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1
Controlled English for Effective Communication during Coalition Operations
In: DTIC (2013)
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2
Enabling Efficient Intelligence Analysis in Degraded Environments
In: DTIC (2013)
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3
An Approach Using MIP Products for the Development of the Coalition Battle Management Language Standard
In: DTIC (2013)
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4
Automated Extraction and Characterisation of Social Network Data from Unstructured Sources -- An Ontology-Based Approach
In: DTIC (2013)
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5
Entity List Completion Using Set Expansion Techniques
In: DTIC (2011)
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6
Multilingual Content Extraction Extended with Background Knowledge for Military Intelligence
In: DTIC (2011)
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7
Recognizing Connotative Meaning in Military Chat Communications
In: DTIC (2009)
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8
Delft University at the TREC 2009 Entity Track: Ranking Wikipedia Entities
In: DTIC (2009)
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9
Patent Retrieval in Chemistry based on Semantically Tagged Named Entities
In: DTIC (2009)
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10
Applying A Formal Language of Command and Control For Interoperability Between Systems
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
In: DTIC (2008)
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12
ReSEARCH: A Requirements Search Engine
In: DTIC (2008)
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13
Semantical Machine Understanding
In: DTIC (2008)
Abstract: Semantical Machine Understanding is the foundation for automatic sense and decision making of multinational, multicultural, and coalition applications. We show an innovative semantical machine understanding system that can be installed on each node of a network and used as a semantic search engine. Innovations of such a system include 1" text mining: extract concepts and meaning clusters based on contexts using pattern recognition and machine learning; 2" meaning learning: extract knowledge patterns that link human labeled meaning to raw data. The knowledge patterns can be applied to predict future data; and 3" collaborative meaning search: incorporate humans and machines to form a collaborative network to search and enhance the meaning iteratively. In this paper, we also show the feasibility of using a semantic search architecture and discuss the two ways it is drastically different from current search engines: 1" indexes embedded in agents are distributed and customized to the learning and knowledge patterns of their own environment and culture. This allows data providers to maintain their own data in their own environment, but still share indexes across peers; 2" Semantic machine understanding enables discovery of new information rather than popular information. ; Presented at the International Command and Control Research and Technology Symposia (13th), ICCRTS 2008, Seattle, WA on 17-19 Jun 2008. The original document contains color images.
Keyword: *CROSS CULTURE(SOCIOLOGY); *INFORMATION RETRIEVAL; *LEARNING MACHINES; *TEXT PROCESSING; BRIEFING CHARTS; COLLABORATIVE MEANING SEARCHS; Computer Programming and Software; CULTURAL AWARENESS; Cybernetics; FREE TEXT OPEN VOCABULARY SENTENCES; Information Science; Linguistics; P2P(PEER-TO-PEER) TECHNOLOGIES; PATTERN RECOGNITION; SBIR TOPIC N06-153 PHASE 1; SBIR(SMALL BUSINESS INNOVATION RESEARCH); SCENARIOS; SEARCH ENGINES; SEMANTIC SEARCH ARCHITECTURE; SEMANTICAL MACHINE UNDERSTANDING; SEMANTICS; SENTIMENT CLASSIFICATION; SIMULATION; STATE PREDICTIONS; SYMPOSIA; TEXT MINING
URL: http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA486897
http://www.dtic.mil/docs/citations/ADA486897
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14
A Methodology to Predict Specific Communication Themes from Overall Communication Volume for Individuals and Teams
In: DTIC (2006)
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15
Content Analysis of HUMINT Reports
In: DTIC (2006)
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16
Deep Versus Broad Methods for Automatic Extraction of Intelligence Information From Text
In: DTIC (2005)
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17
Quality of Service-Driven Requirements Analyses for Component Composition: A Two-Level Grammar++ Approach
In: DTIC (2005)
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18
LOM: A Lexicon-based Ontology Mapping Tool
In: DTIC (2004)
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19
Inferring Parts of Speech for Lexical Mappings via the Cyc KB
In: DTIC (2004)
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20
Analysis of Free-Form Battlefield Reports with Shallow Parsing Techniques
In: DTIC AND NTIS (2004)
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