In order to implement the decisions and deployment of the CPC Central Committee and the State Council on strengthening the protection of intellectual property, and to respond to the needs of innovative entities to further clarify the examination rules of patent application involving new forms of business and new fields such as artificial intelligence, the decision to amend the Guidelines for Patent Examination is hereby issued, effective from February 1, 2020.

 

Hereby Noticed.

China National Intellectual Property Administration

December 31, 2019

 

 

The Decision of the China National Intellectual Property Administration on Amending theGuidelines for Patent Examination

 

The China National Intellectual Property Administration decided to make amendments to theGuidelines for Patent Examination:

 

Section 6 is added to Chapter 9 of Part II of the Guidelines for Patent Examination, the content is as follows:

 

6. ​​Provisions on the examination of invention patent applications that contain algorithmic features or business rules and methodological features

Invention patent applications involving artificial intelligence, Internet plus, big data, and blockchain generally include rules and methodological features of intellectual activities such as algorithms or business rules and methods. This section is intended to make provisions for the specificity of the examination of such applications based on the Patent Law and its detailed implementing regulations. 

 

6.1 Examination criteria

The examination shall be conducted on the solution to be protected, that is, the solution defined by the claims. In the examination, all the content recorded in the claims should be taken as a whole, rather than simply separate the technical features from algorithm features or business rules and methodological features. The technical means involved, the technical problems solved, and the technical effects obtained should be analyzed. 

 

6.1.1 Examination in accordance with the Article 25, Paragraph 1, Item (2) of the Patent Law

If a claim involves abstract algorithms or pure business rules and methods without any technical features, it belongs to the rules and regulations of intellectual activity stipulated in Article 25, Paragraph 1, Item (2) of the Patent Law. The claim should not be granted a patent. For example, a method for mathematical model based on an abstract algorithm without any technical features belongs to the condition that should not be granted a patent as stipulated in Article 25, Paragraph 1, Item (2) of the Patent Law. Another example is a method of rebate based on the user’s consumer spending, of which all the features are business rules and methodological features related to the rebate rules, rather technical features. It belongs to the condition that should not be granted a patent as stipulated in Article 25, Paragraph 1, Item (2) of the Patent Law.

 

If a claim contains technical features in addition to algorithmic features or business rules and methodological features and is not a rule and method of intellectual activity as a whole, it should not be excluded from the possibility of obtaining patent rights based on Article 25, Paragraph 1, Item (2) of the Patent Law.

 

6.1.2 Examination in accordance with Article 2, Paragraph 2 of the Patent Law

If the claim as a whole does not belong to the condition that should be excluded from the acquisition of patent rights as stipulated in Article 25, Paragraph 1, Item (2) of the Patent Law, it is necessary to be examined to determine whether it is technical proposal described in Article 2, Paragraph 2 of the Patent Law. 

 

When examining whether a claim containing algorithmic features or business rules and methodological features belongs to a technical proposal, it is necessary to consider all the features recorded in the claim as a whole. If the claim records that the technical means using the laws of nature are used to solve the technical problems, by which the technical effects that conform to the laws of nature is obtained, the solution defined by the claim belongs to the technical proposal described in Article 2, Paragraph 2 of the Patent Law. For example, if the steps involved in the algorithm in the claims 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, the execution of the algorithm can directly reflect the process of using the laws of nature to solve a certain problem, and obtain the technical effect, then usually the solution defined by the claim belongs to the technical proposal described in Article 2, Paragraph 2 of the Patent Law.

 

6.1.3 Examination of novelty and inventiveness

When conducting an examination of novelty to an application for invention patent that contains algorithmic features or business rules and methodological features, all the features recorded in the claims shall be considered. These features include not only technical features, but also algorithmic features or business rules and methodological features.

 

When conducting an examination of inventiveness to an application for invention patent that contains not only technical features, but also algorithmic features or business rules and methodological features, the algorithm features or business rules and methodological features that functionally support and interact with each other should be considered as a whole with technical features. "Functionally support and interact with each other" means that the algorithm features or business rules and methodological features are closely combined with technical features, constitute together a technical means to solve a technical problem, and can obtain corresponding technical effects.

