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Cleaning Your Wrong Google Scholar Entries

机译:清理错误的谷歌学者条目

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Entity categorization - the process of grouping entities into categories for some specific purpose - is an important problem with a great many applications, such as Google Scholar and Amazon products. Unfortunately, many real-world categories contain mis-categorized entities, such as publications in one's Google Scholar page that are published by the others. We have proposed a general framework for a new research problem - discovering mis-categorized entities. In this demonstration, we have developed a Google Chrome extension, namely GSCleaner, as one important application of our studied problem. The attendees will have the opportunity to experience the following features: (1) mis-categorized entity discovery - The attendee can check mis-categorized entities on anyone's Google Scholar page; and (2) Cleaning onsite - Any attendee can login and clean his Google Scholar page using GSCleaner. We describe our novel rule-based framework to discover mis-categorized entities. We also propose effective optimization techniques to apply the rules. Some empirical results show the effectiveness of GSCleaner on discovering mis-categorized entities.
机译:实体分类 - 为某些特定目的分组实体的过程 - 是一个很多应用程序的重要问题,例如Google Scholar和亚马逊产品。不幸的是,许多现实世界类别包含错误分类实体,例如其他人在其他人发布的谷歌学者页面中的出版物。我们提出了一个新的研究问题的一般框架 - 发现错误分类的实体。在这次演示中,我们开发了一个Google Chrome扩展,即GSCleaner,作为我们研究的问题的一个重要应用。与会者将有机会体验以下功能:(1)错误分类实体发现 - 与会者可以在任何人的谷歌学者页面检查错误分类的实体; (2)清洁现场 - 任何与会者都可以使用GSCleaner登录并清理他的Google学者页面。我们描述了我们的基于规则的基于规则的框架,以发现错误分类的实体。我们还提出了有效的优化技术来应用规则。一些经验结果表明了GSCleaner在发现错误分类实体的有效性。

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