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    Bridge Deterioration Knowledge Ontology for Supporting Bridge Document Analytics 

    Source: Journal of Construction Engineering and Management:;2022:;Volume ( 148 ):;issue: 006:;page 04022030
    Author(s): Kaijian Liu; Nora El-Gohary
    Publisher: ASCE
    Abstract: Bridge owners possess important data sources, such as bridge construction records and inspection and maintenance reports, which hold great promise for improving understanding of bridge deterioration and informing maintenance ...
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    Semantic Neural Network Ensemble for Automated Dependency Relation Extraction from Bridge Inspection Reports 

    Source: Journal of Computing in Civil Engineering:;2021:;Volume ( 035 ):;issue: 004:;page 04021007-1
    Author(s): Kaijian Liu; Nora El-Gohary
    Publisher: ASCE
    Abstract: Bridge inspection reports are important sources of technically detailed data/information about bridge conditions and maintenance history, yet remain untapped for bridge deterioration prediction. To capitalize on these ...
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    Deep Learning–Based Analytics of Multisource Heterogeneous Bridge Data for Enhanced Data-Driven Bridge Deterioration Prediction 

    Source: Journal of Computing in Civil Engineering:;2022:;Volume ( 036 ):;issue: 005:;page 04022023
    Author(s): Kaijian Liu; Nora El-Gohary
    Publisher: ASCE
    Abstract: Existing data-driven bridge deterioration prediction methods mostly learn from abstract inventory data from a single source to predict the future conditions of bridges. Bridge inventory data [e.g., the National Bridge ...
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    Crowdsourcing Construction Activity Analysis from Jobsite Video Streams 

    Source: Journal of Construction Engineering and Management:;2015:;Volume ( 141 ):;issue: 011
    Author(s): Kaijian Liu; Mani Golparvar-Fard
    Publisher: American Society of Civil Engineers
    Abstract: The advent of affordable jobsite cameras is reshaping the way on-site construction activities are monitored. To facilitate the analysis of large collections of videos, research has focused on addressing the problem of ...
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    Fusing Data Extracted from Bridge Inspection Reports for Enhanced Data-Driven Bridge Deterioration Prediction: A Hybrid Data Fusion Method 

    Source: Journal of Computing in Civil Engineering:;2020:;Volume ( 034 ):;issue: 006
    Author(s): Kaijian Liu; Nora El-Gohary
    Publisher: ASCE
    Abstract: Data buried in textual bridge inspection reports offer great promise for enhanced data-driven bridge deterioration prediction. However, learning from these reports is challenging because they typically use multiple concept ...
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