A Natural‐Language‐Based Approach to Intelligent Data Retrieval and Representation for Cloud BIM. (29th May 2015)
- Record Type:
- Journal Article
- Title:
- A Natural‐Language‐Based Approach to Intelligent Data Retrieval and Representation for Cloud BIM. (29th May 2015)
- Main Title:
- A Natural‐Language‐Based Approach to Intelligent Data Retrieval and Representation for Cloud BIM
- Authors:
- Lin, Jia‐Rui
Hu, Zhen‐Zhong
Zhang, Jian‐Ping
Yu, Fang‐Qiang - Abstract:
- Abstract: 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. The situation will be even worse for personnel without extensive knowledge of Industry Foundation Classes (IFC) or for nonexperts of the BIM software. 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 theAbstract: 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. The situation will be even worse for personnel without extensive knowledge of Industry Foundation Classes (IFC) or for nonexperts of the BIM software. 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. The case study illustrated the following: (1) relationships between the user requirements and the data users concerned are established, (2) user‐concerned data can be automatically retrieved and aggregated based on the cloud for BIM, and (3) the data are represented in a proper form for a visual view and a comprehensive report. With this approach, users can significantly benefit from requesting for information and the value of BIM will be enhanced. … (more)
- Is Part Of:
- Computer-aided civil and infrastructure engineering. Volume 31:Number 1(2016:Jan.)
- Journal:
- Computer-aided civil and infrastructure engineering
- Issue:
- Volume 31:Number 1(2016:Jan.)
- Issue Display:
- Volume 31, Issue 1 (2016)
- Year:
- 2016
- Volume:
- 31
- Issue:
- 1
- Issue Sort Value:
- 2016-0031-0001-0000
- Page Start:
- 18
- Page End:
- 33
- Publication Date:
- 2015-05-29
- Subjects:
- Civil engineering -- Data processing -- Periodicals
Computer-aided engineering -- Periodicals
624.0285 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1467-8667 ↗
http://www.ingenta.com/journals/browse/bpl/mice ↗
http://www.intute.ac.uk/sciences/cgi-bin/fullrecord.pl?handle=p.curran.1032797039 ↗
http://www3.interscience.wiley.com/journal/118514357/home ↗
http://onlinelibrary.wiley.com/ ↗
http://firstsearch.oclc.org ↗ - DOI:
- 10.1111/mice.12151 ↗
- Languages:
- English
- ISSNs:
- 1093-9687
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3393.519350
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 1760.xml