Understanding On-Site Inspection of Construction Projects based on Keyword Extraction and Topic Modeling

IEEE Access, 2020

引用方式: Lin, J.R.*, Hu, Z.Z., Li, J.L., and Chen, L.M. (2020). "Understanding On-Site Inspection of Construction Projects based on Keyword Extraction and Topic Modeling" IEEE Access. 8: 198503-198517. doi: 10.1109/ACCESS.2020.3035214 http://doi.org/10.1109/ACCESS.2020.3035214 cited by count

摘要

作为保障工程建设质量与安全的重要措施,施工现场检查至关重要。随着移动终端及手机App的普及,施工现场检查积累的文本数据快速增长。然而,由于缺乏对现场检查文本的高效分析与知识抽取工具,我们往往会忽视或遗漏现场问题并难以高效的做出决策响应。因此,本文提出一种基于关键词提取与主题建模的文本挖掘方法,可以识别施工现场隐患的关键关注点及其动态变化,从而支持更加高效、精准的决策。

有关方法在某实际项目现场质安隐患检查的额文本数据上进行了测试验证。结果表明,该方法可以从质安隐患关键词及主题分布两个角度准确抽取文本中隐藏的关键信息,并可分析有关信息随时间的变化,从而支持更加高效的现场隐患检查与以数据为中心的决策过程。

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引用方式: Lin, J.R.*, Hu, Z.Z., Li, J.L., and Chen, L.M. (2020). "Understanding On-Site Inspection of Construction Projects based on Keyword Extraction and Topic Modeling" IEEE Access. 8: 198503-198517. doi: 10.1109/ACCESS.2020.3035214

This research is supported by the Natural Science Foundation of China (No. 51908323), the Beijing Municipal Science and Technology Project (No. Z181100005918006) and the Tsinghua University Initiative Scientific Research Program (No. 2019Z02UOT).

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