.png){kind=icon}
.png){kind=icon}
Return
Text visualization for construction document information management
.png){kind=icon}
PRE
AI
DOI：10.1016/j.autcon.2019.103048.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In this study, text mining and visualization technology is applied to extract valuable information otherwise buried in the dense and abstract form of construction report text and process it into simple and intuitive graphics. This framework allows managers to quickly understand and make more informed decisions based upon key information. To extract such key information from a text automatically, the Term Frequency Inverse Document Frequency algorithm was optimized to the characteristics of engineering texts. The key messages extracted from a case study construction report text in the form of keywords/terms were then visualized using a tag cloud algorithm. Questionnaires completed by construction managers then demonstrated that the proposed information visualization framework can facilitate rapid and informative access to key project information. This framework can thus reduce the workload and time required for construction managers to ascertain and act upon the status of their projects.
Keywords:
Construction document management
Text visualization
Information extraction
Text mining
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
11.5
Papers:
6.2K
Citations:
4.2W