A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Automatic Review of Construction Specifications Using Natural Language Processing
Since construction specifications are normally over 1000 pages and are complicated and often inconsistent, reviewing them is a labor-intensive and time-consuming activity. Thus, the aim of this study was to automate the review process by comparing construction specifications with standard specifications using natural language processing. Standard specifications for road construction projects were collected from 43 different states in the U.S. and used as experimental data. Doc2Vec, cosine similarity, and named entity recognition (NER) were used to recognize construction objects, standard values, and execution conditions, which can be used to find specification errors. As an early stage of the research, most of related sentences were found from standard specifications with high relevancy, and the average F1 score of NER was 0.256. The research findings will contribute to enhancing the efficiency of checking for specification errors by automatically detecting abnormalities and the absence of specific standards.
Automatic Review of Construction Specifications Using Natural Language Processing
Since construction specifications are normally over 1000 pages and are complicated and often inconsistent, reviewing them is a labor-intensive and time-consuming activity. Thus, the aim of this study was to automate the review process by comparing construction specifications with standard specifications using natural language processing. Standard specifications for road construction projects were collected from 43 different states in the U.S. and used as experimental data. Doc2Vec, cosine similarity, and named entity recognition (NER) were used to recognize construction objects, standard values, and execution conditions, which can be used to find specification errors. As an early stage of the research, most of related sentences were found from standard specifications with high relevancy, and the average F1 score of NER was 0.256. The research findings will contribute to enhancing the efficiency of checking for specification errors by automatically detecting abnormalities and the absence of specific standards.
Automatic Review of Construction Specifications Using Natural Language Processing
Moon, Seonghyeon (author) / Lee, Gitaek (author) / Chi, Seokho (author) / Oh, Hyunchul (author)
ASCE International Conference on Computing in Civil Engineering 2019 ; 2019 ; Atlanta, Georgia
Computing in Civil Engineering 2019 ; 401-407
2019-06-13
Conference paper
Electronic Resource
English
Automatic Review of Construction Specifications Using Natural Language Processing
| British Library Conference Proceedings | 2019
Systematic Review of Construction Specifications
| British Library Conference Proceedings | 1999
Construction specifications : managing the review process
| TIBKAT | 1992
Critical review of wood construction specifications
| Engineering Index Backfile | 1937