Introduction And Interpretation Of The Revisions To The "Patent Examination Guidelines" (2023) Concerning Computer Program Inventions

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The newly revised "Patent Examination Guidelines" (2023) came into effect on January 20, 2024. Below is an introduction and interpretation of the main revisions...
China Intellectual Property
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The newly revised "Patent Examination Guidelines" (2023) came into effect on January 20, 2024. Below is an introduction and interpretation of the main revisions to the examination of patent applications involving computer programs, as detailed in Part II, Chapter IX of the "Patent Examination Guidelines".

1. Clarification on the Eligibility of Computer Program Products as Subject Matter in Claims (Section 5.2, Part II, Chapter IX)

The revised guidelines explicitly allow computer program products to be the subject matter of claims. The claims of a patent application involving a computer program can be drafted as method claims or product claims, such as devices that implement the method, computer-readable storage media, or computer program products. The guidelines further clarify that computer program products should be understood as software products whose solutions are primarily realized through computer programs.

Interpretation: With the development of internet technology, an increasing amount of computer software no longer relies on traditional physical storage media such as CDs or disks. Instead, it is transmitted, distributed, and downloaded over the internet in the form of signals. This revision enriches the types of protectable subject matter for patent applications involving computer programs, allowing computer program products to be considered as a type of protectable subject matter. This means that protection for computer programs is no longer limited to physical storage media and clarifies that computer program products also fall under product claims.

2. Addition of Criteria and Examples for Algorithmic Improvements in Internal Computer System Performance (Sections 6.1.2 and 6.2, Part II, Chapter IX)

The revised guidelines include new criteria and examples for the examination of subjects involving improvements in artificial intelligence and big data algorithms. If the solution of the claim involves improvements in deep learning, classification, clustering, and other AI and big data algorithms that have specific technical associations with the internal structure of computer systems, and addresses technical issues such as enhancing hardware computational efficiency or execution effects, including reducing data storage and transmission volumes and improving hardware processing speed, then the solution defined by the claim is considered a technical scheme as described in Article 2, Paragraph 2 of the Patent Law.

Interpretation: The current guidelines stipulate that the examination should focus on the solution for which protection is sought, as defined by the claims. During the examination, it is not appropriate to simply separate technical features from algorithmic features or business rules and methods. Instead, all content recorded in the claims should be considered as a whole, and an analysis should be conducted of the technical means involved, the technical problems solved, and the technical effects achieved. The guidelines also specify that when examining whether a claim containing algorithmic features or business rules and methods features constitutes a technical scheme, all features recorded in the claim must be considered comprehensively. Section 6.1.2 clarifies that if there is a specific technical association between the algorithm and the internal structure of the computer system, and it addresses technical issues related to improving hardware computational efficiency or execution effects, achieving technical effects that conform to natural laws in the internal performance of computer systems, then it is considered a technical scheme under Article 2, Paragraph 2 of the Patent Law.

3. Addition of Criteria and Examples for Big Data Processing (Sections 6.1.2 and 6.2, Part II, Chapter IX)

The revised guidelines include new criteria and examples for the examination of subjects involving big data processing. If the solution of the claim processes big data in a specific application field, using classification, clustering, regression analysis, neural networks, etc., to mine inherent correlations in the data that conform to natural laws, and addresses technical issues on how to improve the reliability or accuracy of big data analysis in a specific application field, and achieves corresponding technical effects, then the solution defined by the claim is considered a technical scheme as described in Article 2, Paragraph 2 of the Patent Law.

Interpretation: Section 6.1.2 clarifies that when the solution processes big data in a specific application field, if it uncovers inherent correlations in the data that conform to natural laws and addresses technical issues on how to improve the reliability or accuracy of big data analysis in that field, then the solution is considered a technical scheme under Article 2, Paragraph 2 of the Patent Law. In the examination example 6 of Section 6.2, the analysis method for the usage propensity of electronic coupons involves big data processing in the specific application of electronic coupons. The solution processes big data related to electronic coupons, classifying them, obtaining sample data, determining behavioral characteristics, and training models. Through model training, it uncovers inherent correlations between user behavioral characteristics and the usage propensity of electronic coupons, which conform to natural laws, addressing the technical issue of improving the accuracy of analyzing user electronic coupon usage propensities and achieving corresponding technical effects. This solution is considered a technical scheme under Article 2, Paragraph 2 of the Patent Law. In the field of big data processing and analysis, individual user behavior may exhibit subjectivity and randomness, but the behavior of a group of users often follows patterns, and the relationships between different behaviors can reflect and conform to specific natural laws. Therefore, the means used to uncover the relationships between different user behaviors also constitute technical means. In the examination example 10 of Section 6.2, the price prediction method for financial products involves big data processing in the financial field. The solution processes big data related to financial products, using neural network models to uncover inherent correlations between historical and future price data of financial products. However, the price trend of financial products follows economic laws, and historical prices do not determine future price trends. There is no inherent correlation between historical and future price data that conforms to natural laws. The solution addresses the issue of predicting the prices of financial products, which does not constitute a technical problem, and the corresponding effect is not a technical effect. This solution does not fall under the technical scheme as stipulated in Article 2, Paragraph 2 of the Patent Law.

In summary, the revisions to the "Patent Examination Guidelines" (2023) represent a significant step forward in addressing the unique challenges and opportunities presented by computer programs and big data in the patent system. By explicitly recognizing computer program products as a valid subject matter for patent claims and providing clear criteria for assessing the patentability of algorithmic improvements and big data processing solutions, the guidelines facilitate a more nuanced and technically informed examination process. This not only promotes innovation in the digital and data-driven sectors but also ensures that the patent protection aligns with the evolving nature of technological advancements. The interpretative guidance offered by the revised guidelines helps to clarify the complex relationship between technical features and algorithmic aspects, reinforcing the importance of considering the entirety of a claim when assessing its compliance with patentability requirements. As a result, these revisions contribute to a more robust, adaptable, and future-proof patent framework that can effectively capture and protect the innovative outcomes of the digital era.

The content of this article is intended to provide a general guide to the subject matter. Specialist advice should be sought about your specific circumstances.

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