nReader: reading news quickly, deeply and vividly

Authors:
Taifeng Wang;Nenghai Yu;Zhiwei Li;Mingjing Li
Affiliations:
University of Science and Technology of China, Heifei, Anhui, China;University of Science and Technology of China, Heifei, Anhui, China;MicroSoft Research Asia, Beijing Sigma Center, Beijing, China;MicroSoft Research Asia, Beijing Sigma Center, Beijing, China
Venue:
CHI '06 Extended Abstracts on Human Factors in Computing Systems
Year:
2006

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Abstract

In this paper we present our design of a novel system, named nReader, to help people read online news. According to researches on news recommendation and a newly deployed survey on user's feeling and requirement about current news reading style, we build our system by adding extra feature to the framework of the popular RSS (Rich Site Summary) system.We designed corresponding views in our reading tools to support browsing mode and intensively reading mode. After a preliminary user testing, the feedback is encouraging. A wider and more delicate user study will be performed to boost our system and interface to give user a more convenient and comfortable online news reading experience.