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A human behavior inspired awareness system for document analysis

机译:人类行为启发了文档分析的认识系统

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With the rapid growth of the Internet, it is natural that we want to handle and process the document not as pen and paper but as online information. To deal with such large amount of information, people often want to use a certain classifier to classify it. To train a classifier, teacher signals are needed. However, different applications have different features, such as spam mail filter, patent analysis and hot-topic retrieval system. It is difficult to get enough teacher signals for every application. In this study, we describe a brain inspired awareness system for document analysis. This system could generate different document classifiers without any prior information. Then the user could give instructions to the system. After retraining, the system could understand user's intention and know how to generate a good classification system. Since the learning methods are drawn inspiration from human learning behaviors, which would be very easy for human beings to understand.
机译:随着互联网的快速增长,我们希望处理和处理文件而不是笔和纸,而是作为在线信息是自然的。要处理这么大的信息,人们通常希望使用某个分类器来对其进行分类。要培训分类器,需要教师信号。但是,不同的应用程序具有不同的功能,例如垃圾邮件滤波器,专利分析和热门主题检索系统。对于每个应用程序,很难获得足够的教师信号。在这项研究中,我们描述了一种用于文件分析的大脑启发意识系统。此系统可以在没有任何先前信息的情况下生成不同的文档分类器。然后用户可以向系统提供指令。再培训后,系统可以理解用户的意图,并知道如何生成良好的分类系统。由于学习方法汲取了人类学习行为的启发,因此人类将非常容易理解。

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