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IRList Digest Volume 3 Number 46

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IRList Digest
 · 1 year ago

IRList Digest           Thursday, 10 December 1987      Volume 3 : Issue 46 

Today's Topics:
Query - Detecting language from a title
- Hypertext bibliography?
- References to knowledge based tools for AI bibliographies
Interest - History and retrieval
- IR analyst using SPIRES
Announcement - Impact of new technology on information professionals
COGSCI - Grouping in recognition
- Comparitive analysis, Truth and cognitive science,
Unified Medical Language system

News addresses are
Internet or CSNET: fox@vtopus.cs.vt.edu
BITNET: foxea@vtvax3.bitnet

----------------------------------------------------------------------

Date: 30-NOV-1987 19:17:17 GMT
From: LOU@VAX.OXFORD.AC.UK
Subject: an interesting problem


Here's an interesting problem someone may have an answer to: what's the best
way of automatically detecting the language in which something is written?
We have a library here in Oxford with a large (well, very large actually)
catalogue of book titles in just about every european language you can think
of: english greek latin german hebrew french russian... in order to get the
indexing strategy right (it's a bit dim to mark "the" as a stop word if the
title is in French) to say nothing of the hyphenation points, it would be
nice to get each title tagged by its language. As there are something like
one and a quarter million titles (I did say it was large) it would be even nicer
to do this at least semi-automtically. Any suggestions? High frequency words
might be one possibility, except that titles are mostly (but not all) quite
short. Has anyone done anything similar with trigrams?

Lou Burnard (LOU @ UK.AC.OXFORD.VAX )

------------------------------

Date: Tue, 1 Dec 1987 11:00 EST
From: James Nolte <$JSN@CLVM>
Subject: Brown Bibliography on Hypertext from Hypertext 87

You mentioned in the IRLIST Digest of Wednesday, 25 November that Brown
distributed a bibliography on Hypertext. Is that Brown University? Do
you have an address or contact person from whom I could obtain such
a bibliography?

[Note: try ny@iris.bitnet which will get you to the IRIS Project at
Brown. Maybe we will get some news from IRIS soon? - Ed]

------------------------------

Date: Wed, 2 Dec 87 08:59 EST
From: Roland Zito-Wolf <RJZ@JASPER.Palladian.COM>
Subject: Knowledge-based bibliographies


I am looking for references regarding knowledge-bases and KB-based tools
for organizing a bibliographic database on AI. I want to be able to retrieve
references by various indices.

Specific issues I'd like to know about:
- friendly data entry
- searching through alternate paths (say, finding articles related
to a given article in some way: by author, topic, system name,
etc.)
- ability to "evolve" the structure of the KB with time
- what is areasonable conceptual structure for reference databases, in
general?

I'll post a digest of responses to the list.

Roland J. Zito-wolf
Palladian Software
4 Cambridge Center
Cambridge, Mass 02142
617-661-7171
RJZ%JASPER@LIVE-OAK.LCS.MIT.EDU

------------------------------

Date: Thu, 3 Dec 87 09:40:12 GMT
From: F.E.Candlin@VME.GLASGOW.AC.UK
Subject: SUBSCRIPTION TO IRList

Dear Professor Fox, This note is to ask you if you would be willing to put me
down for subsription to IRList. I work as the programmer at the DISH History
and Computing Lab at Glasgow University, Scotland. At Glasgow, we have a
number of fairly large databases - bankruptcies, marriage records, property
valuations, trade accounts etc - which were produced largely using software
developed by ourselves. In addition about half of the academic staff involved
in using computers in history teaching are now producing smaller datasets
specifically related to their courses. One of the interesting things about this
kind of data is the fact that it usually existed in retrievable form long before
computers were invented. To maintain the integrity of the source, we usually
try to reflect the original form of the data in our databases (be it the
marriage register, the account book or whatever). Very few dbms's cope well
with such data - normally preferring explicit relationships between items
of interest and disliking small inconsistencies whem carrying out analysis.
More strain is put on the dbms by the demands of the typical historian, who
is as interested in exceptions as general statistics. He is also interested
in following up specific people who may pop up in a number of otherwise
unrelated sources. None of this is unique to historians, of course, but the
insight that we have gained has inspired us to set up a new project to look
into ways of instructing information managers in the implications of large-
sets of messy data.

My address is: F.E.Candlin,
DISH History Computing Laboratory,
2 University Gardens,
Glasgow University,
Glasgow G12 8QQ, SCOTLAND
Telephone: 041 339 8855 x 4510
Email: F.E.Candlin@UK.AC.Glasgow.VME

Many Thanks

------------------------------

Date: Fri, 27 Nov 87 11:50:02 MST
From: Terry Butler <TBUTLER@UALTAVM>
Subject: Join IRList

I would like to join IRList. I am an IR analyst in the computing department
at the University of Alberta, Edmonton, Alberta, Canada. Our unit provides
computing support for academics at our university. Our major offering is
SPIRES on the mainframe; and we are supporting several micro data base
packages.

