Affiliation:
1. Kobe University, Japan
Abstract
Today more than ever, narrative content generation has become important. This is due to the advances and accessibility of computational devices. As these devices become more familiar to people and easier to handle, there will be greater expectations for autonomous functioning and desires for a natural communication with the users. To achieve such demands, computational devices need to process and generate higher levels of meanings such as context and abstraction of topics. This chapter gives a background on topics that have been developed so far in content analysis and content generation, but focuses mainly on the figure-ground impression model, for both analysis and generating narrative context. By focusing on the characters and their attributes in the text, not only is this model able to represent the figure-ground impressions qualitatively, but also quantitatively. Such a feature may be useful to execute in computational devices such as artificial intelligence.