Discourse generation is a critical task of natural language generation. In this thesis, we introduce an approach to discourse generation for qualitative causal probabilistic domains that incorporates argumentation into the generation process. The discourse generation process uses three modules: a qualitative causal probabilistic domain model, a genre-specific discourse grammar, and a normative argument generator. The model of discourse generation has been implemented for the domain of clinical genetics. In conjunction with GenIE, a prototype intelligent system for generating the first draft of a patient letter on behalf of a genetic counselor, the discourse grammar exploits general information about clinical genetics as well as documentation about a specific patient's case provided by a genetic counselor, to create discourse plans. The argument generator generates arguments for the claims passed to it from the discourse grammar using domain-independent argument strategies. An important contribution of the thesis is a modification of the argument generator to support interactive argument exploration.
Identifer | oai:union.ndltd.org:NCSU/oai:NCSU:etd-01282008-150847 |
Date | 30 January 2008 |
Creators | Navoraphan, Kanyamas |
Contributors | Dr. James C. Lester, Dr. Nancy L. Green, Dr. R. Michael Young, Dr. Robert D. Rodman |
Publisher | NCSU |
Source Sets | North Carolina State University |
Language | English |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | http://www.lib.ncsu.edu/theses/available/etd-01282008-150847/ |
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