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A Framework of Organic Streams: Integrating Dynamically Diversified Contents into Ubiquitous Personal Study

机译:有机流框架:将动态多样化的内容整合到无所不在的个人学习中

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Recently, SNS, blog and microblog have become very popular. A different form of diversified contents, comparing to traditional static HTML web pages, are so easy to be generated dynamically, and can be provided to users by timeline. These contents are generally processed data streams, and have become an important part of the Internet resources. In this study, we try to integrate these dynamically diversified contents, such as twitter stream data, into Ubiquitous Personal Study (UPS), a personalized virtual study proposed in our previous study. In this paper, we introduce and define a set of new metaphors to represent a variety of data streams, such as Drop, Stream, River, and Ocean. We propose a Framework of Organic Streams to meaningfully organize these stream data. We describe the design and implementation issues of a prototype system, and discuss a scenario of using the enhanced UPS to support learning that utilizes twitter data streams.
机译:最近,SNS,博客和微博客变得非常流行。与传统的静态HTML网页相比,多样化的内容形式非常容易动态生成,并且可以按时间轴提供给用户。这些内容通常是经过处理的数据流,已经成为Internet资源的重要组成部分。在本研究中,我们尝试将这些动态多样化的内容(例如Twitter流数据)集成到无所不在的个人研究(UPS)中,这是我们先前研究中提出的个性化虚拟研究。在本文中,我们介绍并定义了一组新的隐喻来表示各种数据流,例如Drop,Stream,River和Ocean。我们提出了一个有机流框架来有意义地组织这些流数据。我们描述了原型系统的设计和实现问题,并讨论了使用增强型UPS支持使用Twitter数据流的学习的方案。

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