Data Driven Detection of Technological Trajectories

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. © 2021, Springer Nature Switzerland AG.

Авторы
Сборник материалов конференции
Издательство
Springer Science and Business Media Deutschland GmbH
Язык
Английский
Страницы
204-215
Статус
Опубликовано
Том
1427
Год
2021
Организации
  • 1 Federal Research Center “Computer Science and Control” RAS, Moscow, Russian Federation
  • 2 Peoples’ Friendship University of Russia (RUDN University), Moscow, Russian Federation
Ключевые слова
Keywords; Similar documents retrieval; Technological trajectories; Text mining
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