Abstract
Narrative and storytelling have played an important role in communication. In this work, we demonstrate that the techniques of storytelling, and in particular raising attention to abnormality, can be used to add interestingness and memorability to descriptions of time-series data. A computational system has been developed for automatically generating descriptions for data graphs. The system identifies visual patterns in the graph, and treats the graph’s deviations from corresponding ideal patterns as abnormal events. It then uses storytelling templates to generate a graph description with the abnormal events highlighted.
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Battad, Z., Si, M. (2018). Apply Storytelling Techniques for Describing Time-Series Data. In: Rouse, R., Koenitz, H., Haahr, M. (eds) Interactive Storytelling. ICIDS 2018. Lecture Notes in Computer Science(), vol 11318. Springer, Cham. https://doi.org/10.1007/978-3-030-04028-4_56
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DOI: https://doi.org/10.1007/978-3-030-04028-4_56
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