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Visualized comparison for CFP datasets by structure identification and ontology

机译:通过结构识别和本体对CFP数据集进行可视化比较

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This paper proposes a method to visualize relations and keywords of two Call For Paper (CFP) datasets for comparison or trend research. Based on our previous works on information extraction from CFP files and trend visualization system (FACT-Graph), this paper describes the contribution and usefulness of the different methods of data input into the visualization system. Using two CFP datasets from two academic societies in order to support our theory, we compare three input data processes from basic plain text data to structured data made from selected relevant data along with the contribution of external data from ontology models.
机译:本文提出了一种可视化两个“论文征集”(CFP)数据集之间的关系和关键字以进行比较或趋势研究的方法。基于我们先前从CFP文件和趋势可视化系统(FACT-Graph)提取信息的工作,本文描述了将各种数据输入可视化系统的方法的贡献和实用性。为了支持我们的理论,使用了来自两个学术协会的两个CFP数据集,我们比较了从基本纯文本数据到由选定相关数据构成的结构化数据的三个输入数据过程,以及来自本体模型的外部数据的贡献。

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