JPO Entrusted AI Business For Trademark Applications to FRONTEO

By: Mutsumi Fukuoka


Since 2016, the Japanese Patent Office (JPO) has been considering using Artificial Intelligence (AI) in the examination of patent, design, and trademark applications.  In April of 2017, the JPO announced “Action Plan for Utilization of AI Technology” (available in Japanese here) in April 2017.

As part of this Plan, the JPO will perform the following tasks: (1) make a list of the JPO’s entire operations (892 operations); (2) select 20 target operations in 15 fields (from the 892 operations) in view of their work volume and systemized situation; (3) consider the possibility of using AI technology based on reviews of external experts; and (4) conduct intermediate verification (evaluation by external experts, etc.).

As part of task (3), the JPO publicly sought companies to conduct empirical research projects to improve examination sophistication and efficiency for examination of trademark applications using AI technology.  In September 2017, the JPO selected and entered into a contract with “FRONTEO, Inc.,” which conducts big data analysis by making full use of AI technology.

According to the press release (available in Japanese here), FRONTEO proposed using the original AI engine “KIBIT,” which combines AI-related technology and behavioral information science, for the above project.

In the examination of trademark applications, “similar group codes” are used to judge whether classifications of designated goods/services are appropriate and whether the descriptions of the designated goods/services are definite.  If the names of goods/service do not exist in the existing database and the similar group codes are not automatically given, the examiners confirm individually to give the similar group codes, which takes considerable time.

FRONTEO is conducting empirical studies to improve the automatic assignment rate of similar group codes by utilizing the text analysis technique of KIBIT to reduce the manual labor of examiners.

The cost for the project, including the investigation of cost-effectiveness through the introduction of the system and the requirement for system reproduction, is approximately 40 million yen.