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Expert Evidence Document Recognition Integrating Relationship of Expert

机译：专家证据记录识别集成专家关系

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摘要

Focus on the issue that the existing expert evidence document recognition method is not effective use of the relationship between experts, this paper proposed a method to recognize.the expert evidence documents which integrate the feature of webpage content and the complex relationship between the experts. First of all, the method analyses characteristics of expert evidence document, to select Coauthors and organization as relationship feature, and then extracts feature values. Secondly, select 10130 expert evidence pages, and build data sets which integrate the feature values of and webpage content and the relationship, and then select different learning algorithms to build recognition model. Finally, experiment of expert evidence document recognition is carried out in the field of information processing. The experimental results shows that the proposed method achieves a good recognition effect. Using relationship can effectively improve the accuracy of the evidence document recognition. Its accuracy is improved by 4% compared to method using the page content feature recognition only.
机译：专注于现有专家证据记录识别方法没有有效地利用专家之间关系的问题，提出了一种识别的方法。专家证据文件整合了网页内容的特征和专家之间的复杂关系。首先，该方法分析专家证据文档的特征，选择共存和组织作为关系功能，然后提取特征值。其次，选择10130专家证据页面，并构建数据集，该组集成了与网页内容的特征值和关系，然后选择不同的学习算法来构建识别模型。最后，在信息处理领域进行了专家证据记录识别的实验。实验结果表明，该方法达到了良好的识别效果。使用关系可以有效提高证据记录识别的准确性。与使用页面内容功能识别的方法相比，其精度提高了4％。

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