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- W3177022616 abstract "AbstractA large amount of data resources in daily management have accumulated in the the port safety supervision department and a knowledge database containing structured and unstructured data has established. The database contains data resources for daily management, safety supervision, accident handling, etc. In the process of using these data, it is faced with the problems of complex knowledge base, difficulty in retrieving related information, and low retrieval accuracy. Therefore, an ontology-based dangerous goods knowledge model is proposed, which supports both structured and unstructured data. Using semantic analysis and data labeling technology, a port dangerous goods knowledge base and a personalized information retrieval framework are established, and the retrieval process and result ranking optimization algorithm are proposed. This method improves the information retrieval efficiency, information recognition and service capabilities of managers in port safety supervision.KeywordsDangerous goods in portSafety supervisionKnowledge modelRetrieval algorithm" @default.
- W3177022616 created "2021-07-05" @default.
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- W3177022616 date "2021-01-01" @default.
- W3177022616 modified "2023-09-27" @default.
- W3177022616 title "Research and Application of Ontology-Based Knowledge Model for Dangerous Goods in Port" @default.
- W3177022616 cites W2114355521 @default.
- W3177022616 doi "https://doi.org/10.1007/978-3-030-70665-4_99" @default.
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