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.

翻译：随着建筑、工程与施工（AEC）项目全生命周期中多学科信息的持续融合，建筑信息模型（BIM）的规模日益庞大。这一状况将导致用户在交互空间有限的移动设备上难以获取真正需要的信息。为提升BIM大数据的价值，本文提出了一种基于自然语言处理的云BIM应用智能数据检索与表示方法。首先，为处理海量BIM数据，探索了基于主流云数据库的数据存储与查询加速策略。其次，提出"关键词"与"约束条件"概念，用以捕捉用户需求自然语言语句中的核心对象及其属性规范。通过国际字典框架（IFD），关键词与约束条件可映射至工业基础类（IFC）实体或属性。基于IFC模式生成的图结构进行路径查找，建立了用户需求与IFC数据模型之间的关联，从而实现数据检索与分析。最后，根据检索数据的结构对BIM数据的分析汇总结果进行可视化表示。为验证所提方法，基于中国最大单体建筑——昆明机场航站楼施工期间采集的数据开发了原型应用。该方法可使用户在信息请求中显著获益，并有效提升BIM数据价值。