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SALIENT SENTENCE IDENTIFICATION IN TEXT
- Small Business Information
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Woman-Owned: NoMinority-Owned: NoHUBZone-Owned: No
- Phase 1
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Fiscal Year: 2012Title: SALIENT SENTENCE IDENTIFICATION IN TEXTAgency / Branch: DOD / OSDContract: N00014-12-M-0397Award Amount: $100,000.00
Abstract:
DDL OMNI Engineering and Virginia Polytechnic Institute and State University will use our Salient Sentence Identification in Text (S2I2T) algorithm for the automated identification and characterization of the salient context related content in text documents. Our approach uniquely identifies salience from sentences within the documents, producing an easy to read result. Further, our approach allows the user to define the context directly at execution of the algorithm to match user entered terms against sentences identified as salient. During Phase I our approach"s effectiveness will be validated via experiments comparing algorithmic results to human recognized salience. Additionally, we will continue refinements to our S2I2T prototype to improve algorithm performance and statistically validate the performance improvements.Small Business Information at Submission:Principal Investigator:
Alan L. Breitler
Principal Investigator
(301) 649-5031
alan.breitler@ddlomni.comResearch Institution Information:DDL Omni Engineering, LLC
8260 Greensboro Drive, Suite 600 McLean, VA -EIN/Tax ID: 541825099DUNS: N/ANumber of Employees:Woman-Owned: NoMinority-Owned: NoHUBZone-Owned: NoVirginia Tech
Dept of Computer Science
2202 Kraft Drive
Blacksburg, VA 24061-0106Contact: Chris NorthContact Phone: (540) 231-2458
Award Information
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Agency: Department of Defense |
Branch: Office of the Secretary of Defense |
Award ID: |
Program Year/Program: 2012 / STTR |
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Agency Tracking Number: O11B-TD1-4005 |
Solicitation Year: 2011 |
Solicitation Topic Code: OSD11-TD1 |
Solicitation Number: 2011.B |