China National Intellectual Property Administration Proclamation
No.343
In order to fully implement the decision-making arrangements of the CPC Central Committee and the State Council on strengthening the protection of intellectual property rights, and to respond to the demand of innovative subjects for further clarifying the rules for patent application examination in new fields involving new formats such as artificial intelligence, it is decided to amend the Patent Examination Guide, which is hereby promulgated and shall come into force as of February 1, 2020.
It is hereby announced.
China National Intellectual Property Administration
December 31, 2019
China National Intellectual Property Administration’s Decision on Amending the Patent Examination Guide
China National Intellectual Property Administration decided to amend the Patent Examination Guide.
Section 6 is added to Chapter 9 of Part II of the Patent Examination Guide, which reads as follows:
6. Relevant provisions on the examination of application for a patent for invention containing algorithmic features or business rules and methods.
Invention patent applications involving artificial intelligence, "internet plus", big data and blockchain generally contain rules and method features of intellectual activities such as algorithms or business rules and methods. This section aims to stipulate the examination particularity of such applications according to the Patent Law and its implementation rules.
6.1 Review benchmarks
The examination shall be conducted for the solution to be protected, that is, the solution defined in the claims. In the examination, technical features and algorithm features or business rules and methods should not be simply separated, but all the contents recorded in the claim should be taken as a whole, and the technical means involved, technical problems solved and technical effects obtained should be analyzed.
6.1.1 Examination according to Item (2) of Paragraph 1 of Article 25 of the Patent Law
If the claim involves abstract algorithms or simple business rules and methods, and does not contain any technical features, it belongs to the rules and methods of intellectual activities stipulated in Item (2) of Paragraph 1 of Article 25 of the Patent Law and should not be granted a patent right. For example, a mathematical model building method based on abstract algorithm and without any technical features belongs to the situation that the patent right should not be granted as stipulated in Item (2) of Paragraph 1 of Article 25 of the Patent Law. Another example is a method of rebate according to the user’s consumption quota. The features contained in this method are all business rules and method features related to rebate rules, and do not contain any technical features, which belongs to the situation that the patent right should not be granted as stipulated in Item (2) of Paragraph 1 of Article 25 of the Patent Law.
If the claim contains technical features in addition to algorithmic features or business rules and methods, and the claim as a whole is not a rule and method of intellectual activities, the possibility of obtaining a patent right shall not be ruled out according to Item (2) of Paragraph 1 of Article 25 of the Patent Law.
6.1.2 Examination according to Paragraph 2 of Article 2 of the Patent Law
If the claim to be protected as a whole does not belong to the situation that the first paragraph (2) of Article 25 of the Patent Law excludes obtaining a patent right, it is necessary to examine whether it belongs to the technical scheme described in the second paragraph of Article 2 of the Patent Law.
When examining whether a claim containing algorithm features or business rules and methods features belongs to a technical scheme, it is necessary to consider all the features recorded in the claim as a whole. If the claim records that the technical problem to be solved adopts the technical means of using the laws of nature, and thus obtains the technical effect in line with the laws of nature, the solution defined in the claim belongs to the technical scheme described in the second paragraph of Article 2 of the Patent Law. For example, if the steps involved in the algorithm in the claim are closely related to the technical problem to be solved, such as the data processed by the algorithm is data with exact technical meaning in the technical field, and the execution of the algorithm can directly reflect the process of solving a technical problem by using natural laws and obtain technical effects, then the solution defined in the claim usually belongs to the technical solution described in Article 2, paragraph 2, of the Patent Law.
6.1.3 Review of novelty and creativity
When examining the novelty of an application for a patent for invention containing algorithmic features or business rules and methods, all the features recorded in the claims should be considered, including both technical features and algorithmic features or business rules and methods.
When creatively examining an application for a patent for invention that contains both technical features and algorithmic features or business rules and methods, the algorithmic features or business rules and methods that are functionally mutually supportive and have an interactive relationship with the technical features should be considered as a whole. "Functionally supporting each other and interacting with each other" means that algorithm features or business rules and method features are closely combined with technical features to form a technical means to solve a technical problem and obtain corresponding technical effects.
