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Adami, V S, Verschoore, J R and Antunes Junior, J A V (2019) Effect of Relational Characteristics on Management of Wind Farm Interorganizational Construction Projects. Journal of Construction Engineering and Management, 145(03).
Alruqi, W M and Hallowell, M R (2019) Critical Success Factors for Construction Safety: Review and Meta-Analysis of Safety Leading Indicators. Journal of Construction Engineering and Management, 145(03).
Chegu Badrinath, A and Hsieh, S (2019) Empirical Approach to Identify Operational Critical Success Factors for BIM Projects. Journal of Construction Engineering and Management, 145(03).
Kim, T and Chi, S (2019) Accident Case Retrieval and Analyses: Using Natural Language Processing in the Construction Industry. Journal of Construction Engineering and Management, 145(03).
- Type: Journal Article
- Keywords: Construction accident case; Tacit knowledge; Knowledge management; Natural language processing; Information retrieval; Information extraction;
- ISBN/ISSN: 0733-9364
- URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0001625
- Abstract:
Knowledge management for construction accident cases can identify dangerous conditions and prevent accidents by controlling risks on-site. However, because accident cases are recorded as unstructured text data, significant time and effort are required to retrieve and analyze the knowledge a user wants. To overcome these limitations, this research proposes a knowledge management system for construction accident cases using natural language processing. For this purpose, two models were developed that can retrieve appropriate cases according to user intentions and automatically analyze tacit knowledge from construction accident cases. In the retrieval model, the query is expanded using a construction accident case thesaurus. Ranking is calculated using Okapi BM25 and weighting according to the thesaurus. In the analysis model, knowledge is automatically extracted using rule-based and conditional random field (CRF) methods. The proposed system can retrieve results that are 97% relevant to the accident cases the user intended and can automatically analyze knowledge with accuracies of 93.75% and 84.13% for the rule-based and CRF models, respectively. The results demonstrate the potential of knowledge discovery from accident reports for more-effective safety management.
Laurent, J and Leicht, R M (2019) Practices for Designing Cross-Functional Teams for Integrated Project Delivery. Journal of Construction Engineering and Management, 145(03).
Lindhard, S M, Hamzeh, F, Gonzalez, V A, Wandahl, S and Ussing, L F (2019) Impact of Activity Sequencing on Reducing Variability. Journal of Construction Engineering and Management, 145(03).
Monzer, N, Fayek, A R, Lourenzutti, R and Siraj, N B (2019) Aggregation-Based Framework for Construction Risk Assessment with Heterogeneous Groups of Experts. Journal of Construction Engineering and Management, 145(03).
Nguyen, L H (2019) Relationships between Critical Factors Related to Team Behaviors and Client Satisfaction in Construction Project Organizations. Journal of Construction Engineering and Management, 145(03).
Su, Z, Wei, H, Zou, X and Qi, J (2019) Zero-One Formulation for a Partial Resource-Constrained Project Scheduling Problem with Generalized Precedence Relations. Journal of Construction Engineering and Management, 145(03).
Wang, Q, Guo, Z, Mintah, K, Li, Q, Mei, T and Li, P (2019) Cell-Based Transport Path Obstruction Detection Approach for 4D BIM Construction Planning. Journal of Construction Engineering and Management, 145(03).
Zhang, H, Yan, X, Li, H, Jin, R and Fu, H (2019) Real-Time Alarming, Monitoring, and Locating for Non-Hard-Hat Use in Construction. Journal of Construction Engineering and Management, 145(03).