 

For example, if the algorithm in the claims applied to a specific technical field can solve a specific technical problem, then it can be considered that the algorithm feature and the technical feature functionally support and interact with each other. The algorithm feature becomes a component of the technical means it adopts. In examination of novelty, the contribution of the described algorithm features to the technical proposal shall be taken into consideration.

 

For another example, if the implementation of the business rules and methodological features in the claims requires adjustment or improvement of technical means, then it can be considered that the business rules and methodological features and the technical features are functionally support and interact with each other. In examination of novelty, the contribution of the described business rules and methodological features to the technical proposal shall be taken into consideration.

 

6.2 Examination Examples

According to the examination criteria mentioned above, the examples of examination of applications for invention patents that include algorithmic features or business rules, and methodological features are given as follows:

 

(1) The applications for invention patents that include algorithm features or business rules and methodological features that fall within the scope of Article 25, Paragraph 1, Item (2) of the Patent Law, are not the object of patent protection.

【Example 1】

A method for a mathematical model

 

Summary of application content

The solution of the application for invention patent is a method for a mathematical model, in which the accuracy of modeling could be improved by increasing the number of training samples. The modeling method treats the training samples of other classification tasks that related to the first classification task as the training samples of the mathematical model of the first classification task to increase the number of training samples. It also uses the feature values, extracting feature values, and label values of the training samples to train the related mathematical models, and eventually obtains the mathematical model of the first classification task which overcomes the shortcomings of poor modeling accuracy due to the overfitting of fewer training samples.

 

Application claims

A method for a mathematical model is characterized by the steps as follows: 

Train the initial feature extraction model with the feature value in the training sample of the first classification task and at least one feature value in the training sample of the second classification task to obtain the target feature extraction model. wherein, the second classification task is the other classification tasks related to the first classification task as described.

 

Process the feature values ​​in each training sample of the first classification task with the target feature extraction model to obtain the extracted feature value corresponding to each training sample;

 

Compose the extracted training samples from the extracted feature values ​​and label values ​​corresponding to each training sample, and train the initial classification model, to obtain the target classification model. 

 

Compose the described mathematical model of the first classification task from the target classification model and the target feature extraction model as described.  

 

Analysis and Conclusion

The solution does not involve any specific application areas. The feature values ​​of training samples, the extracted feature values, the label values, the target classification models, and the target feature extraction models processed are all abstract general data. The process of model training with relevant data of training samples and other processing is a series of abstract steps of mathematical method, and the result is also an abstract general classification mathematical model. This solution is an abstract model building method, of which the processing objects, proceeding and results do not involve the combination with specific application fields. The solution is an optimization of abstract mathematical methods, without any technical features. The solution of the application for invention patent belongs to the rules and methods of intellectual activities stipulated in Item (1), Article 25, Paragraph 1 of the Patent Law, and is not the object of patent protection.

 

(2) The application for invention patent containing algorithm features or business rules and methodological features that use technical means to solve technical problems and obtain technical effects belongs to the technical proposal stipulated in Article 2, Paragraph 2 of the Patent Law. Therefore, it is the object of patent protection. 

【Example 2】

A training method of convolutional neural network model

 

Summary of application content

The solution of the application for invention patent is to perform the convolution operation and the maximum pooling operation on the training images at all levels of convolutional layers. After that, further horizontal pooling operation is performed on the obtained feature images from the maximum pooling operation to make the well-trained CNN model recognize images to be recognized of any size when recognizing image categories.

 

Application claims

A training method for a convolutional neural network CNN model is characterized by the methods as described:  

 

Obtain the initial model parameters of the CNN model to be trained. The initial model parameters include the initial convolution kernel of each level of convolutional layer, the initial bias matrix of each level of convolutional layer, the initial weight matrix of the fully connected layer, and the initial bias vector of the fully connected layer.

 

Obtain multiple training images.

 

On the convolutional layers of each level, perform the convolution operation and the maximum pooling operation on each training image with the initial convolution kernel and the initial bias matrix on the convolutional layers of each level to obtain the first feature image of each training image on the convolutional layer at all levels.

