leff@smu.CSNET.UUCP (02/18/87)
IST-8603407
$27,000 - 12 mos.
Robert D. Rodman
North Carolina State University
Dialog Processing for Voice Interactive Problem Solving
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For several years now, Professor Robert D. Rodman and Professor Alan W.
Biermann at Duke University have collaborated on research efforts
directed at voice interactive computing systems. They are studying the
dynamics of human-machine voice interactive computing systems. They are
studying the dynamics of human-machine voice interactive problem solving
with the goal of constructing a fast and efficient voice interactive
computer system. The voice interactive dialogue machine will allow the
user to display data on a computer terminal and manipulate it using
voice commands and touch sensitive inputs to the screen. Each command
will result in immediate action visible on the screen allowing the user
to confirm that a proper response has occured. A natural language
computer (NLC) was used and considerable experience has been gained with
subjects using the voice equipment. Among the accomplishments has been
the integration of a voice and touch facility into the NLC system and
the modification of the system for the idiosyncracies of voice and touch
input. The initial implementation of the voice interactive dialogue
machine address the equipment repair problem where the human provides
the eyes and mechanical skills to work on a failing device and the
machine has the appropriate functional diagrams and debugging
algorithms. The major issues to be addressed concern finding
characterizations for typical human-machine task oriented dialogues,
developing formalisms for understanding them and for implementing them
in a computer, and measuring the performance of human-machine
cooperative efforts when utilizing such a grammar-driven voice
conversational machine.
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IST-8640925
$198,800 - 12 mos.
Naomi Sager
New York University
Language As a Database Structure
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The proposal is based on past work of the Principal Investigator and
associates, which include: the development of a computer grammar and
program for analyzing free-text documents and converting their contents
into a structured form; methods of identifying the fact-structures and
text- wide regularities in specific subject domains ("sublanguages");
and experimental results in mapping the computer-structured textual
information into databases of the network and relational types. The
database experiments showed that certain necessary features of language
information did not fit the existing models. This result, along with
the accumulated knowledge of the major mechanisms of language
information, have led to this project to develop a new database model in
which the informational relations of language have a direct
correspondence in constructs of the model. Using the techniques of
database design, generalized Linguistic Schemata (LS's) will be
developed for sample computer-structured language databases; the LS's
will be specified in a Linguistic Schemata Decription Language (LSDL) to
be designed for this purpose. Implementation of some of the schema
elements will be undertaken in the form of enhancements to a relational
data model, in particular, for treating the recursive connective
structure of language information and the time-order relations in
narrative.
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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.
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IST-8610293
$80,630 - 12 mos.
Glenn R. Shafer
University of Kansas Main Campus
Belief Functions in Artificial Intelligence
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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.
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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.
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DMS-8606178
$20,000 - 12 mos.
Paul C. Shields
University of Toledo
Mathematical Sciences: Entropy in Ergodic Theory, Graph Theory and
Statistics
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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 boundaries in mathematics, for it utilizes ideas from
ergodic theory, information theory, statistics, data compression, graph
theory, diffusion theory, and computer 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.
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IST-8607849
$101,839 - 12 mos.
Edward Smith
BBN Laboratories, Inc.
A Computational Approach to Decision-Making
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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