Open Access

ARTICLE

Identifying Cross Section Technology Application through Chinese Patent Analysis

Ping-Yu Hsu¹, Ming-Shien Cheng^2,*, Chih-Hao Wen³, Yen-Huei Ko¹

1 Department of Business Administration, National Central University, Jhongli City, 32001, Taiwan
2 Department of Industrial Engineering and Management, Ming Chi University of Technology, New Taipei City, 24301, Taiwan
3 Department of Communication Management, Shih-Hsin University, 11604, Taiwan

* Corresponding Author: Ming-Shien Cheng. Email:

Intelligent Automation & Soft Computing 2021, 27(1), 269-285. https://doi.org/10.32604/iasc.2021.013404

Received 05 August 2020; Accepted 15 October 2020; Issue published 07 January 2021

Abstract

Cross-domain technology application is the application of technology from one field to another to create a wide range of application opportunities. To successfully identify emerging technological application cross sections of patent documents is vital to the competitive advantage of companies, and even nations. An automatic process is needed to save precious resources of human experts and exploit huge numbers of patent documents. Chinese patent documents are the source data of our experiment. In this study, an identification algorithm was developed on the basis of a cross-collection mixture model to identify cross section and emerging technology from patents written in Chinese. To verify the algorithm’s effectiveness, documents in three transmission-related technology subclasses and one application technology category were collected from WEBPAT Taiwan. The former subclasses consist of H04B: Transmission; H04L: Transmission of digital information; and H04N: Image communication; and the latter is G06Q: Patents for administration, management, commerce, operation, supervision, or prediction by using data processing systems or methods. Growth rate detection was the most popular approach to forecast emerging technologies, our research defined the growth rate as the difference between the numbers of technology-containing documents published in different time. The emerging technology identified using the proposed method exhibited an average growth rate of 95.08%. By comparison, two benchmark methods identified emerging technology with average growth rates of 9.57% and 51.49%.

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Keywords

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