ArticlePloS one2024
Application of a text mining method in navigation and communication for enhancing maritime safety.
Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This paper introduces a model for the translation of natural language into ontology and vice versa in an autonomous navigation system of a sea-going vessel. The system comprehensively executes communication tasks at sea. The authors use machine learning methods in the field of text mining and basic and additional properties of ontologies. The newly developed ontology is applicable in shipping. The key elements of the prototype are the sequence of communication commands given from the ship's bridge, decomposition, extraction of the communication sequence and the rule base. The presented model has been implemented and verified in selected scenarios of collision situations at sea. The test results confirm that the assumptions, the designed system architecture and the algorithms in the prototype are correct.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.