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Use of Minimal Lexical Conceptual Structures for Single-Document Summarization
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In: DTIC (2004)
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Discriminative Slot Detection Using Kernel Methods
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In: DTIC (2004)
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Information Extraction from Multiple Syntactic Sources
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In: DTIC AND NTIS (2004)
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Cognitive Tools for Humanoid Robots in Space
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In: DTIC AND NTIS (2004)
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Open Modules: Modular Reasoning about Advice
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In: DTIC (2004)
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Informedia at TRECVID 2003: Analyzing and Searching Broadcast News Video
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In: DTIC (2004)
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Towards a Warfighter's Associate: Eliminating the Operator Control Unit
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In: DTIC (2004)
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HTN Planning for Web Service Composition Using SHOP2
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In: DTIC (2004)
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Limited-Domain Speech-to-Speech Translation between English and Pashto
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In: DTIC (2004)
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The MMSR Bilingual and Crosschannel Corpora for Speaker Recognition Research and Evaluation
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In: DTIC (2004)
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Skeletons in the Parser: Using a Shallow Parser to Improve Deep Parsing
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In: DTIC (2004)
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From Unstructured to Structured Information in Military Intelligence - Some Steps to Improve Information Fusion
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In: DTIC (2004)
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Abstract:
Military commanders require timely and accurate understanding of the situation in their respective area of responsibility as well as a prediction of the likely intentions and capabilities of supposed or potential adversaries. To achieve this, intelligence cells have to process and evaluate information from all kinds of sources. Particularly in the area of non-conventional conflicts, e.g. in the fight against terrorism, heterogeneous and complex non-military information factors are influencing the production of intelligence. Large volumes of information and data have to be processed but manual evaluation and the conventional presentation of results is much too time consuming. A first essential aspect in the automated support to the exploitation and fusion of information and data is to deal with very different natures of data: numerical data, usually in the form of simple tables, more complex structured data such as relational databases, semi-structured messages, totally unstructured texts. A second challenging aspect in the automation of information fusion is provided by the heuristic nature of the real human processing of the imperfect information that is available. Fragments of information about ground truth are compared with the current picture of the situation, related to the most likely aspects of estimated threats, aggregated to more complex and significant situation objects, and finally integrated into a new picture of the situation. Correlation and aggregation of information is typically driven by knowledge about the structure and behaviour of adversary factions. This paper will present some of the findings of the RTO Task Group on Information Fusion Demonstration (IST-038/RTG-016) concerning these areas of topical interest. Relevant open research aspects and an analysis and functional model approach to human Intelligence processing is presented. ; Presented at the RTO SCI Symposium on Systems, Concepts and Integration (SCI) Methods and Technologies for Defence Against Terrorism, held in London, United Kingdom on 25-27 Oct 2004. Published in the proceedings, ADM201977, Systems, Concepts and Integration Methods and Technologies for Defence against Terrorism (Systemes, concepts, methodes d'integration et technologies pour la luttre contre le terrorisme), RTO-MP-SCI-158, paper 3. The original document contains color images.
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Keyword:
*DATA FUSION; *MILITARY INTELLIGENCE; BRIEFING CHARTS; COMPUTATIONAL LINGUISTICS; Cybernetics; FOREIGN REPORTS; GERMANY; Information Science; INTELLIGENCE CYCLE; Linguistics; Military Intelligence; NATO FURNISHED; SEMANTIC NETWORKS; SEMANTICS; SYMPOSIA; TEXT PROCESSING
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URL: http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA460220 http://www.dtic.mil/docs/citations/ADA460220
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Stochastic Language Generation in a Dialogue System: Toward a Domain Independent Generator
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In: DTIC (2004)
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Spoken Dialogue for Simulation Control and Conversational Tutoring
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In: DTIC (2004)
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The Case for Using Semantic Nets as a Convergence Format for Symbolic Information Fusion
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In: DTIC AND NTIS (2004)
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Extracting Dynamic Evidence Networks
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In: DTIC AND NTIS (2004)
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