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• W4377018023 startingPage "101421" @default.
• W4377018023 abstract "Identifying research fronts is an essential aspect of promoting scientific development. Many researchers choose their research directions and topics by analyzing their field's current research fronts. Many previous researchers have used academic papers or patents to identify research fronts; however, this is potentially outdated and reduces the prospective value of the research front detection. Considering this, this work proposes adapted indicators to conduct research front topic detection based on research grant data, which aims to identify research front topics and forecast trends using path analysis. First, research topics were identified using topic modeling, and then the mapping relations from topics to both fund projects and cross-domain categories were built. Then, research front topics were detected by multi-dimensional measurements, and the evolution of research topics was analyzed using topic evolution visualization to predict development trends. Finally, the Brillouin index was used to measure the cross-domain degree. Our method was evaluated using a dataset from the field of health informatics and was shown to be effective in research front identification. We found that the proposed adapted indicators were informative in identifying the evolutional trends in the health informatics field. In addition, research grants with higher cross-domain degrees are more likely to receive a high amount of funding." @default.
• W4377018023 created "2023-05-19" @default.
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• W4377018023 date "2023-08-01" @default.
• W4377018023 modified "2023-09-26" @default.
• W4377018023 title "Research frontier detection and analysis based on research grants information: A case study on health informatics in the US" @default.
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• W4377018023 doi "https://doi.org/10.1016/j.joi.2023.101421" @default.
• W4377018023 hasPublicationYear "2023" @default.
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