Interesting proposals to think about, discuss, and use as a benchmark
for OHS/DKR development..
DISCOVERY MACHINE, INC.
265 Dogwood Ridge Road
Montgomery, PA 17752
Phone: (570) 547-6774
PI: Todd Griffith
Topic#: DARPA 00-013
http://www.sbirsttr.com/SbirMisc/abs001DARPA.htm
Title: Intelligent Adaptive Software Construction
Abstract:
The objective of this proposal is to show the feasibility of building a
set of software tools enabling researchers (i.e. scientists, inventors,
designers, planners, or investors) to represent multiple problem-solving
strategies. These DiscoveryTools will allow researchers to quickly and
cheaply automate discovery processes thereby increasing the productivity
of R&D budgets. The tools will provide a graphical user interface for
encoding the strategies (i.e. tasks, methods, and knowledge) required to
solve specific problems, and will allow the users to "run" these
strategies over sets of data. Most software tools attempt to retrieve or
display knowledge from databases so that researchers can act on that
knowledge. This research attempts to show that this can be done the
other way around. Instead of supplying researchers with knowledge to
solve problems, supply a program with strategies to act on the knowledge
to which it has access. DiscoveryTools will allow researchers to specify
multiple high-level strategies, each of which can be used to solve some
set of problems. The tools assist researchers in explicating their
problem-solving tasks as a hierarchy of methods and subtasks. In
essence, DiscoveryTools will multiply expert researchers leaving more
time and money available to pursue the most promising options.
STOTTLER HENKE ASSOC., INC.
1660 S. Amphlett Blvd., Suite 350
San Mateo, CA 94402
Phone: (206) 545-1478
PI: Ronald Braun
Topic#: DARPA 00-012
http://www.sbirsttr.com/SbirMisc/abs001DARPA.htm
Title: Ontology-Based Information Extraction from Free-Form Text
Abstract:
We propose an innovative combination of machine learning techniques
coupled with a novel end-to-end system architecture built around a
shared domain ontology to permit ontology-based information extraction
(IE) from free text. Our Ontology-Based IE (OBIE) system will
significantly increase end-to-end recall for the IE task while
maintaining or improving precision. OBIE will accomplish this by
enabling interaction between different levels of the IE processing
pipeline simultaneously through a shared ontology. IE components will be
developed to demonstrate increases in recall permitted by the inclusion
of hierarchical knowledge in their learning algorithms. Active learning
and bootstrapping algorithms will be extended to automatically learn the
ontology of a new domain, to assist in training the IE components, and
to reduce the burden of annotation on the end-user. Performance metrics
in a variety of system configurations will allow a characterization of
performance gains enabled by the proposed architecture. Phase I research
and development of a proof-of-concept limited prototype will demonstrate
the feasibility and utility of OBIE's ontology-based IE capability and
will lay the groundwork for its Phase II implementation.
APTIMA, INC.
600 W. Cummings Park, Suite 3050
Woburn, MA 01801
Phone: (781) 935-3966
PI: Steven Hess
Topic#: NAVY 00-086
http://www.sbirsttr.com/SbirMisc/abs001NAVY.htm
Title: Metrics for Evaluation of Cognitive Architecture-Based
Collaboration Tools
Abstract:
The practice of modern intelligence analysis is increasingly becoming a
team effort, requiring distributed teams of experts, to collect, filter,
and collaboratively fuse data into coherent responses to Requests for
Information (RFI's). To quickly generate a team response, analysts must
achieve a shared understanding of the problem and the best ways to
assemble data for effective communication back to a consumer.
Information Technology (IT) suited to the domain of intelligence
analysis, will have to support new collaboration strategies that allow
analysts to represent and share evolving understandings of the world,
interact with data and link it to emerging arguments, and collaborate to
combine related argument threads into a single response to consumers.
