Abstract
The paper presents a text mining approach to identifying and analyzing technological trajectories. The main problem addressed is the selection of documents related to a particular technology. These documents are needed to detect a trajectory of technology. The approach includes new keyword and keyphrase detection method, word2vec embeddings-based similar document search method and fuzzy logic-based methodology for revealing technology dynamics. USPTO patent database was used for experiments. The database contains more than 4.7 million documents from 1996 to 2020. Self-driving car technology was chosen as an example. The result of the experiment shows that the developed methods are useful for effective searching and analyzing information about given technologies.
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Acknowledgements
This study was supported by Russian Foundation for Basic Research, grant number 17-29-07016 of i_m.
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Volkov, S., Devyatkin, D., Tikhomirov, I., Sochenkov, I. (2021). Data Driven Detection of Technological Trajectories. In: Sychev, A., Makhortov, S., Thalheim, B. (eds) Data Analytics and Management in Data Intensive Domains. DAMDID/RCDL 2020. Communications in Computer and Information Science, vol 1427. Springer, Cham. https://doi.org/10.1007/978-3-030-81200-3_15
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