For example, if the algorithm in the claim is applied to a specific technical field and can solve specific technical problems, it can be considered that the algorithm features and technical features support each other functionally and have an interactive relationship, and the algorithm features become an integral part of the adopted technical means, and the contribution of the algorithm features to the technical scheme should be considered when conducting creative review.
For another example, if the implementation of the business rules and method features in the claims requires adjustment or improvement of technical means, it can be considered that the business rules and method features and technical features support each other functionally and have an interactive relationship, and the contribution of the business rules and method features to the technical scheme should be considered when conducting creative review.
6.2 Review examples
Below, according to the above-mentioned examination criteria, an examination example of an application for a patent for invention containing algorithm features or business rules and methods features is given.
(1) An application for a patent for invention, which is within the scope of Item (2) of Paragraph 1 of Article 25 of the Patent Law and contains features of algorithm or business rules and methods, does not belong to the object of patent protection.
[Example 1]
A method of establishing mathematical model
Overview of application content
The solution of invention patent application is a method of establishing mathematical model, which improves the accuracy of modeling by increasing the number of training samples. This modeling method takes the training samples of other classification tasks related to the first classification task as the training samples of the mathematical model of the first classification task, thus increasing the number of training samples, and training related mathematical models by using the eigenvalues, extracting eigenvalues and label values of the training samples, and finally obtaining the mathematical model of the first classification task, which overcomes the defect of poor modeling accuracy due to over-fitting caused by few training samples.
Claim of application
A method for establishing a mathematical model is characterized by comprising the following steps:
According to the feature values in the training samples of the first classification task and the feature values in the training samples of at least one second classification task, the initial feature extraction model is trained to obtain a target feature extraction model; Wherein the second classification task is other classification tasks related to the first classification task;
According to the target feature extraction model, the feature values in each training sample of the first classification task are respectively processed to obtain extracted feature values corresponding to each training sample;
Combining the extracted feature values and label values corresponding to each training sample to extract training samples, and training an initial classification model to obtain a target classification model;
Combining the target classification model and the target feature extraction model into a mathematical model of the first classification task.
Analysis and conclusion
The solution doesn’t involve any specific application field, in which the characteristic value, extracted characteristic value, label value, target classification model and target feature extraction model of the training samples are all abstract general data, and the processing process of training the mathematical model by using the relevant data of the training samples is a series of abstract mathematical method steps, and the final result is also an abstract general classification mathematical model. This scheme is an abstract model building method, and its processing object, process and result are not related to the combination with specific application fields, which belongs to the optimization of abstract mathematical methods, and the whole scheme does not include any technical features. The solution of the patent application for this invention belongs to the rules and methods of intellectual activities stipulated in Item (2) of Paragraph 1 of Article 25 of the Patent Law, and does not belong to the object of patent protection.
(2) An application for a patent for invention that uses technical means to solve technical problems and obtains technical effects, including algorithmic features or business rules and methods, belongs to the technical scheme specified in the second paragraph of Article 2 of the Patent Law, and therefore belongs to the object of patent protection.
[Example 2]
A training method of convolutional neural network model
Overview of application content
The solution of the invention patent application is to perform convolution operation and maximum pooling operation on the training image at all levels of convolution layer, and then perform horizontal pooling operation on the feature image obtained after the maximum pooling operation, so that the trained CNN model can identify the image to be identified with any size when identifying the image category.
Claim of application
A training method for CNN model of convolutional neural network is characterized by comprising the following steps:
Acquiring initial model parameters of a CNN model to be trained, wherein the initial model parameters comprise initial convolution kernels of convolution layers at all levels, initial bias matrices of convolution layers at all levels, initial weight matrices of fully connected layers and initial bias vectors of fully connected layers;
Acquiring a plurality of training images;
Performing convolution operation and maximum pooling operation on each training image on each convolution layer by using the initial convolution kernel and the initial offset matrix on each convolution layer to obtain a first feature image of each training image on each convolution layer;
Performing horizontal pooling operation on a first characteristic image of each training image on at least one convolution layer to obtain a second characteristic image of each training image on each convolution layer;
Determining the feature vector of each training image according to the second feature image of each training image on each convolution layer;
Processing each feature vector according to the initial weight matrix and the initial bias vector to obtain a category probability vector of each training image;
Calculating a class error according to the class probability vector of each training image and the initial class of each training image;
Adjusting the model parameters of the CNN model to be trained based on the category error;
Based on the adjusted model parameters and the plurality of training images, the process of adjusting model parameters is continued until the number of iterations reaches a preset number;
The model parameters obtained when the number of iterations reaches the preset number are used as the model parameters of the trained CNN model.