The current proposal seeks to blend contemporary theories of team
cognition with computational modeling techniques and evolving
collaboration tools to prototype and assess an innovative solution that
allows analysts to generate collaborative responses through the natural
process of recognizing and critically evaluating the value of evidence
to hypotheses about a situation. The resulting tool will help analysts
focus on relevant data, help them organize data, and provide
computational tools that insure coherence in final response and assess
the impacts of evidence on dynamic team understanding. The results of
the proposed work will be a prototype tool supporting collaborative
argument construction through the natural process of critically
evaluating the value of evidence to competing hypotheses about a
situation. The applicability of our proposed tool can be easily extended
beyond the targeted domain of intelligence analysis. At the end of Phase
I we will have a functional demonstration of the tool, and will be well
positioned to demonstrate the generality of our solution for other
application domains, both military (e.g., military C2) and civilian
(e.g., scientific collaboration, journalism).
KNOWLEDGE ANALYSIS TECHNOLOGIES, LLC
4001 Discovery Drive Suite 390
Boulder, CO 80303
Phone: (303) 545-9092
PI: Thomas K. Landauer, Ph.D.
Topic#: NAVY 00-088
http://www.sbirsttr.com/SbirMisc/abs001NAVY.htm
Title: Dynamic SuperManuals with Latent Semantic Analysis
Abstract:
The object is to be able to design potentially order-of-magnitude better
ways to dynamically customize information for given jobs and individual
maintainers. This project will address three interrelated issues: (1)
the optimum organization of maintenance-aiding information in text, (2)
the presentation of the best information in the best order depending on
the current knowledge and need of the user, and (3) the best handling of
complex graphics under the constraint of low resolution, small-screen
technology. In Phase I we propose three activities: (a) Review the
literature for the last five years on design, usability, usefulness, and
practical experience with systems for organizing information and for
aiding and individualizing information finding for maintenance and
related jobs,
(b) Create partial prototypes or mock ups to demonstrate the design and
intent of representative new features, functions, and enhancements based
on the new computer text-understanding technology, Latent Semantic
Analysis (LSA), coupled with the empirically proven design, functions
and features of the SuperBook hypertext manual browser, (c) Propose a
new overall design for a browser with LSA, enhanced dynamic information
aids and advanced graphics functions to be prototyped and evaluated in
Phase II. Maintenance of increasingly complex technological systems is a
critical and difficult problem for defense, government and private
sector organizations.
Traditional print media and current on-line systems are not adequate.
The expected outcome of this project is identification of the optimum
organization and presentation of maintenance information in job-aiding,
and design of potentially order-of-magnitude better ways to dynamically
organize, present, and customize information for given jobs and
individual maintainer levels of expertise. A successful technology of
this kind will be the basis of a high revenue Internet-based service and
licensing business, and will result in major cost savings and product
improvements for a wide spectrum of large industries, from
telecommunications to computer and network systems to airline
operations.
SENTAR, INC.
4900 University Square Suite 8
Huntsville, AL 35816
Phone: (256) 704-0863
PI: Andrew Schooley
Topic#: BMDO 00-010
http://www.sbirsttr.com/SbirMisc/abs001BMDO.htm
Title: Agent-based Knowledge-design Assistance (AKA)
Abstract:
Over the past decade the growth of data, information and knowledge has
been accelerating and search engines and simple automation have proven
to be inadequate at addressing the ensuing information glut. This points
to the opportunity to apply Intelligent Agent technology to the problem
by using them as assistants in managing data/information and developing
the needed knowledge. Our proposed "Agent-based Knowledge-design
Assistance (AKA) Environment" concept is a significant opportunity for
the creation of an integrated environment for rapidly formulating
knowledge bases utilizing agents in conjunction with design pattern
concepts. The AKA concept provides an environment for hosting knowledge
design pattern agents, called Template Agents (TA) and using XML as a
run-time tool for conversion, storage, and maintenance of knowledge. The
environment presents the user with an integrated view of the available
TAs using an orchestrating agent, called Design Assistant Agent (DAA),
which manages, arbitrates and negotiates with the TAs. All the agents
act autonomously to promulgate their design pattern and agenda within
the context of the AKA environment and the knowledge base content. We
believe that the application of design patterns with the AKA environment
will reduce risk, lead-time, complexity and level-of-effort associated
with creation of knowledge and management of information. We expect the
AKA project to be on a FastTrack due to commercialization plans of our
teammates, Boeing and KnoWave, both of whom have immediate need for the
technology. The AKA is targeted at the "solution seeking" market which
is projected to grow from $240M in 2000 to about $1.9B in 2002.
