A Semantic Information Management Approach for Improving Bridge Maintenance based on Advanced Constraint Management
dc.contributor.author | Wu, Chengke | |
dc.contributor.supervisor | Xiangyu Wang | en_US |
dc.contributor.supervisor | Peng Wu | en_US |
dc.date.accessioned | 2021-12-02T02:49:03Z | |
dc.date.available | 2021-12-02T02:49:03Z | |
dc.date.issued | 2021 | en_US |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/86728 | |
dc.description.abstract |
Bridge rehabilitation projects are important for transportation infrastructures. This research proposes a novel information management approach based on state-of-the-art deep learning models and ontologies. The approach can automatically extract, integrate, complete, and search for project knowledge buried in unstructured text documents. The approach on the one hand facilitates implementation of modern management approaches, i.e., advanced working packaging to delivery success bridge rehabilitation projects, on the other hand improves information management practices in the construction industry. | en_US |
dc.publisher | Curtin University | en_US |
dc.title | A Semantic Information Management Approach for Improving Bridge Maintenance based on Advanced Constraint Management | en_US |
dc.type | Thesis | en_US |
dcterms.educationLevel | PhD | en_US |
curtin.department | School of Design and the Built Environment | en_US |
curtin.accessStatus | Open access | en_US |
curtin.faculty | Humanities | en_US |