SALIENT SENTENCE IDENTIFICATION IN TEXT

Award Information
Agency:
Department of Defense
Branch
Office of the Secretary of Defense
Amount:
$100,000.00
Award Year:
2012
Program:
STTR
Phase:
Phase I
Contract:
N00014-12-M-0397
Award Id:
n/a
Agency Tracking Number:
O11B-TD1-4005
Solicitation Year:
2011
Solicitation Topic Code:
OSD11-TD1
Solicitation Number:
2011.B
Small Business Information
8260 Greensboro Drive, Suite 600, McLean, VA, -
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
081093775
Principal Investigator:
AlanBreitler
Principal Investigator
(301) 649-5031
alan.breitler@ddlomni.com
Business Contact:
NancyDoolin
Corporate Contracting Officer
(703) 918-4335
nancy.doolin@ddlomni.com
Research Institute:
Virginia Tech
Chris North
Dept of Computer Science
2202 Kraft Drive
Blacksburg, VA, 24061-0106
(540) 231-2458

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.

* information listed above is at the time of submission.

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