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Literary Psychology-Modeling Figure-Ground Structures in Narrative Stories: Towards a Narrative Content Generation

Literary Psychology-Modeling Figure-Ground Structures in Narrative Stories: Towards a Narrative Content Generation

Eugene Schneider Kitamura
Copyright: © 2018 |Pages: 36
ISBN13: 9781522547754|ISBN10: 1522547754|EISBN13: 9781522547761
DOI: 10.4018/978-1-5225-4775-4.ch006
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MLA

Kitamura, Eugene Schneider. "Literary Psychology-Modeling Figure-Ground Structures in Narrative Stories: Towards a Narrative Content Generation." Content Generation Through Narrative Communication and Simulation, edited by Takashi Ogata and Shin Asakawa, IGI Global, 2018, pp. 205-240. https://doi.org/10.4018/978-1-5225-4775-4.ch006

APA

Kitamura, E. S. (2018). Literary Psychology-Modeling Figure-Ground Structures in Narrative Stories: Towards a Narrative Content Generation. In T. Ogata & S. Asakawa (Eds.), Content Generation Through Narrative Communication and Simulation (pp. 205-240). IGI Global. https://doi.org/10.4018/978-1-5225-4775-4.ch006

Chicago

Kitamura, Eugene Schneider. "Literary Psychology-Modeling Figure-Ground Structures in Narrative Stories: Towards a Narrative Content Generation." In Content Generation Through Narrative Communication and Simulation, edited by Takashi Ogata and Shin Asakawa, 205-240. Hershey, PA: IGI Global, 2018. https://doi.org/10.4018/978-1-5225-4775-4.ch006

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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.

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