 

Perform a horizontal pooling operation on the first feature image of each training image on at least the first level of convolutional layer to obtain a second feature image of each training image on each level of convolutional layer.

 

Determine the feature vector of each training image according to the second feature image of each training image on each level of convolutional layer.

 

Process each feature vector according to the initial weight matrix and the initial bias vector to obtain the category probability vector of each training image.

 

Calculate the category error according to the category probability vector of each training image as described and the initial category of each training image.

 

Adjust the model parameters of the CNN model to be trained based on the category error. 

Make the adjusted model parameters and multiple training images as described continue the process of adjusting model parameter until the number of iterations reaches the preset.

 

Treat the model parameters that are obtained when the number of iterations reaches the preset as the model parameters of the trained CNN model.

 

Analysis and Conclusion

The solution is a training method for a convolutional neural network CNN model, which clarifies that the data processed in each step of the model training method is image data and how to process image data in each step, reflecting that the neural network training algorithm is closely related to the image information processing. This solution solves the problem that the CNN model can only recognize images with a fixed size. It uses the method of processing and training images differently on different convolutional layers and adapts technical means that follow the laws of nature to obtain the technical effect that the trained CNN model can recognize images to be recognized of any size. Therefore, the solution of the application for invention patent belongs to the technical proposal stipulated in Article 2, Paragraph 2 of the Patent Law, and is the object of patent protection

【Example 3】

A method to use shared bicycles

 

Summary of application content

The application for invention patent proposes a method of using shared bicycles, in which the user can accurately find the shared bicycles that can be ridden based on the status information of the shared bicycles due to the acquisition of the location information of the user's terminal equipment and the status information of the shared bicycles within a certain distance. The user is guided to park by prompts, too. This method facilitates the use and management of shared bicycles, saves users' time, and improves user’ experience.

 

Application claims

A method for the use of shared bicycles is characterized by the following steps:

Step 1 The user sends a request for the use of shared bicycles to the server through a terminal device.

 

Step 2 The server searches for the second location information of shared bicycles within a certain distance to the user’s first location information based on the first location information it obtained. Meanwhile, the server obtains the status information of these shared bicycles, and send it, as well as the second location information to the terminal devices. The first location information and the second location information are obtained through GPS signals.

 

Step3 The user finds a target shared bicycle that can be ridden according to the location information displayed on the terminal device.

 

Step 4 The user scans the QR code on the body of the target shared bicycle through the terminal device and obtains the permission to use the target shared bicycle after being authenticated by the server.

 

Step 5 The server pushes the parking reminder to the user according to the riding situation. If the user parks the car in the designated area, the preferential tariff will be used for billing, otherwise the standard tariff will be used for billing.

 

Step 6 The user makes a choice according to the prompts. When the ride is over, the user performs the lock operation of the shared bicycle, and the shared bicycle will send a completion signal to the server after it detects the state of locking. 

Analysis and Conclusion

The solution involves a method of using shared bicycles to solve the technical problem of how to accurately find the location of shared bicycles that can be ridden and start the shared bicycle. The solution succeeds in controlling and guiding the behaviors of users using shared bicycle through executing the computer programs in terminal devices and servers. That reflects the control of collecting and calculating location information and the data of authentication, uses the technical means that follow the laws of nature, and achieve the technical effect to accurately find the location of shared bicycles that can be ridden and turn on shared bicycles. Therefore, the solution of the application for invention patent belongs to the technical proposal stipulated in Article 2, Paragraph 2 of the Patent Law, and is the object of patent protection.

 

【Example 4】

Method and device for communication between blockchain nodes

 

Summary of application content

The application for invention patent proposes a method and device for communication between blockchain nodes. Before establishing a communication connection among business nodes in blockchain, it can determine whether to establish a communication connection according to the CA certificate carried in the communication request and the pre-configured CA trust list. Thereby reducing the possibility of leaking private data from business nodes and improving the security of the data stored in the blockchain.

