Work

Identification of Trends in Automotive Industries Based on Text Mining

Year: 2024

Type: article

Abstract: Understanding the trends of evolution in a technology is essential to make appropriate decisions. This paper aimed at mapping the technological evolution in automotive industries and understanding the main trends through patent data. Thus, the objective of this paper is to provide a structured overview for identifying the trend of patent in three automotive companies by employing text mining techniques. In natural language processing (NLP), text mining is used to determine several features such as segmentations and attributes of data. To achieve the objective, the abstract of patent documents in the period of the last two decades are mined from the DWPI database. To demonstrate the behaviour of selected patent documents, word cloud, co-occurrence networks and correspondence analysis are presented.

Source: Journal of Advanced Research in Applied Sciences and Engineering Technology

DOI: 10.37934/araset.60.4.157170

Authors: Hafizah Farhah Saipan Saipol, Syarifah Zyurina Nordin, Amir Syafiq Syamin Shah Amir Hamzah, Naoki Ohshima

Institutions: University of Technology Malaysia, Yamaguchi University

Language: English

Topic: Intellectual Property and Patents

Subfield: Management of Technology and Innovation

Field: Business, Management and Accounting

Domain: Social Sciences

SDG: Industry, innovation and infrastructure

Open Access status: hybrid

Funder: Japan International Cooperation Agency