------------------------------

Date: Sun, 29 Nov 87 20:05:19 EST
From: dws@EDDIE.MIT.EDU (Don W. Saklad)
Message-Id: <8711300105.AA11893@EDDIE.MIT.EDU>
To: FOX@VTCS1.BITNET
Subject: notice posted at our local public library

Summary: interesting notice posted on our local public library bulletin board
Keywords: library libraries
The Graduate School of Library & Information Science
Simmons College

invites you to attend
a lecture in

The Samuel Lazerow Memorial Lecture Series sponsored by
The Institute for Scientific Information

featuring

Dr. Elizabeth Young
Vice-President, INMARSAT, Policy and Representation
COMSAT Maritime Services

An executive in one of the nations's leading satellite
communications companies, Dr. Young will share her
insights: "the impact of new technologies on the role
and status of the information professional."

Wednesday, December 9, 1987
Simmons College Auditorium
300 The Fenway
Boston

Schedule of Events
----------------------


2:00-2:30 Registration

2:30-4:00 Welcome and Introduction
Dean Robert D. Stueart

Lazerow Lecture
Dr. Elizabeth Young

4:00-5:00 Reception and refreshments, GSLIS Lounge
Open House, GSLIS Computer Access Laboratory

Hardware and software recently acquired by the School will be on
display in the Computer Access Laboratory. Faculty and students will be
available to discuss and demonstrate some of the new technologies
which include BiblioFile, SilverPlater, Dissertation Abstracts on Disc,
DATEXT, Dialog on Disc, OCLC's Search CD-450, WilsonDisc and the Library
Students Association electronic bulletin board.

Attendance by reservation only.
RSVP to Linda Willey, at 617-738-2223 by Monday December 7

[Note: Can anyone tell us what happened? - Ed]

------------------------------

Date: Mon, 16 Nov 1987 13:17 EST
From: Peter de Jong <DEJONG%OZ.AI.MIT.EDU@XX.LCS.MIT.EDU>
Subject: Cognitive Science Calendar [Extract - Ed]

Date: Saturday, 14 November 1987 11:36-EST
From: Paul Resnick <pr at ht.ai.mit.edu>
Re: AI Revolving Seminar

Thursday 19, November 4:00pm Room: NE43- 8th floor Playroom


The Artificial Intelligence Lab
Revolving Seminar Series


THE USE OF GROUPING IN VISUAL OBJECT RECOGNITION


David Jacobs


Many systems have been developed for recognizing two and three
dimensional objects in images. Some problems emerge, however, when we
try to extend these approaches to handle more complex tasks. More
complex tasks might include using knowledge of large libraries of
different objects instead of looking for just a single object, knowing
about flexible objects instead of rigid ones, or recognizing objects in
large, complex images. All these tasks require much more computation
from existing recognition systems, and make them more prone to commit
errors.

This talk will describe an object recognition system which attempts to
deal with these problems of accuracy and complexity by using grouping.
The system, called GROPER, knows about a library of different
two-dimensional objects, and examines images which contain some of these
objects, perhaps partially occluded. It proceeds by forming groups of
image edges which seem particularly likely to have come from a single
object. It then matches these groups of image edges to groups of model
edges by hashing. Grouping allows GROPER to first try to perform
recognition with the groups of edges most likely to lead to the correct
recognition of an object. A comparison between GROPER's performance and
that of a similiar recognition system which does not use grouping shows
that this can dramatically reduce the amount of computation required
for recognition and dramatically reduce the number of mistakes made.

------------------------------

Date: Sat, 28 Nov 1987 12:40 EST
From: Peter de Jong <DEJONG%OZ.AI.MIT.EDU@XX.LCS.MIT.EDU>
Subject: Cognitive Science Calendar [Extract - Ed]

Date: Tuesday, 24 November 1987 18:22-EST
From: Marc Vilain <MVILAIN at G.BBN.COM>
Re: BBN AI Seminar -- Daniel Weld

BBN Science Development Program
AI Seminar Series Lecture

THEORIES OF COMPARATIVE ANALYSIS

Daniel S. Weld
MIT Artificial Intelligence Lab
(WELD@REAGAN.AI.MIT.EDU)

BBN Labs
10 Moulton Street
2nd floor large conference room
10:30 am, Tuesday December 1


This talk analyzes two approaches to a central subproblem of automated
design, diagnosis, and intelligent tutoring systems: comparative
analysis. Comparative analysis may be considered an analog of
qualitative simulation. Where qualitative simulation takes a structural
model of a system and qualitatively describes its behavior over time,
comparative analysis is the problem of predicting how that behavior will
change if the underlying structure is perturbed and also explaining why
it will change.

