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Multilingual Content Extraction Extended with Background Knowledge for Military Intelligence
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In: DTIC (2011)
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| 42 |
Maritime Domain Awareness via Agent Learning and Collaboration
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In: DTIC (2010)
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| 43 |
Related Entity Finding: University of Waterloo at TREC 2010 Entity Track
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In: DTIC (2010)
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| 44 |
Projecting Grammatical Features in Nominals: Cognitive Processing Theory & Computational Implementation
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In: DTIC (2010)
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| 45 |
The Impact of Interpretation Problems on Tutorial Dialogue
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In: DTIC (2010)
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| 46 |
A Multi-Disciplinary University Research Initiative in Hard and Soft Information Fusion: Overview, Research Strategies and Initial Results
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In: DTIC (2010)
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| 47 |
Enabling Multinational Communications with CENTRIXS
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In: DTIC (2010)
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| 48 |
Towards Real-time Program Awareness via Lexical Link Analysis
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In: DTIC (2010)
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| 49 |
TIACRITIS System and Textbook: Learning Intelligence Analysis through Practice
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In: DTIC (2010)
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| 51 |
A Novel Framework for Related Entities Finding: ICTNET at TREC 2009 Entity Track
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In: DTIC (2009)
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| 52 |
Recognizing Connotative Meaning in Military Chat Communications
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In: DTIC (2009)
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Abstract:
Over the last five to seven years the use of chat in military contexts has expanded quite significantly, in some cases becoming a primary means of communicating time-sensitive data to decision makers and operators. For example, during humanitarian operations with Joint Task Force-Katrina, chat was used extensively to plan, task, and coordinate predeployment and ongoing operations. The informal nature of chat communications allows the relay of far more information than the technical content of messages. Unlike formal documents such as newspapers, chat is often emotive. "Reading between the lines" to understand the connotative meaning of communication exchanges is now feasible, and often important. Understanding the connotative meaning of text is necessary to enable more useful automatic intelligence exploitation. The research project described in this paper was directed at recognizing user connotations of uncertainty and urgency. The project built a matrix of speech features indicative of these categories of meaning, developed data mining software to recognize them, and evaluated the results. ; Prepared in collaboration with Syracuse University, Syracuse, NY. Presented at the SPIE Defense, Security & Sensing Symposia 2009 in Orlando, FL on 13-17 Apr 2009. Published in Evolutionary and Bio-Inspired Computation: Theory and Applications III, SPIE Proceedings, v7347 paper 73470G, 2009. The original document contains color images.
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Keyword:
*CHAT COMMUNICATIONS; *CONNOTATIVE MEANING; *EMOTIONS; *NATURAL LANGUAGE; *TEXT PROCESSING; Cybernetics; INFORMATION EXTRACTION METRICS; Information Science; INTELLIGENCE ANALYSIS; LINGUISTIC CUES; Linguistics; PE61102F; PUNCTUATION; RULE BASED ANALYSIS; SEMANTICS; STATISTICAL ANALYSIS; SYMPOSIA; UNCERTAINTY; URGENCY; WUAFRO23088DAH
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URL: http://www.dtic.mil/docs/citations/ADA506312
http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA506312
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| 53 |
Metacognitive Awareness versus Linguistic Politeness: Expressions of Confusion in Tutorial Dialogues
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In: DTIC (2009)
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| 54 |
Relevance Feedback based on Constrained Clustering: FDU at TREC 09
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In: DTIC (2009)
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| 56 |
A Journey in Entity Related Retrieval for TREC 2009
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In: DTIC (2009)
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| 58 |
Lucene for n-grams using the ClueWeb Collection
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In: DTIC (2009)
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| 59 |
BIT at TREC 2009 Faceted Blog Distillation Task
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In: DTIC (2009)
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| 60 |
Recovering Asynchronous Watermark Tones from Speech
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In: DTIC (2009)
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