 

Application claims

A method for communication between blockchain nodes. The blockchain nodes in a block-chain network include business nodes, in which the certificate sent by the certificate authority CA is stored and a pre-configured with a CA trust list is pre-configured. The described method includes: 

The first blockchain node receives the communication request sent by the second blockchain node, wherein the communication request carries the second certificate of the second blockchain node.

 

Determine the CA identity corresponding to the second certificate. 

 

Judge and determine whether the CA identity corresponding to the second certificate exists in the CA trust list. 

 

If yes, establish a communication connection with the second blockchain node. 

 

If not, then not establish a communication connection with the second blockchain node.

 

Analysis and Conclusion

The problem to be solved in this application is how to prevent blockchain business nodes from leaking user private data in the consortium chain network, which is a technical problem to improve the security of blockchain data. Through the method of determining whether to establish a connection with the CA certificate carried in the communication request and the CA trust pre-configured, the objects that business nodes can connect to are limited. It uses technical means that follow the laws of nature to obtain the technical effects of securing communication between business nodes and reducing the possibility leaking private data from business nodes. Therefore, the solution of the application for invention patent belongs to the technical proposal stipulated in Article 2, Paragraph 2 of the Patent Law, and is the object of patent protection. 

 

(3) The applications for invention patents containing algorithmic features or business rules and methodological features that don’t solve technical problems, don’t use technical means, or don’t obtain technical effects, do not belong to the technical proposals spiculated in Article 2, paragraph 2 of the Patent Law. Therefore, it is not the object of patent protection.

【Example 5】

A method of consumption rebate

 

Summary of application content

The applications for invention patents propose a method of consumption rebate. User's willingness to consume is increased by the cash coupons given in accordance with the rebate rules executed by computer. Thereby the merchants can get more profits. 

 

Application claims

A method of consumption rebate is characterized by the following steps:

When a user makes a purchase at a merchant, the merchant returns a certain cash coupon according to the amount of consumption, specifically.

 

The merchant uses the computer to calculate the user's consumption amount, dividing the user's consumption amount R into M intervals, where M is an integer, and the value from interval 1 to interval M is from small to large. The amount F of the returned cash coupon is also divided into For M intervals, in which values ​​are also arranged from small to large.

 

According to the calculated value of the computer, the rebate amount is the first value when the user's current consumption amount is judged in interval 1. when the user's current consumption amount is judged in interval 2, the rebate amount is the second value. By the analogy, returning the amount of rebate in corresponding interval to the users.

 

Analysis and conclusion

The solution involves a method of consumption rebate which is executed by a computer. Its processing object is the user's consumption data and the problem to be solved is how to promote the user's consumption, which does not constitute a technical problem. The method it uses is making the computer execute the rebate rules set artificially, and according to the specified rules, the computer is limited to determine the rebate amount based the user's consumption amount without the restriction of the laws of nature. So, it does not use technical means. The effect obtained by the solution is only to promote user consumption, rather than the technical effect that conforms to the laws of nature. Therefore, the applications for invention patents does not belong to the technical proposal stipulated in Article 2, paragraph 2 of the Patent Law, and is not the object of patent protection.

【Example 6】

An analysis method of economic prosperity index based on the characteristics of electricity consumption

 

Summary of application content

The applications for invention patents evaluates the economic prosperity index of the area to be tested through collecting various economic indicators and electricity consumption indicators.

 

Application claims

A method of analyzing economic prosperity index analysis based on the characteristics of regional electricity consumption, which is characterized by the steps as follows:  

According to the economic data and electricity consumption data of the area to be tested, select the preliminary indicators of the economic prosperity index of the area, wherein the preliminary indicators include economic indicators and electricity consumption indicators.

 

Determine the economic prosperity indicator system of the area through the cluster analysis method and time difference correlation analysis method executed by computer, including leading indicators, consistent indicators and lagging indicators.

 

Adopt the synthetic index calculation method based on the economic prosperity index system of the area to be tested to obtain the economic prosperity index of the area to be tested. 

