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IRList Digest Volume 2 Number 67
IRList Digest Monday, 1 December 1986 Volume 2 : Issue 67
Today's Topics:
Abstracts - NSF IST Awards for Fiscal Year 1986 - Part 5 of 5
News addresses are ARPANET: fox%vt@csnet-relay.arpa BITNET: foxea@vtvax3.bitnet
CSNET: fox@vt UUCPNET: seismo!vtisr1!irlistrq
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Date: Fri, 21 Nov 86 18:38:14 est
From: vtopus!fox (Ed Fox)
Subject: Information on NSF awards, sent by J. Deken at NSF
Fiscal Year 1986 Research Projects
Funded by the Information Science Program
(now Knowledge and Database Systems Program)
Part 5 of 5
IST-8640053
$59,178 - 12 mos.
Sharon C. Salveter
Boston University
Transportable Natural Language Database Update
- - -
The use of natural languages such as English to interact with computer databases
has been an active research area for many years. Most projects in this area
have been limited to handling requests for information already in the database.
This research project uses verbgraphs, a formal representation technique
previously developed by the Principal Investigator, as a basis for also handling
the more difficult task of making changes to this information in the database.
General information needed to handle natural language is kept separate from
information about a specific application, in order to allow the system to be
used for a variety of applications with as few changes as possible. The project
will advance both the theory and the applications of database management systems
and natural language understanding.
_____
IST-8610293
$80,630 - 12 mos.
Glenn R. Shafer
University of Kansas Main Campus
Belief Functions in Artificial Intelligence
- - -
This research develops and investigates the "belief function" approach to
representing uncertainty. In realistic situations which are now being modeled by
expert computer systems, hypotheses, facts, and values are usually not held with
certainty. Classic approaches to uncertainty such as probability have a firm
mathematical foundation but often require more input data than realistic expert
systems have available. In the belief function approach pioneered by Dempster
and Shafer, uncertain elements are not assigned probabilities but degrees of
belief. The present theoretical research extends the range of situations where
belief functions can be used, and develops procedures which will allow
computers to reason efficiently to derive new hypotheses and conclusions from
belief function representations. The representation of uncertainty is a pivotal
element in modern artificial intelligence systems. The dual (and often
competing) goals are to provide new frameworks which will be expressive
enough to capture realistic situations, and yet sufficiently formal that the
accuracy of derived conclusions can be trusted.
_____
IST-8603214
$85,583 - 12 mos.
William Shaw
University of North Carolina
An Evaluation and Comparison of Term and Citation Indexing
- - -
Text documents are produced and stored in vast quantities today. Consequently,
it is nearly impossible to locate relevant text documents for any particular
purpose without computerized searching. For reasons of efficiency, computer
systems for searching documents do not use the entire text of such documents;
only a compact representation of each document is stored in memory, along with
the information necessary to locate the original text if it should be needed.
This research investigates two of the more common components of compact
representations for documents: A representation based on the terms contained in
the text, and a representation based on the documents which the text cites.
Both of these representations are evaluated by extensive judgements (by human
experts) of the relevance of documents retrieved using them. The research
illuminates the optimal use of each alternate type of representation, as well as
a comparison between the two alternatives. The importance of the research is
that it provides a solid base of empirical evidence and a benchmark document
collection for evaluating information retrieval strategies. Although new
architectures for document representation and retrieval may make some of the
specific style of queries obsolete, the value of the test collection and the
insights about intrinsic content (term) versus extrinsic context (citation)
analysis for documents will be valuable for future work.
_____
DMS-8606178
$20,000 - 12 mos.
