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Lexical Link Analysis Application: Improving Web Service to Acquisition Visibility Portal
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In: DTIC (2013)
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Applications of Lexical Link Analysis Web Service for Large-Scale Automation, Validation, Discovery, Visualization, and Real-Time Program Awareness
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In: DTIC (2012)
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Portable Language-Independent Adaptive Translation From OCR
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In: DTIC (2009)
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Portable Language-Independent Adaptive Translation from OCR
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In: DTIC (2009)
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Portable Language-Independent Adaptive Translation from OCR. Phase 1
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In: DTIC (2009)
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| 6 |
Coherence of Off-Topic Responses for a Virtual Character
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In: DTIC (2008)
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Portable Language-Independent Adaptive Translation from OCR
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In: DTIC (2008)
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| 8 |
Portable Language-Independent Adaptive Translation From OCR
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In: DTIC (2008)
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| 9 |
A GH-Based Ontology to Support Applications for Automating Decision Support
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In: DTIC (2005)
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| 10 |
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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Consolidating the Results of the CIRCSIM-Tutor Project and Further Consolidation of the Results of the CIRCSIM-Tutor Project
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In: DTIC AND NTIS (2003)
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TRAINS: Dialogue Transcription Tools.
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In: DTIC AND NTIS (1994)
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Detection and Correction of Repairs in Human-Computer Dialog
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In: DTIC (1992)
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A Nonclausal Connection-Graph Resolution Theorem-Proving Program
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In: DTIC (1982)
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| 19 |
Adaptive Understanding: Correcting Erroneous Inferences.
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In: DTIC AND NTIS (1980)
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Abstract:
This thesis is about understanding potentially misleading stories. A reader cannot know ahead of time whether or not a story will turn out to contradict one of its own previous implications. Therefore, virtually every story is potentially misleading. Understanding a story requires the reader to be able to recognize when a story contradicts a previous inference, and to correct the erroneous inference by replacing it with a better inference. ARTHUR (A Reader THat Understands Reflectively) is a computer program that understands stories by inferring unstated connections among the statements in the text, and producing a representation of the story which includes these inferences. The inferences in this story representation must be continually updated in light of each new story statement read. ARTHUR can recognize and correct its own erroneous inferences during understanding, and hence it can understand stories which contain entirely novel information. ARTHUR demonstrates its understanding of a story by using its story representation to answer questions about the story. ARTHUR embodies a theory of adaptive understanding: it's own understanding processes are affected and altered by what it reads. ARTHUR's ability to understand depends on its knowledge of the situations that can appear in stories, and, reciprocally, its knowledge can be increased according to what ARTHUR reads. ARTHUR's operation is based on a theory of the organization of situational knowledge in an understander's memory, and a theory of the processes by which that knowledge is applied during story understanding. ; Doctoral thesis.
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Keyword:
*ARTIFICIAL INTELLIGENCE; *NATURAL LANGUAGE; *TEXT PROCESSING; ADAPTIVE SYSTEMS; ARTHUR computer program; COMPUTER PROGRAMMING; Computer Programming and Software; Cybernetics; ERROR CORRECTION CODES; INPUT OUTPUT PROCESSING; Linguistics; RECOGNITION; THESES
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URL: http://www.dtic.mil/docs/citations/ADA081012
http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA081012
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