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Generating Natural Language Descriptions With Integrated Text and Examples

Good documentation is critical for user acceptance of any system. Advances in areas such as knowledge-based systems, text generation and multi-media have now made it possible to investigate the automatic generation of documentation from the underlying knowledge bases. Empirical studies have shown that examples can greatly increase the effectiveness of system documentation. However, studies also show that badly integrated text and examples can be actually detrimental compared to using either text or examples alone. It is thus clear that in order to provide useful documentation automatically, a system must be capable of providing well-integrated examples to illustrate its points. 
This thesis builds upon previous work in natural language generation, example generation, cognitive and educational psychology to identify relevant issues in the generation of coherent descriptions that integrate text and examples. We identify how text and examples co-constrain each other and show that a system must consider example generation as an integral part of the generation process. We describe an implementation, and present an initial evaluation of the system's effectiveness. (Copies available exclusively from Micrographics Department, Doheny Library, USC, Los Angeles, CA 90089-0182.)