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1
Story Link Detection and New Event Detection are Asymmetric
In: DTIC (2003)
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2
A Noisy-Channel Approach to Question Answering
In: DTIC (2003)
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3
Utterance Classification in Auto Tutor
In: DTIC (2003)
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4
Hedge Trimmer: A Parse-and-Trim Approach to Headline Generation
In: DTIC (2003)
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5
The Benefit of Ontologies for Interoperability of CCIS. (Easy, Quick and Cheap Solutions are Impossible, if Semantics of CCIS are Affected.)
In: DTIC (2003)
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6
UMass at TREC 2003: HARD and QA
In: DTIC (2003)
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7
HowtogetaChineseName(Entity): Segmentation and Combination Issues
In: DTIC (2003)
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8
Multimodal Speaker Authentication using Nonacoustic Sensors
In: DTIC (2003)
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9
Combining Cross-Stream And Time Dimensions In Phonetic Speaker Recognition
In: DTIC (2003)
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10
Predictors of Plebe Summer Attrition at the United States Naval Academy
In: DTIC AND NTIS (2003)
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11
Spatial Language for Human-Robot Dialogs
In: DTIC AND NTIS (2003)
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12
Intelligence Cooperation in the Asia-Pacific Region: Establishing a Framework for Multilateralism
In: DTIC (2003)
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13
Exercising a Native Intelligence Metric on an Autonomous On-Road Driving System
In: DTIC (2003)
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14
Integration of Language and Cognition at Pre-Conceptual Level
In: DTIC (2003)
Abstract: This paper discusses mathematical models of the mechanisms that the mind can use for combining language and cognition. I address the problem of concurrent language acquisition and conceptual learning. How can a child learn so fast? In concurrent learning of language and cognitive structures, language helps learning about objects in the surrounding world and vice versa, which might explain why we can learn to recognize objects and words, but cannot remember a yellow page telephone book. The proposed theory addresses cognitive mechanisms of concepts, emotions, and goals and relates them to thought processes in which an event (in the outside world, or inside the mind) is understood as a concept. Learning language at the same time helps in this process. The described framework can use various language models described in cognitive and computational linguistic literature, while avoiding combinatorial computational complexity that has been the nemesis of artificial intelligence and computational linguistics. The combinatorial complexity is avoided by using a new type of logic, dynamic logic, that unifies fuzzy logic and formal logic. The postulated mechanisms of integration of language and cognition at a pre-conceptual level, where conceptual and emotional contents are not differentiated might be interesting for theoretical linguistics and for practical development of understanding-based search engines. ; Presented at the International Conference on Integration of Knowledge Intensive Multi-Agent Systems (KIMAS '03), Modeling, Exploration, and Engineering, held in Cambridge, MA on 30 Sep-4 Oct 2003. Published in the Proceedings of the International Conference on Integration of Knowledge Intensive Multi-Agent Systems (KIMAS '03), Modeling, Exploration, and Engineering, p280-285, 2003. This article is from ADA441198 International Conference on Integration of Knowledge Intensive Multi-Agent Systems. KIMAS '03: Modeling, Exploration, and Engineering Held in Cambridge, MA on 30 September-October 4, 2003
Keyword: *COGNITION; *INTEGRATION; *LANGUAGE; *MATHEMATICAL MODELS; ARTIFICIAL INTELLIGENCE; COMPONENT REPORTS; COMPUTATIONAL LINGUISTICS; CONCEPTS; Cybernetics; DYNAMIC LOGIC; EMOTIONS; LANGUAGE ACQUISITION; Linguistics; LOGIC; MIND; MODELING FIELD THEORY; NEURAL NETS; SEARCH ENGINES; SEMIOTICS; SYMBOLS; SYMPOSIA; THINKING
URL: http://www.dtic.mil/docs/citations/ADP021392
http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADP021392
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15
HITIQA: An Interactive Question Answering System. A Preliminary Report
In: DTIC (2003)
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16
Dialogue Management for an Automated Multilingual Call Center
In: DTIC (2003)
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