人工知能学会論文誌
Online ISSN : 1346-8030
Print ISSN : 1346-0714
ISSN-L : 1346-0714
原著論文
iPoster: Interactive Poster Generation based on Topic Structure and Slide Presentation
Yuanyuan WangYukiko KawaiKazutoshi Sumiya
著者情報
ジャーナル フリー

2015 年 30 巻 1 号 p. 112-123

詳細
抄録

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 interactive poster (iPoster) generation method and we have also included an evaluation of our method's effectiveness.

著者関連情報
© The Japanese Society for Artificial Intelligence 2015
前の記事 次の記事
feedback
Top