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• W4386870714 abstract "We propose a reproducible, automated, scalable, and free method for automated bibliometric analysis that requires little computing power. We explain how firms can use this method with open source data from public repositories to generate unbiased insights about future technology developments, and to assess the maturity, security and likely future development of particular technology domains. The method is demonstrated by systematic text mining of more than 400,000 e-prints from the arXiv repository." @default.
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• W4386870714 date "2023-01-01" @default.
• W4386870714 modified "2023-09-27" @default.
• W4386870714 title "Identification of Future Cyberdefense Technology by Text Mining" @default.
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• W4386870714 doi "https://doi.org/10.1007/978-3-031-30191-9_5" @default.
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