Wang, H; Xu, S; Cui, D; Xu, H and Luo, H (2024) Information integration of regulation texts and tables for automated construction safety knowledge mapping. Journal of Construction Engineering and Management, 150(5): 04024034, ISSN 0733-9364
Abstract
The explicit safety knowledge contained in regulations in the form of texts and tables is crucial for construction safety management. However, the presence of rich semantic content within texts and the intricate layout of complex tables makes domain information extraction challenging. Therefore, this research proposed a hybrid approach to map safety knowledge graphs by automatically extracting information from both texts and tables in a scenario-oriented manner, combining rules and deep learning methods to achieve a balance between scene applicability and method flexibility. Furthermore, metrics from social network analysis (SNA) were applied to evaluate and verify the quality of the constructed knowledge graph. For extracting semantic information from text, the proposed approach supplemented the semantics information of the sentence and balanced the granularity of knowledge by combining the BERT-BiLSTM-CRF-based named entity recognition (NER) model and semantic role labeling (SRL)-based information extraction model. For irregular tables, a unified automatic extraction method was developed to process nested tables without preprocessing. The experiment constructed a comprehensive and scenario-oriented knowledge graph with 907 nodes, and showed high precision and recall for texts (89.37%, 85.42%) and tables (97.11%, 85.22%) on the test data. SNA results showed the proposed method ensured information richness and structural complexity.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | knowledge graphs; named entity recognition; regulation information extraction; semantic role labeling; social network analysis |
| Index terms: | semantics, information integration, automated construction, experiment, regulation, construction safety, complexity, deep learning, mapping, presence, social network analysis |
| Subjects: | environmental health, research methods, analytical methods, systems engineering, artificial intelligence, spatial and geospatial analysis, political science, automation and robotics, information systems, environmental science, data collection methods |
| Topics: | Digital Applications, Research Practice, Governance, Sustainability, Engineering Principles |
| Descriptive scope: | 5 PCTEA |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here