Analysis and conclusion
This solution is a training method for CNN model of convolutional neural network, in which the data processed in each step of the model training method are all image data and how to process the image data in each step is made clear, which shows that the neural network training algorithm is closely related to image information processing. The solution is how to overcome the technical problem that CNN model can only identify images with fixed size. It adopts different processing and training methods for images on different convolution layers, and uses the technical means of following the laws of nature to obtain the technical effect that the trained CNN model can identify images with any size to be identified. Therefore, the solution of the application for a patent for invention belongs to the technical scheme stipulated in the second paragraph of Article 2 of the Patent Law and belongs to the object of patent protection.
[Example 3]
Method for using bike-sharing
Overview of application content
An application for a patent for invention proposes a method for using bike-sharing. By obtaining the position information of the user terminal equipment and the state information of bike-sharing within a certain distance, the user can accurately find the bike-sharing that can ride according to the state information of bike-sharing, and guide the user to stop by prompting. This method facilitates the use and management of bike-sharing, saves the user’s time and improves the user’s experience.
Claim of application
The use method of bike-sharing is characterized by comprising the following steps:
Step 1, a user sends a request for using bike-sharing to a server through terminal equipment;
Step 2, the server obtains the first location information of the user, looks up the second location information of bike-sharing within a certain distance corresponding to the first location information and the state information of these bike-sharing, and sends the second location information and the state information of bike-sharing to the terminal equipment, wherein the first location information and the second location information are obtained through GPS signals;
Step 3, the user finds the riding target bike-sharing according to the position information of bike-sharing displayed on the terminal equipment;
Step 4, the user scans the two-dimensional code on the car body of the target bike-sharing through the terminal equipment, and obtains the use authority of the target bike-sharing after passing the server authentication;
Step 5, the server pushes the parking reminder to the user according to the riding situation, and if the user parks the car in the designated area, the preferential tariff is adopted for charging, otherwise, the standard tariff is adopted for charging;
Step 6, the user makes a choice according to the prompt, and after the riding is finished, the user locks the car by bike-sharing, and bike-sharing sends a riding completion signal to the server after detecting the car locking state.
Analysis and conclusion
The solution involves a method of using bike-sharing, and the technical problem to be solved is how to accurately find the location of and open the bike-sharing. The solution realizes the control and guidance of users’ use of bike-sharing by executing computer programs on terminal equipment and servers, which reflects the control of collecting and calculating data such as location information and authentication, and uses the technical means of following natural laws to achieve the technical effects of accurately finding the location of bike-sharing and opening bike-sharing. Therefore, the solution of the invention patent application belongs to the technical scheme stipulated in the second paragraph of Article 2 of the Patent Law and belongs to the object of patent protection.
[Example 4]
Communication method and device between blockchain nodes
Overview of application content
The invention patent application provides a communication method and device for blockchain nodes. Before establishing communication connection, business nodes in the blockchain can determine whether to establish communication connection according to the CA certificate carried in the communication request and the pre-configured CA trust list, thus reducing the possibility of business nodes leaking private data and improving the security of data stored in the blockchain.
Claim of application
The invention relates to a communication method of blockchain nodes, wherein the blockchain nodes in a blockchain network comprise service nodes, wherein the service nodes store certificates sent by a certificate authority center (CA) and are pre-configured with a CA trust list, and the method comprises the following steps:
A first blockchain node receives a communication request sent by a second blockchain node, wherein the communication request carries a second certificate of the second blockchain node;
Determining a CA identifier corresponding to the second certificate;
Judging whether the determined CA identifier corresponding to the second certificate exists in the CA trust list;
If so, establishing communication connection with the second blockchain node;
If not, no communication connection is established with the second blockchain node.