For example, given Hooke's law as the model of a horizontal,
frictionless spring/block system, qualitative simulation might generate
a description of oscillation. Comparative analysis, on the other hand,
is the task of answering questions like: ``What would happen to the
period of oscillation if you increase the mass of the block?'' I have
implemented, tested, and proven theoretical results about two different
techniques for solving comparative analysis problems, differential
qualitative (DQ) analysis and exaggeration.

DQ analysis would answer the question above as follows: ``Since force is
inversely proportional to position, the force on the block will remain
the same when the mass is increased. But if the block is heavier, then
it won't accelerate as fast. And if it doesn't accelerate as fast, then
it will always be going slower and so will take longer to complete a
full period (assuming it travels the same distance).''

Exaggeration can also solve this problem, but it generates a completely
different answer: ``If the mass were infinite, then the block would
hardly move at all. So the period would be infinite. Thus if the mass
was increased a bit, the period would increase as well.''

Both of these techniques has advantages and limitations. DQ analysis is
proven sound, but is incomplete. It can't answer every comparative
analysis problem, but all of its answers are correct. Because
exaggeration assumes monotonicity, it is unsound; some answers could be
incorrect. Furthermore, exaggeration's use of nonstandard analysis makes
it technically involved. However, exaggeration can solve several
problems that are too complex for DQ analysis. The trick behind its
power appears to have application to all of qualitative reasoning.

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

Date: Thursday, 19 November 1987 12:09-EST
From: Eric Sven Ristad <RISTAD%OZ.AI.MIT.EDU at XX.LCS.MIT.EDU>
Tuesday, 1 December 7:30pm Room: 34-401 (Grier Conference Room)


TRUTH AND COGNITIVE SCIENCE

Hilary Putnam
Department of Philosophy, Harvard University

The following facts are commonly cited as examples of
"intentionality": (i) the fact that words, sentences, and other
"representations" have meaning; (ii) the fact that representations may
refer to some actually existing thing or each of a number of actually
existing things; (iii) the fact that representations may be about
something which does not exist; and (iv) the fact that a state of mind
may have a "state of affairs" as its object, as when someone says,
"she believes that [he is trustworthy]."

When the computer revolution burst upon the world, it was widely
expected (and claimed) that computer models would explain the nature
of these various phenomena. In short, people expected that a reductive
account of the various topics included under the chapter-heading
"intentionality" would be given. Now that this has not proved so easy,
a number of thinkers are beginning to suggest that it isn't so bad if
this can't be done; intentionality is only a feature of "folk
psychology" anyway. If a first class scientific account of intentional
facts and phenomena can't be given, that is not because scientific
reductionism is not the right line to take in metaphysics, but rather
it is because there is, so to speak, nothing there to reduce. I want
to argue that both attitudes are mistaken; that intentionality won't
be reduced and won't go away.


Commentary: Jerry Fodor
Department of Philosophy, CUNY


Copies of paper Karen persinger, 20B-225, 253-7358

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

Date: Tuesday, 24 November 1987 12:34-EST
From: Rosemary B. Hegg <ROSIE at XX.LCS.MIT.EDU>
Re: Komorowski Seminar


DATE: Wednesday, December 2, 1987
TIME: Refreshments: 1.45PM
Lecture: 2.00PM
PLACE: NE43-8th floor playroom

THE UNIFIED MEDICAL LANGUAGE SYSTEM

HENRYK JAN KOMOROWSKI

Decision Systems Laboratory
Harvard Medical School/Brigham and Women's Hospital
MIT Artificial Intelligence Laboratory

Knowledge systems in medical applications had several undeniable
successes, yet it is fair to say that only very few of the systems
found their way to everyday use. One well recognized impediment to
progress is the lack of a knowledge-base (KB) which would encompass
a broad spectrum of medical knowledge. Instead of embarking on a
200 man/year project to encode a comprehensive KB of modern
medicine, a group of academic institutions joined efforts and
expertise to develop a canonical taxonomy of medical terms and
relations. This canonical taxonomy, called a Unified Medical Language
System, will provide standards for structuring, indexing, retrieving,
and communicating medical knowledge. It is anticipated that the
UMLS will be the kernel of most future biomedical applications. An
application may develop its knowledge-base as an extension to the
taxonomy and use the UMLS as an interlingua to communicate with
other applications. In this scenario parallel development and sharing
of multiple expert resources will be possible.

One critical issue in the creation of UMLS and a particular focus in
our research is the identification of semantic features and relations
which should be represented in the taxonomy, and the design of
appropriate structures and tools for storing, displaying, and authoring
these features and relations. The currently developed prototypical
taxonomy and the viewing and authoring environment has begun to
open the road to a magnitude of applications. They include an
environment for learning the structure of medicine, efficient
preparation of queries to the external body of the existing medical
literature, automatic acquisition of medical knowledge, automatic
identification of related concepts, free browsing in pursuit of
curiosity, etc.

The development of the UMLS continues to challenge both the
computer scientists and the medical community.

HOST: Peter Szolovits

------------------------------

END OF IRList Digest
********************

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