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FactCheck - Identify and Fix Conflicting Data on the Web

机译:FarmCheck - 识别并修复网络上的冲突数据

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Today's Web pages more frequently contain structured information by means of semantically-rich embedded data. These data are currently used by search engines to provide an improved semantic, structured search result. However, very often these data are conflicting when present on different Web pages. Data consumers do not receive any support in handling (recognizing, interpreting, correcting) structured data. The more frequent structured data will be available on the Web, the more critical is the problem in recognizing and handling conflicting structured data. This paper presents FactCheck as an approach for the detection and resolution of conflicting structured data on the Web. We applied our solution to websites and APIs using JSON-LD and Microdata. First experiments with a prototypical implementation of FactCheck show that the resolution of conflicting data has high potential to significantly improve the quality of information on the Web. First evaluation reveals positive effects through the additional information indicators provided by FactCheck and indicates an impact on users of FactCheck at various levels. The resulting improvement of the data quality on websites will be of benefit to all data consumers who are depending on data on the Web as well as cognitive computing services and its building blocks.
机译:今天的网页更频繁地包含通过语义上的嵌入式数据来包含结构化信息。这些数据目前由搜索引擎使用,以提供改进的语义,结构化搜索结果。但是,当存在于不同的网页上时,通常这些数据通常是冲突的。数据消费者不会在处理(识别,解释,纠正)结构数据中的任何支持下都没有接收任何支持。在Web上可以使用更频繁的结构化数据,识别和处理冲突的结构化数据的问题越重要。本文提出了FACTCHECK作为检测和解决Web上的冲突结构化数据的方法。我们使用JSON-LD和Microdata将我们的解决方案应用于网站和API。第一个实验具有FarmCheck的原型实施,表明冲突数据的分辨率具有很高的潜力,以显着提高网络上信息的质量。首先评估通过事实上提供的附加信息指标显示积极影响,并表明对各级的事实情况的影响。由此产生的网站上的数据质量的提高将有益于所有数据消费者,这些数据消费者根据网上的数据以及认知计算服务及其构建块。

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