New Programming Languages for Artificial Intelligence Research
ACM Computing Surveys (CSUR)
Transition network grammars for natural language analysis
Communications of the ACM
Logic for Problem Solving
Conceptual Information Processing
Conceptual Information Processing
Understanding Natural Language
Understanding Natural Language
Natural Language Communication with Computers
Toward A Model Of Children''s Story Comprehension
Toward A Model Of Children''s Story Comprehension
The metanovel: writing stories by computer.
The metanovel: writing stories by computer.
Partitioned networks for the mathematical modeling of natural language semantics.
Partitioned networks for the mathematical modeling of natural language semantics.
Representation and Understanding: Studies in Cognitive Science
Representation and Understanding: Studies in Cognitive Science
Composite document extended retrieval: an overview
SIGIR '85 Proceedings of the 8th annual international ACM SIGIR conference on Research and development in information retrieval
Relating sentences and semantic networks with procedural logic
Communications of the ACM
Representation, Coherence and Inference
Artificial Intelligence Review
Computing text constituency: an algorithmic approach to the generation of text graphs
SIGIR '84 Proceedings of the 7th annual international ACM SIGIR conference on Research and development in information retrieval
COLING '86 Proceedings of the 11th coference on Computational linguistics
Text knowledge bases: University of Texas at Austin
ACM SIGART Bulletin
Exploring interactive stories in an HIV/AIDS learning game: HEALTHSIMNET
Simulation and Gaming
Petri Net-Based Episode Detection and Story Generation from Ubiquitous Life Log
UIC '08 Proceedings of the 5th international conference on Ubiquitous Intelligence and Computing
Exploiting mobile contexts for Petri-net to generate a story in cartoons
Applied Intelligence
Dynamic quest plot generation using Petri net planning
Proceedings of the Workshop at SIGGRAPH Asia
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A theory of understanding (parsing) texts as a process of collecting simple textual propositions into thematically and causally related units is described, based on the concept of macrostructures as proposed by Kintsch and van Dijk. These macrostructures are organized into tree hierarchies, and their interrelationships are described in rule-based story grammars related to the Kowalski logic based on Horn clauses. A procedure for constructing and synthesizing such trees from semantic network forms is detailed. The implementation of this procedure is capable of understanding and summarizing any story it can generate using the same basic control structure.