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1
A Hybrid Method for Opinion Finding Task (KUNLP at TREC 2008 Blog Track)
In: DTIC (2008)
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2
TREC 2008 at the University at Buffalo: Legal and Blog Track
In: DTIC (2008)
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3
THUIR at TREC2008: Blog Track
In: DTIC (2008)
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4
KLE at TREC 2008 Blog Track: Blog Post and Feed Retrieval
In: DTIC (2008)
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5
DCU at the TREC 2008 Blog Track
In: DTIC (2008)
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6
Applying A Formal Language of Command and Control For Interoperability Between Systems
In: DTIC (2008)
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7
Automating Convoy Training Assessment to Improve Soldier Performance
In: DTIC (2008)
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8
Barriers, Bridges, and Progress in Cognitive Modeling for Military Applications
In: DTIC (2008)
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9
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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10
ReSEARCH: A Requirements Search Engine
In: DTIC (2008)
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11
Integrating a Natural Language Message Pre-Processor with UIMA
In: DTIC (2008)
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12
CSIR at TREC 2008 Expert Search Task: Modeling Expert Evidence in Expert Search
In: DTIC (2008)
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13
Support for the Annual Meeting (30th) of the Cognitive Science Society
In: DTIC (2008)
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14
Laboratory for Computational Cultural Dynamics
In: DTIC (2008)
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15
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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16
Natural Language Dialogue Architectures for Tactical Questioning Characters
In: DTIC (2008)
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17
IIT Kharagpur at TREC 2008 Blog Track
In: DTIC (2008)
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18
DERI at TREC 2008 Enterprise Search Track
In: DTIC (2008)
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19
UTDallas at TREC 2008 Blog Track
In: DTIC (2008)
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20
Empirical Properties of Multilingual Phone-To-Word Transduction
In: DTIC (2008)
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