Analysis and conclusion
The problem to be solved in this application is how to prevent the blockchain service nodes from leaking user privacy data in the alliance chain network, which belongs to the technical problem of improving the security of blockchain data. By carrying CA certificate in communication request and configuring CA trust list in advance, whether to establish a connection is determined, which limits the objects that the service nodes can establish a connection. By using the technical means of following natural laws, the technical effects of safe communication between service nodes and reducing the possibility of leaking privacy data by service nodes are obtained. Therefore, the solution of the invention patent application belongs to the technical scheme stipulated in the second paragraph of Article 2 of the Patent Law and belongs to the object of patent protection.
(3) An application for a patent for invention that contains algorithmic features or business rules and methods without solving technical problems, using technical means or obtaining technical effects does not belong to the technical scheme specified in the second paragraph of Article 2 of the Patent Law, and therefore does not belong to the object of patent protection.
[Example 5]
Method for rebate of consumption
Overview of application content
The invention patent application puts forward a method of consumer rebate, which gives cash coupons to consumers through computer execution of set rebate rules, thus improving the consumer’s willingness to consume and obtaining more profits for businesses.
Claim of application
A consumption rebate method is characterized by comprising the following steps:
When a user makes a consumption in a merchant, the merchant returns a certain cash coupon according to the amount of consumption, specifically,
The merchant uses a computer to calculate the user’s consumption amount, and divides the user’s consumption amount R into m intervals, where m is an integer, and the values from interval 1 to interval m are from small to large, and the amount of cash coupons returned is also divided into m values, and the m values are also arranged from small to large;
According to the calculated value of the computer, it is judged that the rebate amount is the first value when the user’s current consumption amount is in the interval 1, and the rebate amount is the second value when the user’s current consumption amount is in the interval 2, and so on, and the rebate amount of the corresponding interval is returned to the user.
Analysis and conclusion
The solution involves a method of rebate for consumption. The method is executed by a computer, and its processing object is the user’s consumption data. The problem to be solved is how to promote the user’s consumption, which does not constitute a technical problem. The method adopted is to implement the rebate rules set artificially by the computer, but the computer is limited to determining the rebate amount according to the specified rules, which is not bound by natural laws. Therefore, no technical means are used. The effect obtained by this scheme is only to promote the user’s consumption, not a technology that conforms to natural laws. Therefore, the application for a patent for this invention does not belong to the technical scheme stipulated in the second paragraph of Article 2 of the Patent Law, and does not belong to the object of patent protection.
[Example 6]
An analysis method of economic prosperity index based on electricity consumption characteristics
Overview of application content
The invention patent application evaluates the economic prosperity index of the area to be tested by counting various economic indicators and electricity consumption indicators.
Claim of application
An economic prosperity index analysis method based on regional electricity consumption characteristics is characterized by comprising the following steps:
According to the economic data and electricity consumption data of the area to be detected, selecting a preliminary index of the economic prosperity index of the area to be detected, wherein the preliminary index comprises an economic index and an electricity consumption index;
Determining an economic prosperity index system of the area to be detected by executing a cluster analysis method and a time difference correlation analysis method by a computer, including a leading index, a consistent index and a lagging index;
According to the economic prosperity index system of the area to be detected, the economic prosperity index of the area to be detected is obtained by adopting a composite index calculation method.
Analysis and conclusion
The solution is an analysis and calculation method of economic prosperity index, which is executed by a computer, and its processing objects are various economic indicators and electricity consumption indicators. The problem to be solved is to judge the economic trend, which does not constitute a technical problem. The adopted means are to analyze the economic situation according to economic data and electricity consumption data, and only to adopt economic management means according to economic laws, which is not bound by natural laws, so technical means are not used. The scheme can finally obtain the economic prosperity index used to evaluate the economy, which is not in line with the technical effect of natural laws, so the solution does not belong to the technical scheme stipulated in the second paragraph of Article 2 of the Patent Law and does not belong to the object of patent protection.
