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dc.contributor.authorWu, Chengke
dc.contributor.supervisorXiangyu Wangen_US
dc.contributor.supervisorPeng Wuen_US
dc.date.accessioned2021-12-02T02:49:03Z
dc.date.available2021-12-02T02:49:03Z
dc.date.issued2021en_US
dc.identifier.urihttp://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.publisherCurtin Universityen_US
dc.titleA Semantic Information Management Approach for Improving Bridge Maintenance based on Advanced Constraint Managementen_US
dc.typeThesisen_US
dcterms.educationLevelPhDen_US
curtin.departmentSchool of Design and the Built Environmenten_US
curtin.accessStatusOpen accessen_US
curtin.facultyHumanitiesen_US


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