Paul C. Shields
University of Toledo
Mathematical Sciences: Entropy in Ergodic Theory, Graph Theory and Statistics
- - -
Professor Shields was one of the first American mathematicians to become
actively involved in the subject of information theory, and he has been one of
the creative contributors. His work cuts across traditional disciplinary boun-
daries in mathematics, for it utilizes ideas from ergodic theory, information
theory, statistics, data compression, graph theory, diffusion theory, and com-
puter science. He proposes here to continue his highly original recent work in
an exciting international collaboration with some of the world's outstanding
information theorists. The project involves entropy and asymptotic estimates
for algorithms for compression of binary data in computer science, tests for
statistical independence, and applications in the communications field. The
latter might ultimately impact the current state of our knowledge in speech
coding and recognition, spectral estimation, and pattern recognition. This is
exciting, innovative, multidisciplinary work that possesses the added value of
international cooperation among world experts.
_____
IST-8607849
$101,839 - 12 mos.
Edward Smith
BBN Laboratories, Inc.
A Computational Approach to Decision-Making
- - -
The purpose of this collaborative research is to develop a theory of how humans
make decisions. The theory is developed as a computational theory, using the
representations and processes currently prevalent in cognitive science and
artificial intelligence research. The theory explains the formation of complex
concepts. Additionally, it accounts for people's incorrect estimates of the
likelihood with which events will occur. The theory is tested through
psychological experimentation. Knowledge about how people make decisions and
estimate probabilities is useful to all decision makers. Additionally, a
computational theory of the process allows the development of computer based
decision-making aids.
_____
IST-8609599
$80,963 - 12 mos.
Paul Smolensky
University of Colorado at Boulder
Inference in Massively Parallel Artificial Intelligence Systems
- - -
The purpose of this research is to study how parallel Artificial Intelligence
(AI) systems can make inferences which allow full use of the information in the
computer system's memory. The approach here is to synthesize the varying
methods of inference currently used in the field in order to formulate general
principles of inference in parallel systems. The synthesis is accomplished by
applying the varying inference methods to a set of inference problems and
developing the resulting set of core models. These models are studied through
mathematical analysis and computer simulation and the relationships among
them are found. Artificial intelligence systems need to be able to make
inferences in order to use whatever knowledge they have stored. This full use of
knowledge is one of the main ways in which AI systems are powerful. This
research deals with inference methods and contributes to the development of
more sophisticated computer systems.
_____
IST-8644907
$15,634 - 12 mos.
Frederik Springsteel
University of Missouri
Formalization of Entity-Relationship Diagrams
- - -
The design of the logical structure of a database is an important component of
the design of many information systems, and the entity-relationship model is
frequently used as a tool in such design. Most of the work on this approach has
emphasized its practical applications rather than its theoretical aspects. The
purpose of this research is to develop more formal analyses of the assumptions
and benefits of this model and to relate it to other models such as the rela-
tional model, which are better understood. The significance of this research
lies in its potential to contribute to the theory and practice of database
design.
_____
IST-8640120
$66,004 - 12 mos.
Robert E. Stepp
University of Illinois at Urbana
Discovering Underlying Concepts in Data Through Conceptual Clustering
- - -
The purpose of this research is to develop theoretical principles, algorithms,
and practical methods for the discovery of underlying concepts in descriptions
of objects or situations through the use of conceptual clustering. A computer
system is being developed that will build a conceptual classification for
descriptions of objects. It acts by generating concepts that describe object
classes and then partitioning the given objects into the appropriate classes.
The generated concepts are encoded as conjunctive statements in an extended
predicate calculus notation and are optimized with respect to a user-supplied
classification evaluation function. The techniques are evaluated by examining
selected problems, such as discovering classes of simple organic molecules and
discovering kinship units within the kinship network. The significance of the
research lies in its potential to contribute to the design and development of
computer-based knowledge resource systems.
_____
IST-8516313
$60,907 - 12 mos.
Richmond H. Thomason
Mellon-Pitt-Carnegie Corp.
