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Using Fuzzy Cognitive Map to Effectively Classify E-Documents and Application

机译:使用模糊认知图对电子文档及其应用进行有效分类

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In the current Web, e-document has been the most common vehicle for delivering and exchanging information. As the amount of e-documents has grown enormously, effective classification facilities are urgently needed to classify and query e-documents users want. In this paper, we propose a method to classify e-documents into a set of predefined categories based on Fuzzy Cognitive Map (FCM). The e-documents are collected from Internet by a meta-search engine. FCM has been employed to capture the semantic relationships between keywords of e-documents. Experiments with a set of local e-documents have proved that this approach has high performance and can help users getting the e-documents efficiently and effectively. The proposed method has been implemented and integrated into the Dunhuang Feitian System to manage and classify e-documents.
机译:在当前的Web中,电子文档已成为传递和交换信息的最常用工具。随着电子文档数量的巨大增长,迫切需要有效的分类工具来分类和查询用户想要的电子文档。在本文中,我们提出了一种基于模糊认知图(FCM)将电子文档分类为一组预定义类别的方法。电子文档是由元搜索引擎从Internet收集的。 FCM已被用来捕获电子文档关键字之间的语义关系。通过一系列本地电子文档的实验证明,这种方法具有很高的性能,可以帮助用户高效,高效地获取电子文档。该方法已经实施,并已集成到敦煌飞天系统中,可以对电子文档进行管理和分类。

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