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Automatic Creation of Hyperlinks in AEC Documents by Extracting the Sheet Numbers Using LSTM Model

机译:通过使用LSTM模型提取图纸编号在AEC文档中自动创建超链接

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In a construction engineering document the sheet number represents a major identifier of the documents. Architecture, Engineering, and Construction (AEC) industry deals with many high dimensional drawing documents. For a construction document management system, it is necessary to extract sheet number from the Title block of the document. Architects and engineers also used to refer another document when creating some new ones. Otherwise, it is very difficult and time consuming to navigate through different files in an interactive way. This paper describes some hand-crafted and Long Short-Term Memory (LSTM) neural-net based features to extract sheet number from the Title Block. At first, we extract the content information from the document. From the extracted content information, we automatically find the sheet number which refers to another document. Then we created the hyperlinks in order to enable the engineers to quickly navigate between files. This work has strong application potential in the AEC industry. We have achieved overall accuracy of 98.52 %.
机译:在建筑工程文件中,图纸编号代表文件的主要标识符。建筑,工程和建筑(AEC)行业处理许多高维工程图文件。对于施工文件管理系统,有必要从文件的标题栏中提取图纸编号。在创建一些新文档时,建筑师和工程师还经常引用另一个文档。否则,以交互方式浏览不同文件非常困难且耗时。本文介绍了一些基于手工制作的长短期记忆(LSTM)神经网络的功能,用于从标题栏中提取工作表编号。首先,我们从文档中提取内容信息。从提取的内容信息中,我们自动找到引用另一个文档的页码。然后,我们创建了超链接,以使工程师能够在文件之间快速导航。这项工作在AEC行业中具有很强的应用潜力。我们已达到98.52 \%的整体精度。

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