Technological topic analysis of standard-essential patents based on the improved Latent Dirichlet Allocation (LDA) model

ABSTRACT

Standard-essential patents (SEPs) are an important technological resource for firms in the telecommunication industry. The utilisation of technological topic analysis to reveal the global development dynamics of SEPs has significant theoretical and practical implications. First, this study defines the phrase extraction rules and constructs a phrase importance evaluation model to extract key technical phrases in the patent text. Second, the extracted key phrases are used as input for the Latent Dirichlet Allocation (LDA) model, and the relative independence (RI) model is proposed to determine the optimal number of topics based on two dimensions of coherence and similarity. Finally, the technological topic analysis based on the improved LDA model is performed on 30,154 texts of declared 5G SEPs. The results show that (1) the RI model can better identify the optimal number of topics for the LDA model; (2) 23 key technologies and four hot spots in 5G are identified based on the improved LDA model; (3) different firms have different technological layouts, and the diversification trend of technology development appears; and (4) the forecasting results also reveal the dynamics of emerging and declining technical areas in the 5G industry.

KEYWORDS:

• Standard-essential patent
• LDA
• technological development
• telecommunication

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by National Social Science Fund of China [grant number 21CJL009]; Humanities and Social Science Project of Ministry of Education in China [grant number 21YJA630113]; Graduate Research and Innovation Projects of Tianjin [grant number 2020YJSB036].

Notes on contributors

Chen Tian

Chen Tian is currently a Ph.D. candidate in Public Administration at Tianjin University’s College of Management and Economics. His research interests include technological innovation and patent analysis.

Junyan Zhang

Junyan Zhang received the Ph.D. degree from Tianjin University in management science and engineering in 2006. She is currently an Associate Professor in Tianjin University. Her research interests include standard essential patents and technology transfer.

Dayong Liu

Dayong Liu received the Ph.D. degree from Nankai University in Economics in 2014. He is currently an Associate Professor in Tianjin University. His research interests include innovation management, intellectual property and allocation mechanism of technology factors.

Qing Wang

Qing Wang received the Ph.D. degree from Tianjin University in Information and Communication Engineering in 2010. She is currently an Associate Professor in Tianjin University. Her research interests include wireless communication, passive radar and intelligent signal processing.

Shen Lin

Shen Lin received the master degree from Tianjin University in Communication and Information System in 2007. She is currently an Associate Researcher and Deputy Director of Patent Examination Cooperation (Beijing) Center of the Patent Office, People' s Republic of China National Intellectual Property Administration. She has rich experience in patent examination and service.