 

Analysis and conclusion

The solution is an analysis and calculation method of the economic prosperity index executed by the computer. Its processing objects are various economic indicators and electricity consumption indicators and the problem to be solved is to judge the economic trend, which does not constitute a technical problem. The method it uses is analyzing the economic situation based on economic data and electricity consumption data. It only uses economic management means in accordance with the laws of economics and is not restricted by the laws of nature. Therefore, technical methods are not used. The economic prosperity index obtained by this solution to evaluate the economy is not the technical effect that conforms to the laws of nature. Therefore, the applications for invention patents does not belong to the technical proposal stipulated in Article 2, paragraph 2 of the Patent Law, and is not the object of patent protection.

 

(4) When carrying out the examination of inventiveness, the contribution made by the algorithm features or business rules and methodological features, which functionally support and interact with the technical features, should be considered.

【Example 7】

A method for detecting the falling state of a humanoid robot based on multi-sensor information

 

Summary of application content

The existing determination of the falling state of a humanoid robot while walking mainly uses the posture information or the ZMP point position information, which is incomplete. The application for invention patent proposes a method for detecting the falling state of a humanoid robot based on multi-sensor. Through real-time fusion of robot gait stage information, posture information, and ZMP point position information, a reference for the next action of the robot can be provided. In this process, a fuzzy decision system is also needed to determine the current stability and controllability of the robot. 

 

Application claims

A method for detecting the fall state of a humanoid robot based on multi-sensor information is characterized by the steps as included: 

(1) Establish a sensor information fusion model with hierarchical structure by fusing posture sensor information, zero-moment point ZMP sensor information and robot walking stage information. 

 

(2) Determine the stability of the robot in the front and rear directions, as well as the left and right directions by using respectively the front and back fuzzy decision-making system and the left-right fuzzy decision-making system. The specific steps are as follows:

①Determine the walking stage of the robot according to the contact between the supporting feet of the robot and the ground and the offline gait planning.

 

②Using fuzzy inference algorithm to process the position information of ZMP points fuzzily;

 

③Using fuzzy inference algorithm to process the pitch angle or roll angle of the robot fuzzily;

 

④ Determine the output membership function.

 

⑤ Determine the rules of fuzzy reasoning according to steps ①～step④

 

⑥ Defuzzification.

 

Analysis and conclusion

Reference 1 discloses the gait planning and sensor information-based feedback control of the humanoid robot and judges the stability of the robot based on the relevant fusion information, which includes the evaluation of the stable state of the humanoid robot based on multiple sensor information. That means, the reference 1 discloses the step (1) in the solution of the application for invention patent. The difference between this solution and the reference 1 is using the fuzzy decision method of specific algorithm in step (2).

 

Based on the application documents, it is known that this solution effectively improves the stability of robot and the reliability and accuracy of the interpretation of its possible fall direction. Using the posture information, ZMP point position information, and walking stage information as input parameters, as well as the fuzzy algorithm outputs information which can determine the stable state of the humanoid robot, to provide a basis for further issuing accurate posture adjustment instructions. Therefore, the above algorithm features and technical features support functionally support and interact with each other. Compared to reference 1, the technical problem actually solved by the invention is how to judge the stable state of the robot and accurately predict its possible fall direction. The algorithm of the fuzzy decision mentioned above, and the judgement applied to the stable state of the robot have not been disclosed in other comparison documents, nor are they common knowledge in the field. The existing technology as a whole does not make the technicians in this field improve the comparison document 1 to obtain the enlightenment of the invention to be protected. The claimed technical proposal of the invention is non-obvious compared with the closest prior art and possesses creativity.

 

【Example 8】

A Multi-robot path planning system based on cooperative co-evolution and multi-group genetic algorithm

 

Summary of application content

The existing multi-mobile robot motion planning control structure usually uses a centralized planning method, which treats the multi-robot system as a complex robot with multiple degrees of freedom and completes the motion planning for all robots in a unified manner by a planner in the system. The disadvantage of structure is that the calculation time is long, and the practicability is not good. The application for invention patent provides a multi-robot path planning system based on collaborative evolution and multi-group genetic algorithm. Each path of the robot is represented by a chromosome, and the shortest distance, smoothness, and safety distance are taken as the three goals of the design path fitness function. The optimal path is obtained by optimizing the path of each robot through the Messy genetic algorithm.

