SBIR Phase I:Building a Flexible, Technology Adaptive Architecture to Support Processing of Content by Knowledge Workers

Award Information
Agency:
National Science Foundation
Amount:
$150,000.00
Program:
SBIR
Contract:
1013935
Solitcitation Year:
2010
Solicitation Number:
NSF 09-609
Branch:
N/A
Award Year:
2010
Phase:
Phase I
Agency Tracking Number:
1013935
Solicitation Topic Code:
IC
Small Business Information
Red Lion
3604 Vale Station Rd, Oakton, VA, 22124
Hubzone Owned:
N
Woman Owned:
N
Socially and Economically Disadvantaged:
N
Duns:
145858168
Principal Investigator
 Eric Koefoot
 PhD
 (703) 472-8337
 ekoefoot@yahoo.com
Business Contact
 Eric Koefoot
Title: PhD
Phone: (703) 472-8337
Email: ekoefoot@yahoo.com
Research Institution
N/A
Abstract
This Small Business Innovation Research (SBIR) Phase I Project addresses the gap between the capabilities of today's natural language processing systems and the accuracy requirements of knowledge workers (analysts and researchers) in language-sensitive fields such as public relations, foreign affairs, and crisis management. Knowledge workers in many organizations monitor and analyze print and web coverage for content of interest. When the volume of search results is large, some filter, classify and score the results with Natural Language Processing (NLP) systems using complex libraries of words, patterns, and context-specific algorithms. However, users complain that these systems fall short of desired accuracy, missing rhetorical devices such as irony, sarcasm, metaphors, double entendre, and improperly interpreting references. Users with high thresholds for accuracy thus turn to manual processes to either supplement or substitute for technology. This project will test a prototype architecture allowing rapid insertion, testing, and adaptation of text analysis algorithms and a workflow process efficiently integrating human review judgment. Once commercialized, the system will enable more rapid adoption of technology by knowledge workers. In fields with high accuracy requirements, the need for human judgment has constrained technology use to discrete areas like search, while in subsequent processing steps, analysts must manually capture, classify, score, analyze, and report on the output.

* information listed above is at the time of submission.

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