
NSF Org: |
TI Translational Impacts |
Recipient: |
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Initial Amendment Date: | July 12, 2002 |
Latest Amendment Date: | October 25, 2004 |
Award Number: | 0216213 |
Award Instrument: | Standard Grant |
Program Manager: |
Juan E. Figueroa
TI Translational Impacts TIP Directorate for Technology, Innovation, and Partnerships |
Start Date: | July 15, 2002 |
End Date: | June 30, 2005 (Estimated) |
Total Intended Award Amount: | $499,764.00 |
Total Awarded Amount to Date: | $880,105.00 |
Funds Obligated to Date: |
FY 2005 = $380,341.00 |
History of Investigator: |
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Recipient Sponsored Research Office: |
48 Wall Street, 11th Floor New York NY US 10003-4602 (212)918-4412 |
Sponsor Congressional District: |
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Primary Place of Performance: |
48 Wall Street, 11th Floor New York NY US 10003-4602 |
Primary Place of
Performance Congressional District: |
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Unique Entity Identifier (UEI): |
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Parent UEI: |
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NSF Program(s): | SBIR Phase II |
Primary Program Source: |
app-0105 |
Program Reference Code(s): |
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Program Element Code(s): |
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Award Agency Code: | 4900 |
Fund Agency Code: | 4900 |
Assistance Listing Number(s): | 47.084 |
ABSTRACT
This Small Business Innovation Research (SBIR) Phase II project will enhance the company's approximate record-matching software, the Maximum Entropy De-Duper, MEDD(TM) by: 1) Enhancing MEDD's performance using advanced standardization tools to convert data, such as names and addresses, into standard formats; 2) Expanding MEDD's market by matching business names not only person names; 3) Internationalizing MEDD to support Canadian French or Mexican Spanish; 4) Benchmarking MEDD against the competition and developing a methodology to objectively compare matching systems; 5) Reducing MEDD's reliance on training data to ease deployment; producing the best possible "untrained" models that will adapt and improve through client use; 6) Applying the latest advances in machine learning technology to the record-matching problem to increase competitive advantage; and 7) Speeding MEDD word blocking with a fast, innovative memory-resident data-store.
MEDD's market includes all business and government entities that store mission-critical information in large databases. The project will yield societal benefits for public health, anti-terrorist efforts, epidemiological research, the U.S. Census, and the data quality of records relating to racial and ethnic minorities.
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