CHARLES RIVER ANALYTICS, INC.
725 Concord Avenue
Cambridge, MA 02138
Phone: (617) 491-3474
PI: Dan L. Grecu
Topic#: NIMA 00-002
Title: Agent for Intelligent Analysis Support
http://www.sbirsttr.com/SbirMisc/alld001.htm
Abstract:
Intelligence analysts have to respond to the information needs of
commanders and decision makers leading military forces into potential
engagements in a diversity of scenarios and in a large variety of
geographical, political and social contexts. For NIMA this task requires
the semantic integration of the imagery and geospatial analysis with
large and diverse data repositories and real-time information. To
support this information retrieval and integration process we propose
the development of an Agent for Intelligent Analysis Support. The agent
will assist analysts by semantically representing the context of the
analysis problem and using it to support the intelligent information
retrieval process. The agent will also amplify the information retrieval
process by using domain ontologies, and will suggest additional
information sources based on semantic associations with the problem
context. The proposed approach will enable imagery and geospatial
analysts to respond to queries anchored in the semantics of concrete
tactical situations, and to complete their responses with data and
knowledge available from intelligence channels, technical databases, and
electronic knowledge repositories. The development effort will comply
with DII-COE standards and integrate with the toolsets that are
currently part of the United States Imagery & Geospatial Information
Systems framework. The proposed effort has significant potential
applications, both as a technology and as an end-product. As a
technology the approach will provide tools for context-based semantic
information retrieval from real-time information streams and
repositories, in response to the decision-makers increasingly complex
information needs. Candidate domains range from command and control
centers, to market analysis, and to assessment in complex medical
domains. As an end-product, the associated knowledge engineering tools
will support on-going DoD efforts to develop multi-domain collections of
knowledge bases, analysis and reasoning tools, that will enable the
warfighter to take rapid, and informed decisions in complex, real-time
situations.
INFORMATION EXTRACTION & TRANSPORT
1911 N. Ft. Myer Drive, Suite 600
Arlington, VA 22209
Phone: (703) 841-3500
PI: Ed Wright
Topic#: NIMA 00-003
Title: A Computational Hypothesis Space for Geospatial Information
http://www.sbirsttr.com/SbirMisc/alld001.htm
Abstract:
This research will develop a revolutionary advance in database concepts
for geospatial information that will support future intelligence
analysts in providing responsive support to military operations. The
concept will provide a computational hypothesis space that provides
capabilities for advanced reasoning about features distributed in time
and space based on diverse sources of information. The proposed
capability will support today's intelligence analyst with the
challenging task of providing responsive support to military operations.
When a crisis arises suddenly in an area of the world where little
initial data is available, the capability will provide rapid access to
imagery, spatial data, text, and intelligence reports from diverse
heterogeneous sources with wide variations in currency and quality. Over
time, as crisis develop, a vast amount of current and detailed data is
continuously collected and generated by a wide range of sensors and
production systems. The proposed database architecture will also provide
capabilities to correlate and fuse all of this information so analysts
can reason about the military situation and provide a high level of
support to commander's operational requirements. The revolutionary
database concepts developed under this research will support advanced
reasoning with geospatial information in a wide range of military and
civilian problem domains. Applications include intelligence analysis,
operational planning, resource management and exploration, and
transportation and urban planning.
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