Towards Automated Identification of Technological Trajectories

The paper presents a text mining approach to identifying technological trajectories. The main problem addressed is the selection of documents related to a particular technology. These documents are needed to identify a trajectory of the technology. Two different methods were compared (based on word2vec and lexical-morphological and syntactic search). The aim of developed approach is to retrieve more information about a given technology and about technologies that could affect its development. We present the results of experiments on a dataset containing over 4.4 million of documents as a part of USPTO patent database. Self-driving car technology was chosen as an example. The result of the research shows that the developed methods are useful for automated information retrieval as the first stage of the analysis and identification of technological trajectories. © Springer Nature Switzerland AG 2019.

Авторы
Volkov S.S. 1 , Devyatkin D.A. 2 , Sochenkov I.V. 2, 5 , Tikhomirov I.A. 3 , Toganova N.V.4
Сборник материалов конференции
Издательство
Springer Verlag
Язык
Английский
Страницы
143-153
Статус
Опубликовано
Том
1093
Год
2019
Организации
  • 1 Peoples’ Friendship University of Russia, Moscow, Russian Federation
  • 2 Federal Research Center “Computer Science and Control” of Russian Academy of Sciences, Moscow, Russian Federation
  • 3 Ministry of Science and Higher Education of the Russian Federation, Moscow, Russian Federation
  • 4 Institute of World Economy and International Relations of Russian Academy of Sciences, Moscow, Russian Federation
  • 5 Lomonosov Moscow State University, Moscow, Russian Federation
Ключевые слова
Similar document retrieval; Technological trajectories; Text mining
Дата создания
24.12.2019
Дата изменения
24.12.2019
Постоянная ссылка
https://repository.rudn.ru/ru/records/article/record/55546/