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Scalable Knowledge Extraction and Visualization for Web Intelligence

机译:网络智能的可扩展知识提取和可视化

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Understanding stakeholder perceptions and assessing the impact of campaigns are key questions of communication experts. Web intelligence platforms help to answer such questions, provided that they are scalable enough to analyze and visualize information flows from volatile online sources in real time. This paper presents a distributed architecture for aggregating Web content repositories from Web sites and social media streams, memory-efficient methods to extract factual and affective knowledge, and interactive visualization techniques to explore the extracted knowledge. The presented examples stem from the Media Watch on Climate Change, a public Web portal that aggregates environmental content from a range of online sources.
机译:了解利益相关者的看法和评估运动的影响是通信专家的关键问题。 Web Intelligence平台有助于回答此类问题,条件是它们足以分析和可视化从挥发性在线来源实时流动的信息。本文提出了一种分布式架构,用于从网站和社交媒体流,内存有效的方法来聚合Web内容存储库,提取事实和情感知识,以及探索提取的知识的交互式可视化技术。所呈现的例子源于媒体观察气候变化,这是一家公共网络门户网站,它从一系列在线来源聚集环境内容。

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