(4) When conducting creative review, the contribution of algorithm features or business rules and method features that are functionally mutually supportive and interactive with technical features to technical solutions should be considered.
[Example 7]
Method for detect falling state of humanoid robot base on multi-sensor information
Overview of application content
At present, the judgment of the falling state of humanoid robot when walking mainly uses attitude information or ZMP point position information, but this judgment is not comprehensive. The invention patent application puts forward a method for detecting the falling state of humanoid robot based on multi-sensors. By fusing the gait stage information, attitude information and ZMP point position information of the robot in real time, and using the fuzzy decision system, the current stability and controllability of the robot are judged, which provides reference for the next action of the robot.
Claim of application
The invention disclose a method for detecting that fall state of a humanoid robot based on multi-sensor information, which is characterized by comprising the follow steps:
(1) By fusing attitude sensor information, zero moment point ZMP sensor information and robot walking stage information, a layered sensor information fusion model is established;
(2) The stability of the robot in the front-rear direction and the left-right direction is judged by using the front-rear fuzzy decision system and the left-right fuzzy decision system respectively. The specific steps are as follows:
① Determine the walking stage of the robot according to the contact between the supporting foot of the robot and the ground and the off-line gait planning;
② Fuzzy reasoning algorithm is used to fuzzify the position information of ZMP points;
③ Fuzzy reasoning algorithm is used to blur the pitch angle or roll angle of the robot;
(4) determine the output membership function;
⑤ Determine fuzzy inference rules according to steps ① to ④;
⑥ deblurring.
Analysis and conclusion
Reference file 1 discloses gait planning and feedback control of humanoid robot based on sensor information, and judges the stability of robot according to relevant fusion information, including evaluating the stable state of humanoid robot according to multiple sensor information, that is, reference file 1 discloses step (1) in the solution of invention patent application, and the difference between this solution and reference file 1 lies in adopting the fuzzy decision method of the specific algorithm in step (2).
Based on the application documents, it can be seen that the solution effectively improves the stability of the robot and the reliability and accuracy of the interpretation of its possible falling direction. Attitude information, ZMP point position information and walking stage information are used as input parameters, and the information for judging the stable state of humanoid robot is output through fuzzy algorithm, which provides a basis for further issuing accurate attitude adjustment instructions. Therefore, the above-mentioned algorithm features and technical features support each other functionally and have an interactive relationship. Compared with the comparison file 1, it is determined that the technical problems actually solved by the invention are: how to judge the stable state of the robot and accurately predict its possible falling direction. The above-mentioned fuzzy decision-making algorithm and its application to the judgment of the robot’s steady state have not been disclosed by other comparison documents, nor do they belong to the common sense in this field. In the prior art as a whole, there is no inspiration for technicians in this field to improve the comparison document 1 to obtain the invention to be protected, and the technical scheme of the invention to be protected is not obvious and creative compared with the nearest prior art..
[Example 8]
Multi-robot path planning system based on cooperative co-evolution and multi-population genetic algorithm
Overview of application content
The existing motion planning control structure of multi-mobile robots usually adopts centralized planning method. This method regards the multi-robot system as a complex robot with multiple degrees of freedom, and the motion planning of all robots is completed by one planner in the system. Its disadvantages are long calculation time and poor practicability. The invention patent application provides a multi-robot path planning system based on cooperative evolution and multi-population genetic algorithm. Each path of the robot is represented by a chromosome, and the shortest distance, smoothness and safe distance are taken as the three objectives of the design path fitness function. The optimal path is obtained by optimizing each robot’s path through Messy genetic algorithm.
Claim of application
A multi-robot path planning system based on cooperative co-evolution and multi-population genetic algorithm is characterized in that:
(1) A path of a robot is represented by a chromosome, and the chromosome is represented as a linked list of nodes, that is, [(x, y), time], (x, y, time∈R) and (x, y) represent the position coordinates of the robot, and time represents the time consumption required to move this node from the previous node, and the time of starting the node is equal to 0, and the chromosome of each robot individual is divided.
