Superieure des Telecommunications, Paris
Date: Mon, 14 Feb 1994 09:51:22 +0100
As guest editors of a special issue of the Sigart Bulletin about :
Time and Neural Networks
we are looking for 4 articles about 10 pages each.
Sigart is a quarterly publication of the Association for Computing
Machinery (ACM) special interest group on Artificial Intelligence.
The paper may either deal with approachs of time processing using
traditional connectionist architectures, or with more specific models
integrating time in their basis.
If you are interested, and if you can submit a paper (not already
published) within a short delay (about 1 month and a half), please send a
draft (if possible a Word file) :
- - preferably by giving ftp access to it (information via e-mail)
- - or sending it as "attached file" on e-mail
- - or posting a paper copy of it.
Drafts should be received before April 1.
Notification of acceptance will be sent before April 20.
grumbach@enst.fr or chaps@enst.fr
Alain Grumbach and Cedric Chappelier
ENST dept INF
46 rue Barrault
75634 Paris Cedex 13
France
------------------------------
Subject: JAIR article
From: Steve Minton <minton@ptolemy.arc.nasa.gov>
Date: Wed, 16 Feb 1994 18:03:21 -0800
Readers of this newsgroup may be interested the following article, which
was recently published in the Journal of Artificial Intelligence
Research:
Ling, C.X. (1994)
"Learning the Past Tense of English Verbs: The Symbolic Pattern Associator
vs. Connectionist Models", Volume 1, pages 209-229
Postscript: volume1/ling94a.ps (247K)
Online Appendix: volume1/ling-appendix.Z (109K) data file, compressed
Appendix: Learning the past tense of English verbs - a seemingly minor
aspect of language acquisition - has generated heated debates since
1986, and has become a landmark task for testing the adequacy of
cognitive modeling. Several artificial neural networks (ANNs) have
been implemented, and a challenge for better symbolic models has been
posed. In this paper, we present a general-purpose Symbolic Pattern
Associator (SPA) based upon the decision-tree learning algorithm ID3.
We conduct extensive head-to-head comparisons on the generalization
ability between ANN models and the SPA under different
representations. We conclude that the SPA generalizes the past tense
of unseen verbs better than ANN models by a wide margin, and we offer
insights as to why this should be the case. We also discuss a new
default strategy for decision-tree learning algorithms.
JAIR's server can be accessed by WWW, FTP, gopher, or automated email.
For further information, check out our WWW server (URL is
gopher://p.gp.cs.cmu.edu/) or one of our FTP sites (/usr/jair/pub at
p.gp.cs.cmu.edu), or send email to jair@cs.cmu.edu with the subject
AUTORESPOND and the message body HELP.
------------------------------
Subject: Shakespeare and Neural Nets
From: Terry Sejnowski <terry@salk.edu>
Date: Thu, 24 Feb 1994 02:49:35 -0800
from New Scientist 22 january 1994 p. 23
In an interesting article on the use of statistical measures to
assess the attribution of texts to authors, Robert Matthews and
Tom Merrriam report that:
"Applying our neural network to disputed works such as
'The Two Noble Kinsman' has produced some interesting
results and helped to settle some bitter arguments over authorship
of controversial texts. ...
"The first task was to train the network. This we did by exposing
it to data extracted from a large number of samples of Shakespeare's
undisputed work, together with that of his successor with The King's
Men [a theater], John Fletcher. ... We then set the network loose on
'The Two Noble Kinsman'. Drawing on a wide variety of essentially
subjective evidence, scholars have claimed that Shakespeare's hand
dominates Acts I and V, with much of the rest appearing to be by
Fletcher. In March last year, our neural network agreed with these
attributions -- and proferred the extra opinion that Fletcher may
have received considerable help from Shakespeare in Act IV. In short,
our neural network quantitatively supports the subjective view of its
much more sophisticated human counterparts that 'The Two Noble Kinsman'
is a genuine collaboration between Shakespeare and one of his
contemporaries."
These results will appear in the journal 'Literary and Linguistic Computing'.
A similar approach might be used to determine the contributions of
coauthors to scientific papers.
Terry
- -----
------------------------------
End of Neuron Digest [Volume 13 Issue 11]
*****************************************