Nonmonotonic Reasoning
- - -
Classical logic is inadequate in many ways for modeling real-world reasoning by
computers. In particular, classical logic is monotonic - adding information or
premises never reverses previously valid conclusions. By contrast, the
appearance of new information in real world situations often causes previous
conclusions or judgements to be reversed. This research, an interdisciplinary
collaboration of computer scientists, philosophers, and logicians, explores
real-world, nonmonotonic reasoning in intelligent computer systems. In
particular, the research investigates how intelligent systems can arrive at
reasonable conclusions by adding assumptions to their current information, and
how intelligent computer programs should cause assumptions to be inherited in
individual cases of general situations. The research provides significant
insight into the strengths and weaknesses of established logical approaches to
reasoning, as well as breaking ground in the implementation of realistic
reasoning networks in computer systems.
_____
IST-8516330
$63,854 - 12 mos.
David S. Touretzky
Carnegie-Mellon University
Distributed Representations for Symbolic Data Structures
- - -
In this project the investigator is studying the representation of symbols in
parallel computers. Symbols are being represented by the presence of activity
in the (processing units) of the computer. Each processing unit contributes to
the representation of many symbols and particular symbols are identified by
activity in some subset of units. This particular method of representation is
called a "parallel distributed" method. The investigator is studying the
representation of symbols in parallel computers by implementing some common
symbolic structures in a parallel computer called the Boltzmann machine.
Additionally, he is studying the mathematical properties of his implementations.
Parallel computers offer a plausible theory of the brain. Using a parallel
computer to implement the kind of symbolic data structure needed for theories
of cognition allows us to link theories of mind with theories of brain. Making
this link, will give us more complete theories of cognition and better computer
implementations of these theories, ultimately producing better artificial
intelligence systems.
_____
IST-8517289
$164,786 - 12 mos.
Joseph F. Traub
Columbia University
The Information Level: Effective Computing with Partial, Contaminated, and
Costly Information
- - -
The information available to solve real-world problems is usually only
incomplete and contaminated by noise or systematic error. The principal
investigators are developing in this research a theory about such problems,
where partial and contaminated information must be used as well as possible.
Potential applications for the theory, which is called "Information Based
Complexity Theory" range from medical imaging and robot vision to economics.
The key goal of this theory is to explain how the accuracy of solving a given
problem is related to the amount and kind of information available. The project
will be significant both for the general mathematical methods it develops and
for the insights it provides into formulating and refining computer systems and
algorithms.
_____
IST-8544806
$121,222 - 12 mos.
Jeffrey D. Ullman
Stanford University
Implementation of Logical Query Languages for Databases
- - -
This research will develop a logic language for databases that will be
substantially more powerful than current formal languages such as relational
calculus. This new language will allow for the use of a knowledge base of
rules, as well as rules for performing integrity and security functions. This
new language will be a form of parallel prolog, an important artificial intelli-
gence language. The significance of this research lies in the fact that it will
provide a very natural language for querying databases.
_____
IST-8511348
$30,383 - 12 mos.
Kenneth Wexler
University of California at Irvine
Learnability and Parsability (see description of award to Berwick)
_____
IST-8514890
$80,000 - 12 mos.
R. Wilensky and R. Alterman
University of California at Berkeley
Adaptive Planning
- - -
In this project the PIs look at issues concerning automated planning systems.
They are developing methods for "adaptive planning" (using familiar plans in
unfamiliar situations). The issue is being addressed through the development of
a computer system in which old plans are first generalized and then
appropriately specialized. Robots need to plan in order to act independently.
Adaptive planning allows a system to plan in novel situations. By addressing
issues of adaptive planning, this project works towards the long-range goal of
building robots which can function in situations that they have not previously
encountered.
_____
IST-8600788
$81,660 - 12 mos.
Robert T. Winkler
Duke University
Combining Dependent Information: Models and Issues
- - -
In realistic applications of computers to modeling knowledge and decision pro-
cesses, information is often available only partially about events of interest.
In addition, many sources may contribute information about the same event, and
these sources in turn are generally not independent of each other. This research
investigates ways in which such uncertain, overlapping, interrelated information
about events may be combined automatically to improve the certainty of
knowledge and the appropriateness of decision-making. A key component of the
research is to test alternative formal models of uncertain information by
experiments in real world applications. This research is significant both for
the explication and comparision of various formal models of uncertainty, and for
the critical feedback obtained by observing the performance of competing models
in realistic situations.
