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  • 标题:Text Visualization using Light and Shadow based on Topic Relevance
  • 本地全文:下载
  • 作者:Yoko Nishihara ; Keita Sato ; Wataru Sunayama
  • 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:2009
  • 卷号:24
  • 期号:6
  • 页码:479-487
  • DOI:10.1527/tjsai.24.479
  • 出版社:The Japanese Society for Artificial Intelligence
  • 摘要:There are so many opportunities to transmit text information on the Web. Since texts on the Web are not always written by professional writers, those may not be coherent or may be hard to be comprehended. Therefore, we should take too much time and energy to grasp topic relevance of a text. This paper describes HINATA system that visualizes texts using light and shadow based on topic relevance. Topic is defined as a set of words such as nouns contained in a title of a text. The light expresses sentences related to a topic, and the shadow expresses sentences unrelated to a topic. This visualization method efficiently supports users for finding the parts related to a topic, and for grasping relations between sentences of a text and a topic. Experimental results showed that the proposed system could support users for understanding how a text was related to a topic.
  • 关键词:text visualization ; light and shadow ; information comprehension ; topic relevance
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