 

Application claims

A multi-robot path planning system based on cooperative co-evolution and multi-group genetic algorithm is characterized by:

(1) A path of a robot is represented by a chromosome, and the chromosome is represented as a linked list of nodes, namely [(x, y), time], (x, y, time ∈ R), (x, y) represents the robot’s Position coordinates, time represents the time required to move this node from the previous node. The time of the initial node is equal to 0. The initial position of the initial node and the target position of the end node of the chromosome of each individual robot is fixed, while the number of intermediate nodes and nodes are alterable. 

 

(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)

 

Wherein ||pi, j|| is a linear combination of distance, smoothness and time consumption, ws is a smoothing weighting factor, wt is a time weighting factor; Distance (pi, j) represents the path length, and smooth (pi, j) represents the smoothness of the path, Time (pi, j) is the time consumption of path pi, j. Each robot uses the fitness function to obtain the optimal path through Messy genetic algorithm optimization.

 

Reference 1 discloses a multi-robot path planning method based on cooperative co-evolution, in which a fitness function is adopted to obtain an optimal path through a chaotic genetic algorithm. The difference between the solution of the application for invention patent and the reference 1 is that the multi-robot path planning is realized through the Messy genetic algorithm.

 

In this solution, the Messy genetic algorithm is used to optimize the robot's forward path. The algorithm features of this solution functionally support and interact with technical features, realizing the optimization of the robot's forward path. Compared with the reference 1, the technical problem actually solved by the invention is how to make the robot advance on the optimal path based on a specific algorithm. Reference 2 has disclosed that a variety of genetic algorithms, including the chaotic genetic algorithm, can be used for path optimization. At the same time, the Messy genetic algorithm can solve the drawbacks of other algorithms and obtain more reasonable optimization results. Based on the enlightenment given by the reference 2, the technician in the field have the motivation to combine the reference 1 and the reference 2 to obtain the technical proposal of the application for invention patent. Therefore, the technical solution of the claimed invention that combines with reference 1 and the reference 2 of is obvious and does not have creativity.

 

【Example 9】

A logistics distribution method

 

Summary of application content

How to effectively improve the efficiency of goods distribution and reduce the cost of distribution in the process of goods distribution is the problem to be solved in the application for invention patent. After the logistics personnel arrive at the delivery location, they can simultaneously notify multiple ordering users in a specific delivery area to pick up the goods in the form of pushing messages to the ordering user terminal through the server. That improves the efficiency of goods delivery and reduce the cost of delivery.

 

Application claims

A logistics distribution method that improves the efficiency of logistics distribution by notifying users in batches to pick up items. The method includes:

 

When the dispatcher needs to notify the users to pick up items, the dispatcher sends a notification through the handheld logistics terminal that the items have arrived.

 

The server informs all users that order items within the dispatch range.

 

The users who received the notification completes the pickup according to the notification information.

 

Wherein, the specific implementation of batch notification by the server is that, according to the dispatcher ID corresponding carried in the arrival notification sent by the logistics terminal, the current location of the logistics terminal, and the corresponding delivery range, the server determines the target order information within the delivery distance that corresponds to the dispatcher ID and centers in the current location of the logistics terminal. Then the notification information is pushed to the terminals of users corresponding to the ordering user account in all the target order information.

 

Analysis and conclusion

Reference 1 discloses a logistics distribution method, in which the logistics terminal scans the barcode on the distribution list and sends the scanned information to the server to notify the server that the goods have arrived. The server obtains the ordering user information in the scanned information and sends a notification to ordering users. Users that receive the notification will complete the pickup according to the notification information.

 

The difference between the solution of the application for invention patent and the reference 1 is that it notifies users of the arrival of orders in batches. To realize the batch notification, the data structure and data communication methods among the server, logistics terminal and user terminal in the solution have been adjusted accordingly. The rules of pick-up notification and the implementation methods of specific batch notification functionally support and interact with each other. Compared with Reference 1, the technical problem actually solved by the invention is how to improve the efficiency of the notification of order arrival and thus the efficiency of goods distribution. From the user's point of view, they can get information of the arrival of orders more quickly, which also improves user’s experience. Since there is no technical enlightenment in the prior art to improve the reference 1 mentioned above to obtain the solution of the application for invention patent, the solution is creative.