(2) The fitness function of path(j) of each Robot(i) is expressed as φ(pi, j):
||pi，j||=Distance(pi，j)+ws×smooth(pi，j)+wt×Time(pi，j)
Where ||pi, j ||| is a linear combination of distance, smoothness and time consumption, ws is a smoothing weighting factor, and wt is a time weighting factor; Distance(pi, j) represents the path length, smooth(pi, j) represents the smoothness of the path, and Time(pi, j) is the time consumption of the paths pi, j; Each robot adopts the fitness function, and the optimal path is obtained through the optimization of Messy genetic algorithm.
Analysis and conclusion
Comparative document 1 discloses a multi-robot path planning method based on cooperative co-evolution, in which the fitness function is adopted and the optimal path is obtained by chaotic genetic algorithm. The difference between the solution of the invention patent application and the reference document 1 is that the multi-robot path planning is realized by Messy genetic algorithm.
In this solution, Messy genetic algorithm is used to optimize the robot’s forward path. The algorithm features and technical features of this solution support each other in function and interact with each other, thus realizing the optimization of the robot’s forward path. Compared with reference document 1, it is determined that the technical problem actually solved by the invention is: how to make the robot advance in the optimal path based on a specific algorithm. The comparison file 2 has disclosed that many genetic algorithms including the chaotic genetic algorithm can be used for path optimization, and the Messy genetic algorithm can solve the disadvantages of other algorithms, so as to obtain more reasonable optimization results. Based on the enlightenment given by reference file 2, the technicians in this field have the motivation to combine reference file 1 and reference file 2 to get the technical scheme of the invention patent application. Therefore, the claimed invention technical scheme is obvious and not creative compared with the combination of reference file 1 and reference file 2.
[Example 9]
Logistics distribution method
Overview of application content
In the process of goods distribution, how to effectively improve the efficiency of goods distribution and reduce the distribution cost is the problem to be solved in the application for invention patent. After the logistics personnel arrive at the delivery place, they can simultaneously notify multiple ordering users in a specific delivery area to pick up the goods by pushing messages to the ordering users’ terminals through the server, so as to improve the efficiency of goods delivery and reduce the delivery cost.
Claim of application
The invention relates to a logistics distribution method, which improves the efficiency of logistics distribution by notifying users to pick up pieces in batches, and the method comprises the following steps:
When the dispatcher needs to inform the user to pick up the parts, the dispatcher sends the notice that the goods have arrived to the server through the handheld logistics terminal;
The server informs the dispatcher in batches of all ordering users within the delivery range;
The ordering user who has received the notice completes the pickup according to the notification information;
Wherein, that specific implementation mode of the serv for batch notification is as follows: accord to the dispatcher ID, the current position of the logistics terminal and the corresponding distribution range carry in the arrival notification sent by the logistics terminal, the server determines all the target order information within the distribution distance range centered on the current position of the logistics terminal corresponding to the dispatcher ID, and then pushes the notification information to the ordering user terminals corresponding to the ordering user accounts in all the target order information.
Analysis and conclusion
Reference Document 1 discloses a logistics distribution method, which comprises the following steps: the logistics terminal scans the bar code on the distribution list and sends the scanned information to the server to inform the server that the goods have arrived; The server obtains the information of the ordering user in the scanned information and sends a notice to the ordering user; The ordering user who receives the notice completes the pickup according to the notification information.
The difference between the solution of the invention patent application and the reference file 1 is that users are notified of the order arrival in batches. In order to realize the batch notification, the data architecture and data communication mode between the server, the logistics terminal and the user terminal in the solution have been adjusted accordingly, and the picking notification rule and the specific batch notification implementation method support each other and interact with each other in function. Compared with reference document 1, it is determined that the technical problem actually solved by the invention is how to improve the efficiency of order arrival notification and then improve the efficiency of goods distribution. From the user’s point of view, users can get the information of order arrival more quickly, and also improve the user experience. Because the prior art does not have the technical enlightenment of improving the above-mentioned reference document 1 to obtain the solution of the invention patent application, the solution is creative.
