Data Driven Detection of Technological Trajectories

Sergey Volkov, Dmitry Devyatkin, Ilya Tikhomirov, Ilya Sochenkov

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.

External IDs:dblp:conf/rcdl/VolkovDTS20