A natural-language-based approach to intelligent data retrieval and representation for cloud BIM

Fuente: arXiv
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Auteurs principaux: Lin, Jia-Rui, Hu, Zhen-Zhong, Zhang, Jian-Ping, Yu, Fang-Qiang
Format: Preprint
Publié: 2024
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author Lin, Jia-Rui
Hu, Zhen-Zhong
Zhang, Jian-Ping
Yu, Fang-Qiang
author_facet Lin, Jia-Rui
Hu, Zhen-Zhong
Zhang, Jian-Ping
Yu, Fang-Qiang
contents As the information from diverse disciplines continues to integrate during the whole life cycle of an Architecture, Engineering, and Construction (AEC) project, the BIM (Building Information Model/Modeling) becomes increasingly large. This condition will cause users difficulty in acquiring the information they truly desire on a mobile device with limited space for interaction. To improve the value of the big data of BIM, an approach to intelligent data retrieval and representation for cloud BIM applications based on natural language processing was proposed. First, strategies for data storage and query acceleration based on the popular cloud-based database were explored to handle the large amount of BIM data. Then, the concepts keyword and constraint were proposed to capture the key objects and their specifications in a natural-language-based sentence that expresses the requirements of the user. Keywords and constraints can be mapped to IFC entities or properties through the International Framework for Dictionaries (IFD). The relationship between the user's requirement and the IFC-based data model was established by path finding in a graph generated from the IFC schema, enabling data retrieval and analysis. Finally, the analyzed and summarized results of BIM data were represented based on the structure of the retrieved data. A prototype application was developed to validate the proposed approach on the data collected during the construction of the terminal of Kunming Airport, the largest single building in China. With this approach, users can significantly benefit from requesting for information and the value of BIM will be enhanced.
format Preprint
id arxiv_https___arxiv_org_abs_2411_09951
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A natural-language-based approach to intelligent data retrieval and representation for cloud BIM
Lin, Jia-Rui
Hu, Zhen-Zhong
Zhang, Jian-Ping
Yu, Fang-Qiang
Human-Computer Interaction
As the information from diverse disciplines continues to integrate during the whole life cycle of an Architecture, Engineering, and Construction (AEC) project, the BIM (Building Information Model/Modeling) becomes increasingly large. This condition will cause users difficulty in acquiring the information they truly desire on a mobile device with limited space for interaction. To improve the value of the big data of BIM, an approach to intelligent data retrieval and representation for cloud BIM applications based on natural language processing was proposed. First, strategies for data storage and query acceleration based on the popular cloud-based database were explored to handle the large amount of BIM data. Then, the concepts keyword and constraint were proposed to capture the key objects and their specifications in a natural-language-based sentence that expresses the requirements of the user. Keywords and constraints can be mapped to IFC entities or properties through the International Framework for Dictionaries (IFD). The relationship between the user's requirement and the IFC-based data model was established by path finding in a graph generated from the IFC schema, enabling data retrieval and analysis. Finally, the analyzed and summarized results of BIM data were represented based on the structure of the retrieved data. A prototype application was developed to validate the proposed approach on the data collected during the construction of the terminal of Kunming Airport, the largest single building in China. With this approach, users can significantly benefit from requesting for information and the value of BIM will be enhanced.
title A natural-language-based approach to intelligent data retrieval and representation for cloud BIM
topic Human-Computer Interaction
url https://arxiv.org/abs/2411.09951