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Context-based page unit recommendation for web-based sensemaking tasks

机译:基于上下文的页面单元基于Web的Sensem制作任务的建议

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Sensemaking tasks require that users gather and comprehend information from many sources to answer complex questions. Such tasks are common and include, for example, researching vacation destinations or performing market analysis. In this paper, we present an algorithm and interface which provides context-based page unit recommendation to assist in connection discovery during sensemaking tasks. We exploit the natural note-taking activity common to sensemaking behavior as the basis for a task-specific context model. Our algorithm then dynamically analyzes each web page visited by a user to determine which page units are most relevant to the user's task. We present the details of our recommendation algorithm, describe the user interface, and present the results of a user study which show the effectiveness of our approach.
机译:Sensemaking任务要求用户收集和理解来自许多来源的信息以回答复杂的问题。这些任务是常见的,包括例如研究假期目的地或进行市场分析。在本文中,我们提供了一种算法和接口,它提供基于上下文的页面单元建议,以帮助在SensemAking任务期间协助连接发现。我们利用了对传感行为共同的自然音符活动作为特定于任务的上下文模型的基础。我们的算法然后动态分析用户访问的每个网页,以确定与用户的任务最相关的页面单元。我们介绍了我们推荐算法的详细信息,描述了用户界面,并呈现了用户研究的结果,显示了我们方法的有效性。

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