[Example 10]
A Visualization Method of Dynamic Viewpoint Evolution
Overview of application content
In recent years, people have expressed their opinions and ideas more and more through social platforms. The emotional content published on social platforms reflects the evolution of people’s views, and we can see the development, changes and trends of events. The invention patent application helps people to better understand the intensity change of emotions at different times and the evolution trend with time by automatically collecting the information published by people on social platforms and analyzing their emotions, and drawing emotional visualization maps by computers.
Claim of application
A visualization method for dynamic viewpoint evolution comprises the following steps:
Step 1, determining the emotional membership degree and emotional classification of information in the collected information set by a computing device, wherein the emotional membership degree of the information indicates how much the information belongs to an emotional classification;
Step 2, the emotion is classified as positive, neutral or negative, and the specific classification method is as follows: if the value r of the number of likes p divided by the number of clicks q is greater than the threshold value a, then the emotion is classified as positive; if the value r is less than the threshold value b, then the emotion is classified as negative; if the value b≤r≤a, then the emotion is classified as neutral, where a>b;
Step 3, based on the emotional classification of the information, automatically establishing the geometric layout of the emotional visualization graphics of the information set, wherein the horizontal axis represents the time when the information is generated, and the vertical axis represents the amount of information belonging to each emotional classification;
Step 4, the computing device colors the established geometric layout based on the emotional membership degree of the information, and colors the information on each emotional classification layer according to the gradual change order of the information color.
Analysis and conclusion
Comparative document 1 discloses a visual analysis method based on emotion, in which time is represented as a horizontal axis, the width of each color band at different times represents the measurement of an emotion at that time, and different colors are used to represent different emotions.
The difference between the solution of the invention patent application and the comparison file 1 lies in the specific classification rules of emotions set in step 2. It can be seen from the content of the application that even if the emotion classification rules are different, the technical means of coloring the corresponding data can be the same, and there is no need to change, that is, the above-mentioned emotion classification rules and specific visualization means are not functionally mutually supportive and have an interactive relationship. Compared with reference document 1, the application for a patent for invention only puts forward a new rule of emotion classification, which does not actually solve any technical problems or make technical contributions to the existing technology. Therefore, the claimed invention technical scheme is not creative compared with reference document 1.
6.3 Writing of Instructions and Claims
6.3.1 Writing of instructions
The description of an application for a patent for invention containing the features of algorithm or business rules and methods shall clearly and completely describe the solution adopted by the invention to solve its technical problems. On the basis of technical features, the solution can further include algorithm features or business rules and method features that are functionally mutually supportive and have an interactive relationship with the technical features.
The specification shall specify how the technical features and the algorithmic features or business rules and method features that support each other functionally and interact with each other can work together and produce beneficial effects. For example, when the algorithm features are included, the abstract algorithm should be combined with the specific technical field, and the definition of at least one input parameter and its related output results should be associated with the specific data in the technical field; When it contains the characteristics of business rules and methods, the whole process of solving technical problems should be described and explained in detail, so that technicians in the technical field can realize the solution of the invention according to the contents recorded in the specification.
The description should clearly and objectively state the beneficial effects of the invention compared with the existing technology, such as the improvement of quality, accuracy or efficiency, the improvement of the internal performance of the system, etc. If the user experience is objectively improved from the user’s point of view, it can also be explained in the manual. At this time, it should also be explained how the improvement of the user experience is brought or produced by the technical features that constitute the invention, as well as the algorithmic features or business rules and method features that support each other functionally and interact with each other.
6.3.2 Writing of Claims
The claim of an application for a patent for invention containing the features of algorithm or business rules and methods shall be based on the specification and clearly and briefly define the scope of patent protection. The claim shall record the technical features and the algorithmic features or business rules and method features that are functionally mutually supportive and have an interactive relationship with the technical features.
Other contents of this chapter have not been modified.
This decision shall come into force as of February 1, 2020.
Related links：Revision and Interpretation of Chapter 9, Part II of Patent Examination Guide in 2020