_____
IST-8644767
$38,474 - 12 mos.
Ronald R. Yager
Iona College
Specificity Measures of Information in Possibility Distributions
- - -
Possibility distributions provide a formalism for representing some types of
uncertainty in information. A measure of the information content in a
possibility distribution is introduced; this measure is called a specificity
measure. The objective of this research is the investigation of properties,
uses, and formulations of the specificity measures associated with possibility
distributions and fuzzy subsets. The trade-offs involved in providing
information that is both specific and correct are also investigated. The
significance of this research lies in its potential contribution to the
development of computer based systems which can handle imprecise and
uncertain information.
_____
IST-8644435
$50,878 - 12 mos.
Po-Lung Yu
University of Kansas
Habitual Domain Analysis for Effective Information Interface and Decision
Support
- - -
Many nontrivial decision and conflict problems cannot readily be solved by
traditional optimization and game theoretic techniques. The concepts of second
order games and habitual domains can be used to approach such problems. This
research investigates several topics in the development and use of habitual
domains, which provide a framework for models of individual and organizational
users of information systems. Specific goals include identifying effective
means for specifying and using habitual domains and developing approaches to
using them in information systems. The significance of this research lies in
its potential for improving computer-based decision systems.
_____
IST-8642900
$108,182 - 12 mos.
Lotfi A. Zadeh
University of California at Berkeley
Management of Uncertainty in Expert Systems
- - -
Much of the information which is resident in the knowledge base of a typical
expert system is imprecise or incomplete. This research provides an approach,
based upon the use of fuzzy logic, for handling this problem. The approach
provides a computational framework for dealing with fuzzy quantifiers, e.g.,
most, many, almost, all, etc., and thereby makes it possible to compute with
imprecisely known probabilities and certainty factors. In this approach the
propositions which form the knowledge base of an expert system may be
expressed in a canonical form which places in evidence the variables which are
constrained by the constituent proposition. From the canonical forms, one can
construct a global possibility distribution which reduces the deduction of a
conclusion to the solution of a nonlinear system. This research will provide an
approach for the systematic inclusion in expert systems of the types of
imprecise rules used by experts.
_____
IST-8605163
$19,776 - 12 mos.
Maria Zemankova
University of Tennessee at Knoxville
Travel to the International Conference on Information Processing and
Management of Uncertainty in Knowledge-Based Systems
- - -
This award supports travel funds for 15 U.S. participants for the International
Conference on Information Processing and Management of Uncertainty in
Knowledge-Based Systems. The conference takes place in Paris, France on June
30, 1986 through July 4 1986. The conference will be co-sponsored by the
International Fuzzy Systems Association. The conference topics cover
uncertainty management, fuzzy sets, possibility measures, and the mathematical
theory of evidence. The conference provides an opportunity for strengthening
the quality of research in reasoning with uncertainty, as well as facilitating
international communication in the area.
_____
IST-8600616
$97,727 - 12 mos.
Pranas Zunde
Georgia Institute of Technology
A Study of Word Association Aids in Information Retrieval
- - -
This research investigates the usefulness of word associations - the additional
words an individual can think of in response to an initial stimulus word - in
assisting information retrieval. Advanced information retrieval systems of the
future will be expected to go beyond simply sorting and matching terms with
documents. These systems must become capable of understanding and reasoning,
both about the knowledge contained in a collection of documents and about the
user's intentions. As investigated in this proposal, knowledge of word
associations represents one such type of understanding an information retrieval
system may exhibit to enhance its performance. The significance of this project
is that it probes a new dimension of semantic content for keyword searching,
virtually unexplored in information retrieval studies to date. User/system
interaction observations gained in the process are likely to have additional
impact on information retrieval concepts.
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END OF IRList Digest
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