BIMTag: Concept-based automatic semantic annotation of online BIM product resources

Ge Gao^a,d, Yu-Shen Liu^a,b,c,*, Pengpeng Lin^a, Meng Wang^a, Ming Gu^a, Jun-Hai Yong^a

^aSchool of Software, Tsinghua University, Beijing, China
^bKey Laboratory for Information System Security, Ministry of Education of China
^cTsinghua National Laboratory for Information Science and Technology
^dDepartment of Computer Science and Technology, Tsinghua University

Abstract:

With the rapid popularity of Building Information Modeling (BIM) technologies, BIM resources such as building product libraries are growing rapidly on the World Wide Web. However, numerous BIM resources are usually from heterogeneous systems or various manufacturers with ambiguous expressions and uncertain categories for product descriptions, which cannot provide effective support for information retrieval and categorization applications. Therefore, there is an increasing need for semantic annotation to reduce the ambiguity and unclearness of natural language in BIM documents. Based on Industry Foundation Classes (IFC) which is a major standard for BIM, this paper presents a concept-based automatic semantic annotation method for the documents of online BIM products. The method mainly consists of the following two stages. Firstly, with reference to the concepts and relationships explicitly defined in IFC, a word-level annotation algorithm is applied to the word-sense disambiguation. Secondly, based on latent semantic analysis technique, a document-level annotation algorithm is proposed to discover the relationships which are not explicitlydefined in IFC. Finally, a prototype annotation system, named BIMTag, is developed and combined with a search engine for demonstrating the utility and effectiveness of our method. The BIMTag system is available at http://cgcad.thss.tsinghua.edu.cn/liuyushen/bimtag/.

Links:

Platform Prototype [BIMTag]
Paper [3.26MB]

Video Demo:

Acknowledgements:

The authors appreciate the comments and suggestions of all reviewers, whose comments significantly improved this paper. The authors would like to thank Dr. Pieter Pauwels at Ghent University for discussing the problem of IFC-to-RDF conversion. The research is supported by the National Science Foundation of China (61472202, 61272229, 61003095) and the National Technological Support Program for the 12th-Five-Year Plan of China (2012BAJ03B07). The fourth author is supported by the Chinese 973 Program (2010CB328003) and the last author is supported by the Chinese 863 Program (2012AA040902).

Contact:

Dr. Yu-Shen Liu, Email address: liuyushen@tsinghua.edu.cn.
Ge Gao, Email address: gg07@mails.tsinghua.edu.cn.