Exploring BIM Data by Graph-based Unsupervised Learning

Chaoyi Jin; Minyang Xu; Lan Lin; Xiangdong Zhou

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Paper

Exploring BIM Data by Graph-based Unsupervised Learning

Topics: Industry Related Applications

In Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods ICPRAM - Volume 1, 582-589, 2018 , Funchal, Madeira, Portugal

Authors: Chaoyi Jin ¹ ; Minyang Xu ¹ ; Lan Lin ² and Xiangdong Zhou ¹

Affiliations: ¹ Fudan University, China ; ² Tongji University, China

Keyword(s): Graph Propagation, Unsupervised Learning, BIM Data Mining.

Abstract: This paper presents an unsupervised learning method for mining the Industry Foundation Classes (IFC) based Building Information Modelling (BIM) data by exploring the inter-relational graph-like building spaces. In our method, the affinity propagation clustering algorithm is adapted with our proposed feature extraction algorithm to get exemplars of certain spaces with similar usage functions. The experiments are conducted on a real world BIM dataset. The experimental results show that some build spaces of typical usage functions can be discovered by our unsupervised learning algorithm.

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Paper citation in several formats:

Jin, C.; Xu, M.; Lin, L. and Zhou, X. (2018). Exploring BIM Data by Graph-based Unsupervised Learning. In Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-276-9; ISSN 2184-4313, SciTePress, pages 582-589. DOI: 10.5220/0006715305820589

@conference{icpram18,
author={Chaoyi Jin. and Minyang Xu. and Lan Lin. and Xiangdong Zhou.},
title={Exploring BIM Data by Graph-based Unsupervised Learning},
booktitle={Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2018},
pages={582-589},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006715305820589},
isbn={978-989-758-276-9},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - Exploring BIM Data by Graph-based Unsupervised Learning
SN - 978-989-758-276-9
IS - 2184-4313
AU - Jin, C.
AU - Xu, M.
AU - Lin, L.
AU - Zhou, X.
PY - 2018
SP - 582
EP - 589
DO - 10.5220/0006715305820589
PB - SciTePress