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Interpretation of Revision to Chapter 9 of the Guidelines for Patent Examination in China

Author:CHEN,Jinlin | UpdateTime:2020-04-28 | Hits:

The Chinese National Intellectual Property Administration (CNIPA) published a final version of the revision to Chapter 9, Part II of the Guidelines for Patent Examination on December 31, 2019, which will come into effect on February 1, 2020. The revision aims at special examination rules for patent applications of new areas such as artificial intelligence (AI), “Internet +”, big data, and blockchain. The final version is substantially the same as the draft revision published by the CNIPA on November 12, 2019, which was introduced in our Newsletter in November of 2019.

 

The revision involves examination rules related to statutory subject-matters, novelty/inventiveness, and drafting requirements regarding claims and specifications. However, more details are specified for the examination of statutory subject-matters and novelty/inventiveness, and ten examples are incorporated to illustrate examination rules regarding these two aspects. Only general principles are presented for drafting requirements of claims and specifications, but more specific rules will probably be provided in future revision to the Guidelines. In this article, examination rules for statutory subject-matters, and novelty/inventiveness will be interpreted based on the ten examples. 

 

1. BASIC PRINCIPLE

Patent applications related to AI, “Internet +”, big data, blockchain, etc. usually comprise features of rules or methods for mental activities such as algorithm and business rules or methods. As a basic principle, all features – including technical features and features of algorithm or business rules or methods – recited in a claim should be considered as a whole during examination, and it is not allowed to simply separate the technical features from the features of algorithm or business rules or methods. This principle prohibits examiners from simply disregarding features of algorithm or business rules or methods such as algorithm and business rules, which are probably the inventive points in the concerned new areas.

 

2. EXAMINATION RULES FOR STATUTORY SUBJECT-MATTERS

The examination of statutory subject-matters specifically involves two articles of the Chinese Patent Law. The first article is Article 25, clause 1, item (2) (simply referred to as Article 25 herein), which precludes a rule or method for mental activities from being patentable. The second article is Article 2, clause 2 (simply referred to as Article 2 herein), which stipulates an invention patent application should be a technical solution.

 

According to the revision to the Guidelines, an application related to the new areas is first examined based on Article 25, and if the application passes the test of Article 25, that is, the application is not a rule or method for mental activities, it is then examined based on Article 2. For Article 2, whether the application is a technical solution is examined.

 

2.1 EXAMINATION RULES FOR ARTICLE 25

For examination under Article 25, if a claim includes technical features in addition to features of rules or methods for mental activities, the claim as whole is not considered as a rule or method for mental activities, and thus cannot be ruled out from being patentable according to Article 25. On the contrary, if a claim does not include any technical features and includes only features of rules or methods for mental activities, then the claim is considered as a rule or method for mental activities and shall be ruled out according to Article 25.

 

EXAMPLE 1

Example 1 illustrates a method for mental activities without any technical features. Example 1 is a method of establishing a mathematical model. The method comprises steps of processing feature values and training models. However, the method does not involve any specific application area. Accordingly, the feature values in the method are abstract mathematical data, the processing steps are abstract mathematical method steps, and the resulting model is an abstract general classification model. Therefore, the solution of example 1 does not involve any technical feature, and is thus a method for mental activities stipulated in Article 25.

 

2.2 EXAMINATION RULES FOR ARTICLE 2

For Article 2, whether a claim is a technical solution is examined based on whether the claim as a whole uses a technical means subject to natural laws to solve a technical problem and achieve a technical effect. In particular, if algorithm steps defined in a claim are related to a technical problem and achieves a technical effect, the claim is a technical solution in principle. For example, an algorithm step can be considered as being related to a technical problem if the algorithm step processes data with definite technical meaning in a specific technical field and the execution of the algorithm involves using natural laws to solve a technical problem.

 

EXAMPLE 2

Example 2 is related to a training method for a convolutional neural network (CNN) model. In the method, convolution operation and maximum pooling operation are performed on training images at each convolution layer, and then the feature images obtained after the maximum pooling operation are further horizontally pooled, so that the trained CNN model can recognize images of any size when identifying an image category. In this example, the data processed in the steps of the training method are image data, reflecting that the training algorithm is related to a specific technical field of image information processing. The training method in this example solves a technical problem that a CNN model can only recognize images of a fixed size and achieves a technical effect of recognizing images of any size by a technical means of performing different processing and training on images in different convolutional layers. Therefore, example 2 is a technical solution stipulated in Article 2.

 

EXAMPLE 3

Example 3 is related to a use method of rental bikes. In the method, a user initiates a use request of a rental bike through a user terminal equipment to a server, the server provides location information and state information of rental bikes around the user to the user terminal equipment based on the location of the user terminal equipment, and the user can find an available rental bike based on the information displayed on the user terminal equipment. The method uses computer programs in the user terminal equipment and the server to control or lead the way a user uses rental bikes. Collecting, calculating and using location information and state information involved in the claim are technical means to solve a technical problem of easily and precisely finding a rental bike. Therefore, example 3 is a technical solution stipulated in Article 2.

 

EXAMPLE 4

Example 4 is related to a communication method between blockchain nodes. The communication method uses a CA certificate and a pre-configured CA trust list to improve the security of data stored in the blockchain. Using a certificate to enhance communication security is a technical means subject to natural laws to solve a technical problem. Therefore, example 4 is a technical solution stipulated in Article 2.

