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Controlled English for Effective Communication during Coalition Operations
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In: DTIC (2013)
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| 2 |
Enabling Efficient Intelligence Analysis in Degraded Environments
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In: DTIC (2013)
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| 3 |
An Approach Using MIP Products for the Development of the Coalition Battle Management Language Standard
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In: DTIC (2013)
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| 4 |
Automated Extraction and Characterisation of Social Network Data from Unstructured Sources -- An Ontology-Based Approach
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In: DTIC (2013)
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| 5 |
Entity List Completion Using Set Expansion Techniques
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In: DTIC (2011)
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| 6 |
Multilingual Content Extraction Extended with Background Knowledge for Military Intelligence
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In: DTIC (2011)
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| 7 |
Recognizing Connotative Meaning in Military Chat Communications
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In: DTIC (2009)
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| 8 |
Delft University at the TREC 2009 Entity Track: Ranking Wikipedia Entities
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In: DTIC (2009)
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| 9 |
Patent Retrieval in Chemistry based on Semantically Tagged Named Entities
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In: DTIC (2009)
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| 10 |
Applying A Formal Language of Command and Control For Interoperability Between Systems
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In: DTIC (2008)
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| 11 |
Odds of Successful Transfer of Low-level Concepts: A Key Metric for Bidirectional Speech-to-Speech Machine Translation in DARPA's TRANSTAC Program
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In: DTIC (2008)
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| 14 |
A Methodology to Predict Specific Communication Themes from Overall Communication Volume for Individuals and Teams
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In: DTIC (2006)
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| 16 |
Deep Versus Broad Methods for Automatic Extraction of Intelligence Information From Text
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In: DTIC (2005)
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Abstract:
Extraction of intelligence from text data is increasingly becoming automated as software and network technology increases in speed and scope. However, enormous amounts of text data are often available and one must carefully design a data mining strategy to obtain the relevant nuggets of gold from the mountains of useless dross. Two strategies can be tried. A deep approach is to use a few strong clues to find reasonable sentence candidates, then apply linguistic restrictions to find and extract key information (if any) surrounding the candidates. A broad approach is to focus on large numbers of weaker clues such as specific words whose implications can be combined to rate sentences and present those of high likelihood of relevance. In the work reported here, we tested the deep approach on military intelligence reports about enemy positions, which were relatively short text extracts, and we tested the broad approach on news stories from the World Wide Web involving terrorism, which presented a large volume of text information. ; Presented at the International Command and Control Research and Technology Symposium (ICCRTS) (10th) held in McLean, VA on 13-16 Jun 2005. Published in the Proceedings of the International Command and Control Research and Technology Symposium (ICCRTS) (10th), 2005. Briefing charts included. Sponsored in part by DARPA. The original document contains color images.
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Keyword:
*EXTRACTION; *INFORMATION RETRIEVAL; *MILITARY INTELLIGENCE; *NATURAL LANGUAGE; *TEXT INFORMATION; AUTOMATIC; DATA MINING; Information Science; INTERNET; Linguistics; Military Intelligence; PARSERS; PARSING; SEMANTICS; SENTENCES; SYMPOSIA; SYNTAX; WORDS(LANGUAGE)
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URL: http://www.dtic.mil/docs/citations/ADA464116
http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA464116
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| 17 |
Quality of Service-Driven Requirements Analyses for Component Composition: A Two-Level Grammar++ Approach
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In: DTIC (2005)
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| 19 |
Inferring Parts of Speech for Lexical Mappings via the Cyc KB
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In: DTIC (2004)
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| 20 |
Analysis of Free-Form Battlefield Reports with Shallow Parsing Techniques
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In: DTIC AND NTIS (2004)
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