As the patent applications in China keep soaring up, the Chinese Patent Office initiated a patent analysis program in 2010 with the aim of helping the public to better use patent information. This post gives an overview of the program, and provides some sample results from it.
Deep involvement of patent examiners and industry
The theme of this program is “coming from industry, basing on industry and promoting industry”. In order to be chosen under the program, patent analysis projects are selected based on industry demands. Those are usually the core industries featured by innovation and economic transformation such as LCD (Liquid Crystal Display), IOT (Internet of Things), and Smart Phones.
When a project is selected, examiners from the corresponding technology field will do the main patent analysis work with engineers from the outside. In the past four years, about 400 patent examiners from nine examination departments have been involved in 38 projects, resulting in 28 industry patent analysis reports, and a patent analysis handbook. This program has been well received, and the China Patent Office is now doing nationwide patent analysis training for the public.
The SIPO patent analysis program has resulted in many remarkable patent analysis results, and many new patent analysis methods have been developed during the process. Here are some sample results (methods and charts).
A Sample Method of Patent Mapping
In the project that the author worked on, the Automotive Passive Safety Industry patent analysis project, a new patent mapping method based on Expanded Family Based Citation (EFB Citation for short) was developed. And below is an overview of this method.
When you are trying to map the patents of a competitor in a specific technology field, in a certain country, China for example, you may use the patent family as a bridge to find “hidden” citations, and uncover “hidden” connections. By using this method, the impact of citation information deficiencies, such as citation information of a patent granted in one Patent Office is not available (for example, citation of Indian Patent No. 206553 is not available while its family member WO2008047380A3 has its citation available) because that PTO has not set up the IT technology to record the citation information or for unknown reasons the citation information for patents granted is not recorded (for example, citation of China Patent No. CN1223312C is not available while CN1117754C’s citation is available), can be mitigated.
The method works as follows: First, choose a Patent P1 of Target X in Country Y, then find patent families of that Patent P1, then retrieve (backward) citations of all patent family members, then ONLY keep (backward) citations of Target X, then find patent families of those kept (backward) citations and ONLY keep granted patents from Country Y. Then a connection is made between the Patent P1, and those finally kept granted patents, which presumably have “hidden” technology relations to the original patent (P1). Chart 1 below shows the workflow, while Chart 2 shows a real-world example based on this method.
More information regarding this method can be found at ssrn.com. Also, Tony Trippe, on this blog, has several pieces of good information regarding methods for working with citation information, and their use. These pieces have included an introduction to Examiner citations in the United States, and a method for determining whether forward citations are coming from an Examiner or an applicant.
More Sample Achievements from Past Projects
Below are two more Charts exemplifying achievements from past patent analysis projects, one relating to inventor analysis and the other showing a macro level patenting trend analysis.
Chart 3 is an inventor analysis looking at the Japanese Chemistry company Toray Group in the field of PAN-based carbon fiber technology. In this case, the important inventors working on different generations of products (T300-T1000, MJ) are displayed.
From Chart 3, a reader can easily identify who is the central inventor for a specific generation of product and who the co-inventors are.
Chart 4 shows global and Chinese patent application status in the automotive passive safety industry, where the application status of four main sectors, i.e. airbag, seat belt, seat, and car body technology fields are displayed.
This Chart exemplifies one kind of expression of macro patent application trend in a certain industry, where a reader is able to see the trend with a quick glance.
In 2014, SIPO renewed the Patent Analysis Program based on the success of past programs in 2010-2013 which have gained strong well-received feedbacks from the industries, and this time it is soliciting projects mainly from the first certified national intellectual property demonstration for enterprises and competitive enterprises. About 40 projects on key products, and services from strategic emerging industries are being chosen as this year’s target.
Binqiang Liu is LLM in IP graduate from UNH Law (formerly Franklin Pierce Law Center) at Concord, New Hampshire. Before coming to US, Mr. Liu was a patent examiner at China Patent Office for more than 7 years. He has both Bachelor and Master Degrees in Mechanical Engineering and a post-graduate Master Diploma in China Civil and Commercial Law. He is experienced in patent examination, patent analysis and patent policy study.
Mr. Liu speaks at IP forums and conferences held by various institutions, including Tsinghua University School of Law, Peking University School of Law and China Patent Agent Committee and Industrial Committees. He has also spoken on China Utility Model Patent at the PIUG 2013 Northeast Conference, on SIPO Patent Databases and China Medicine Patent Search at the PIUG 2014 Biotech Conference and on Mining the Treasures for Competence of Human Resource & Technology Using Patent Information at the PIUG 2014 Annual Conference.
Mr. Liu is a regular writer and has published more than 20 papers on patent related topics published at various journals both in China and in US. He is member of PIUG and other associations (ABA, AIPLA, FBA, INTA and LES).