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| Content Provider | ACM Digital Library |
|---|---|
| Author | Chi, Pei-Yu Lieberman, Henry |
| Abstract | When editing a story from a large collection of media, such as photos and video clips captured from daily life, it is not always easy to understand how particular scenes fit into the intent for the overall story. Especially for novice editors, there is often a lack of coherent connections between scenes, making it difficult for the viewers to follow the story. In this paper, we present Raconteur, a story editing system that helps users assemble coherent stories from media elements, each annotated with a sentence or two in unrestricted natural language. It uses a Commonsense knowledge base, and the AnalogySpace Commonsense reasoning technique. Raconteur focuses on finding story analogies - different elements illustrating the same overall "point", or independent stories exhibiting similar narrative structures. |
| Starting Page | 301 |
| Ending Page | 304 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781605585154 |
| DOI | 10.1145/1719970.1720016 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2010-02-07 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Story goal Storytelling Video Commonsense computing Media editing Photograph Story analogy |
| Content Type | Text |
| Resource Type | Article |
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