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Developing a hybrid approach to extract constraints related information for constraint management

journal contribution
posted on 2021-04-01, 00:00 authored by C Wu, P Wu, Jun WangJun Wang, R Jiang, M Chen, X Wang
Construction projects face various constraints (e.g., materials and equipment). Constraint management approaches such as advanced working packaging (AWP) can remove constraints and ensure smooth work. However, due to inefficient information extraction, the prerequisite of AWP, i.e., identifying and modelling constraints, are performed manually. Efforts that integrate constraint information into project knowledge bases are also limited. This paper proposes a hybrid approach to automatically extract and integrate constraint information from texts. The approach combines a deep learning model with pre-defined rules. The model extracts constraint entities whereas rules created based on domain knowledge are used to establish relations between these entities. Extracted information is encoded into the original ontologies. The approach can extract both entities and relations with over 90% accuracy. The original ontologies can be successfully enriched and support semantic queries. The approach improves AWP by partially automating constraint identification and modelling as well as ontology development for information integration.

History

Journal

Automation in Construction

Volume

124

Article number

103563

Pagination

1 - 17

Publisher

Elsevier

Location

Amsterdam, The Netherlands

ISSN

0926-5805

Language

eng

Publication classification

C1 Refereed article in a scholarly journal