Discovering and visualizing narrative themes
نویسنده
چکیده
This paper presents a framework for indexing and browsing databases of stories, in particular characterizing and visually exploring each narrative’s thematic content. We introduce a method for discovering thematic content in texts via lexical dissimilarity statistics. A maximumlikelihood algorithm clusters words into pools of similar meaning, using a thesaurus for rough estimates of word sense similarities. The highest ranked clusters indicate thematic motifs in the story. With these clusters we can form efficient representations for indexing, keyword summaries, and textual segmentation into thematically coherent sections. We demonstrate this representation in a system that generates interactive 3D visualizationsof stories and their thematic structures.
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