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  • 标题:iPoster: Interactive Poster Generation based on Topic Structure and Slide Presentation
  • 本地全文:下载
  • 作者:Yuanyuan Wang ; Yukiko Kawai ; Kazutoshi Sumiya
  • 期刊名称:人工知能学会論文誌
  • 印刷版ISSN:1346-0714
  • 电子版ISSN:1346-8030
  • 出版年度:2015
  • 卷号:30
  • 期号:1
  • 页码:112-123
  • DOI:10.1527/tjsai.30.112
  • 出版社:The Japanese Society for Artificial Intelligence
  • 摘要:MOOC is a crucial platform for improving education; students are able to obtain various educational presentation contents through the Web. Recently, Prezi introduced a zoomable canvas as a substitute to the traditional presentations that allows users to zoom in and out of the presentation media. Teachers then attempt to provide presentations in a nonlinear fashion for enhancing the user interaction through these presentations; however, creation of nonlinear presentations would be time-consuming, besides posing design challenges. Therefore, we have developed a novel support system for grasping overviews of presentation slides, it generates a meaningfully structured presentation, called iPoster; this enables users to automatically navigate through the slide-based educational contents. The system places elements such as text and graphics of presentation slides in a structural layout by semantically analyzing the slide structure. The structural layout can reveal the hierarchy of elements based on topic structure by moving from the overview to a detail using automatic transitions, such as zooms and pans. Through this, the iPoster can support students to interactively browse online presentation slides for grasping an overview; it would substantially help the students navigate the presentation slides effectively for their learning purposes. In this paper, we discuss our i nteractive poster (iPoster) generation method and we have also included an evaluation of our method's effectiveness.
  • 关键词:presentation slides ; slide structure ; topic structure ; interactive poster ; iPoster ; e-learning
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