 

【Example 10】

A visual method of dynamic evolution of the viewpoint 

 

Summary of application content

In recent years, people have increasingly expressed their opinions and thoughts on social platforms. The emotional content that people publish on social platforms reflects the evolution of people's opinions, from which the development, changes and trends of events can also be seen. The application for invention patent automatically collects the information published by people on social platforms and analyzes the emotions in it and uses computers to draw emotion visualization graphs to help people better understand the intensity changes of emotions at different times and the trend that evolves over time.

 

Application claims

A visual method of dynamic evolution of the viewpoint, which includes:

Step1 Determines the emotional membership and emotional classification of the information collected in the information set by computing device. The emotional membership of the information indicates how likely the information belongs to a certain emotional classification.

 

Step 2 The emotion is classified as positive, neutral, or negative. The specific classification method is: if the value r of the number of likes p divided by the number of dislikes q is lager than the threshold a, then the emotional classification is considered to be positive, if the value r is less than the threshold b, then the emotional classification is considered as negative, if the value b≤r≤a, then the emotional classification is neutral, wherein a>b.

 

Step 3 Based on the emotional classification of the information, automatically establish the geometric layout of the emotional visualization graphics of the information set, with the horizontal axis indicating the time when the information was generated, and the vertical axis indicating the amount of information belonging to each emotion classification.

 

Step 4 The computing device colorizes the established geometric layout based on the emotional membership of the information and colorizes the information on each emotional classification layer according to the gradient order of the colors of the information.

 

Analysis and conclusion

Reference 1 discloses an emotion-based visualization analysis method, in which time is represented as a horizontal axis. The width of each color band at different times represents a measure of emotion at that time, and different color bands represent different emotion.

 

The difference between the solution of the application for invention patent and the reference 1 is the specific classification rules of emotions set in step 2. It can be seen from the content of the application that even if the rules of emotion classification are different, the technical means for coloring the corresponding data can be the same without any changes. That is, the emotional classification rules mentioned above, and the specific visualization means are not functionally supportive and interactive. Compared with Reference 1, the application for invention patent only proposes a new emotional classification rule, without actually solving any technical problems or making any technical contribution to the existing technology. Therefore, the technical solution of the claimed invention is not creative compared to the reference 1.

 

6.3 The writing of the specification and claims

6.3.1 The writing of the specification

The specification of an application for invention patent containing algorithmic features or business rules and methodological features should clearly and completely describe the solution adopted by the invention to solve its technical problems. Based on the including of technical features, the solution may further include algorithmic features or business rules and methodological features that functionally support and interact with the technical features.

 

The specification should state how the technical features and the algorithm features or business rules, and methodological features that functionally support and interact with each other work together and produce beneficial effects. For example, when algorithm features are included, it should be combined with specific technical fields. At least one input parameter and the definition of its related output results should be associated with specific data in the technical field; when business rules and methodological characteristics are included, it should be described and explained in detail the entire process of solving the technical problem. So that the technician in the field can implement the solution of the invention according to the content recorded in the specification.

 

The specification should clearly and objectively state the beneficial effects of the invention compared with the prior art, such as the improvement of quality, accuracy or efficiency, and the improvement of the internal performance of the system, etc. From the user’s point of view if the user’ experience is objectively improved, it can also be explained in the specification. At this time, it should also be explained how the improvement of the user’ experience is brought or produced by the technical features that compose the invention and algorithm features or business rules and methodological features that functionally support and interact with technical features. 

 

6.3.2 The writing of the claims

The claims of an application for invention patent containing algorithmic features or business rules and methodological features should be based on the specification, clearly and concisely limiting the scope of patent protection. The claims shall record the technical features and the algorithm features or business rules, and methodological features that functionally support and interact with the technical features.

 

The rest of the section is not modified. 

This decision shall take effect on February 1, 2020.