Systemic Text Generation as Problem Solving
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BeschreibungThis study explores a new approach to text generation that interprets systemic grammar as a computational representation. Terry Patten demonstrates that systemic grammar can be easily and automatically translated into current AI knowledge representations and efficiently processed by the same knowledge-based techniques currently exploited by expert systems. Thus the fundamental methodological problem of interfacing specialized computational respresentations with equally specialized linguistic representations can be resolved. The study provides a detailed discussion of a substantial implementation involving a relatively large systemic grammar, and a formal model of the method. It represents a fundamental and productive contribution to the literature on text generation.
InhaltsverzeichnisPreface; 1. Introduction; 2. Background I: AI problem solving; 3. Background II: systemic grammar; 4. The conflation; 5. The formal model; 6. The implementation; 7. Related work in text generation; 8. Conclusions; Appendix A: OPS5 tutorial; Appendix B: sample texts; Appendix C: excerpts from the grammar; Notes; Bibliography; Index.
Untertitel: 'Studies in Natural Language Pr'. Sprache: Englisch.
Verlag: CAMBRIDGE UNIV PR
Erscheinungsdatum: August 2007
Seitenanzahl: 214 Seiten