 

EXAMPLE 5

Example 5 is related to a consumption rebating method. The method uses a computer to execute a set of rebate rules based on consumption amount to provide consumers with coupons so as to increase the consumers’ consumption willingness. In this method, the rebate rule is an artificial rule, which is not subject to natural laws. Therefore, although the method is executed by a computer, the computer does not run a program subject to natural laws. Therefore, example 5 is not a technical solution stipulated in Article 2.

 

EXAMPLE 6

Example 6 is related to an analysis method for economic prosperity indexes based on characteristics of electricity consumption. The method evaluates economic prosperity indexes of districts based on electricity consumption characteristics of the districts by executing analysis algorithm on a computer. This example uses tools subject to economical laws rather than natural laws; therefore it is not a technical solution stipulated in Article 2.

 

3. EXAMINATION RULES FOR NOVELTY/INVENTIVENESS

As a principle, for novelty examination, all features defined in a claim, including technical features and features of algorithm or business rules or methods, shall be considered. For inventiveness examination, features of algorithm or business rules or methods and technical features that support each other functionally and have an interactive relationship with each other shall be considered as a whole to evaluate technical contributions to the prior art. In other words, examiners cannot disregard features of algorithm or business rules or methods directly for inventive examination, but need to consider whether the features of algorithm or business rules or methods support technical features functionally and have an interactive relationship with technical features to determine whether the features of algorithm or business rules or methods have technical contributions to the prior art. If the features of algorithm or business rules or methods have technical contributions to the prior art, the features of algorithm or business rules or methods shall be considered to have contributions regarding the inventiveness examination; otherwise, they shall not be considered to have contributions to inventive examination. "The features of algorithm or business rules or methods and the technical features support each other functionally and have an interactive relationship with each other" means that the features of algorithm or business rules or methods are closely combined with the technical features to form a technical means to solve a technical problem and obtain a corresponding technical effect.

 

Examples 7 to 10 are related to inventiveness examination. In examples 7 and 8, the distinctive features with respect to the closest prior art are algorithm features, but those algorithm features and related technical features support each other functionally and have an interactive relationship with each other. Therefore, those algorithm features are considered together with the technical features to evaluate inventiveness. In example 9, the distinctive features with respect to the closest prior art comprise both technical features and features of business rules, and they support each other functionally and have an interactive relationship with each other. Therefore, those technical features and features of business rules are considered together to evaluate inventiveness. In example 10, the distinctive feature with respect to the closet prior art is a feature of rules for mental activities, and it does not support a technical feature functionally and does not have an interactive relationship with a technical feature. Therefore, the feature of rules for mental activities is not considered to have technical contribution to the prior art.

 

EXAMPLE 7

Example 7 is related to a method for detecting fall states of a humanoid robot based on multi-sensor information. The distinctive features with respect to the closest prior art are a specific fuzzy algorithm. The specific fuzzy algorithm takes the posture information, ZMP point position information and walking stage information as input parameters to calculate the information for determining the stable states of the humanoid robot, which provides a basis for further issuing accurate posture adjustment instructions.

 

Therefore, the above algorithm features and other technical features such as determining the stable states of the humanoid robot defined in the claim are closely combined together to form a technical means, that is, they support each other functionally and interact with each other, and shall be considered together to evaluate inventiveness. Since no prior art discloses or teaches using the above fuzzy algorithm to determine the stable states of a humanoid robot, the solution of example 7 is considered to have inventive steps.

 

EXAMPLE 8

Example 8 is related to a multi-robot path planning system based on a cooperative evolution and multi-population genetic algorithm. The distinctive features with respect to the closest prior art are a Messy genetic algorithm for multi-robot path planning. The forward paths of the robots are obtained with optimization of the Messy genetic algorithm. Therefore, the above algorithm features and other technical features such as paths and locations of the robots defined in the claim support each other functionally and interact with each other, and shall be considered together to evaluate inventiveness. However, in example 8, another prior document discloses using various genetic algorithms to optimize paths, and Messy genetic algorithm can obtain better optimization results. Therefore, the solution of example 8 is considered to lack inventive steps in view of the combination of the two prior art documents.

 

EXAMPLE 9

Example 9 is related to a logistics distribution method. The distinctive features with respect to the closest prior art are notifying all ordering users within a delivery range in batch rather than notifying them one by one and accordingly different specific notification implementations such as  different data architectures and communication methods. The feature of notification rule and the features of specific notification implementations support each other functionally and interact with each other, and shall be considered together. Since no prior art discloses or teaches using the above features to improve delivery efficiency, the solution of example 9 is considered to have inventive steps.

 

EXAMPLE 10

Example 10 is related to a method for visualizing dynamic viewpoint evolution for an event. The method automatically collects information on an event published by people on social platforms, analyzes the emotions in the information, and visualizes changes of the emotions over time by coloring diagrams to be displayed in a computer. The closest prior art discloses a similar method, and the difference is only that the solution of example 10 uses a different emotion classification rule to determine the emotions and their changes. The emotion classification rule is an artificial rule, and the rule does not influence the coloring process. In other words, the feature of emotion classification rule and the technical feature of coloring process do not support each other functionally and do not interact with each other. Therefore, the distinctive feature is considered as an isolated feature of rules for mental activities, and even if no prior art document discloses such a feature, the solution of example 10 is considered to lack inventive steps since it has no technical contributions to the prior art.

 

Booming of new areas such as artificial intelligence (AI), “Internet +”, big data, and blockchain brings lots of legal issues. Patenting in those areas is one of them. We believe the authorities shall continue issuing new regulations regarding patenting in the new areas, such as more detailed regulations for drafting requirements of claims and specifications. As always, Liu Shen will keep up-to-date and provide our clients with well-informed advice.