False and counterfeit business supervision and management system and method

Abstract

The invention relates to the technical field of information, and discloses a false and counterfeit business supervision and management system and method, which realize accurate identification and quick response of false and counterfeit cases so as to improve the supervision efficiency and reduce the supervision cost. In the scheme of the invention, the system receives false and counterfeit case progress monitoring requests from different channels, the requests comprise information of a to-be-monitored false and counterfeit case, the case category is determined according to the information of the to-be-monitored false and counterfeit case, and then the sub-object and the mapping relation related to the case are determined according to the case category. The system obtains case related information from various sources, automatically analyzes and extracts the case related information, analyzes the analyzed case related information to obtain progress information of a counterfeit case, continuously monitors the case progress, judges whether the case has progress abnormality or not, and triggers an early warning mechanism if the case progress abnormality exists. The system adopts a multi-level encoding structure to encode cases and associate case information. The method is suitable for efficient supervision of fake and counterfeit businesses.

Description

Technical Field

[0001] The present invention relates to the field of information technology, and particularly to a supervision and management system and method for counterfeiting and piracy business. Background Art

[0002] With the rapid development of the global market economy and the booming rise of e-commerce, the intensity of market competition has been increasing day by day. Online sales platforms have become the preferred trading channels for many enterprises and consumers due to their convenience and wide coverage. However, this trend has also provided a breeding ground for counterfeit and shoddy products and the problem of cross-region sales, becoming one of the major challenges faced by enterprises, and causing damage to brand reputation, market share, and even the entire market order.

[0003] The existing supervision and management means for counterfeiting and piracy business mainly include channels such as telephone reporting and email reporting. These channels have obvious shortcomings in terms of information reception volume and transmission efficiency. On the one hand, due to limited reporting channels, information on a large number of counterfeiting and piracy cases cannot be captured and transmitted in a timely manner, resulting in it being difficult for the regulatory authorities to comprehensively and accurately grasp the true situation of counterfeiting cases. On the other hand, delays and distortions in the information transmission process mean that when the regulatory authorities receive the information, they often miss the best processing opportunity, increasing the difficulty of cracking down on counterfeiting and piracy behaviors.

[0004] In addition, in the existing supervision schemes, the information on counterfeiting and piracy cases is manually reviewed, with a cumbersome and time-consuming process. Coupled with limited human resources, the regulatory authorities often have a slow response speed to counterfeiting and piracy cases. Moreover, after collecting the information on counterfeiting and piracy cases, the regulatory authorities often lack effective data analysis and utilization means, and the utilization of data resources is insufficient, restricting the scientific basis for the regulatory authorities to formulate supervision strategies and also affecting the efficiency and effectiveness of the regulatory authorities in cracking down on counterfeiting and piracy behaviors. Summary of the Invention

[0005] The technical problem to be solved by the present invention is: to propose a supervision and management system and method for counterfeiting and piracy business, realizing the accurate identification and rapid response to counterfeiting and piracy cases, so as to improve the supervision efficiency and reduce the supervision cost.

[0006] The technical solution adopted by the present invention to solve the above technical problem is:

[0007] On the one hand, the present invention provides a supervision and management system for counterfeiting and piracy business, including:

[0008] An information receiving module, configured to receive progress monitoring requests for counterfeiting and piracy cases from different channels, where the progress monitoring requests include information on the counterfeiting and piracy cases to be monitored;

[0009] A case classification module, configured to determine the case category according to the information on the counterfeiting and piracy cases to be monitored;

[0010] A sub-object mapping module for determining sub-objects related to a case and mapping relationships according to the case category;

[0011] An information parsing module for obtaining case-related information from multiple sources and automatically parsing and extracting the case-related information;

[0012] A data analysis module for analyzing the parsed case-related information to obtain the progress information of counterfeit cases;

[0013] A monitoring and early warning module for continuously monitoring the progress of a case and determining whether there is an abnormal progress in the case. If there is an abnormality, an early warning mechanism is triggered;

[0014] A coding management module for coding cases using a multi-level coding structure and associating case information.

[0015] Furthermore, the system further includes:

[0016] A big data processing module for deeply mining and analyzing massive case data, discovering the laws and trends of counterfeit behaviors, and providing decision-making support for regulatory authorities.

[0017] Furthermore, the information receiving module supports requests for monitoring the progress of counterfeit cases from multiple channels, including public reports, self-inspections by enterprises, and transfers from regulatory authorities.

[0018] Furthermore, the information parsing module supports obtaining case-related information from multiple sources such as databases, file servers, and third-party platforms, and automatically parsing and extracting the case-related information using OCR, speech recognition, and image recognition technologies.

[0019] Furthermore, the case classification module performs intelligent analysis on the information of counterfeit cases to be monitored using natural language processing technology and determines the case category. For cases whose category cannot be automatically determined, a manual assistance judgment function is provided.

[0020] Furthermore, the sub-object mapping module presets a list of sub-objects related to the case according to the case category, establishes a mapping relationship table between the sub-objects and the case category, and dynamically adjusts the sub-object list and mapping relationship during the case processing.

[0021] Furthermore, the multi-level coding structure adopted by the coding management module includes four levels of coding. Among them, the first-level coding represents the case type, the second-level coding represents the case sub-type, the third-level coding represents the case status / progress, and the fourth-level coding represents the key elements of the case.

[0022] Further, the data analysis module analyzes the parsed case-related information based on sub-objects: for the investigation progress sub-object, key information in the investigation report is extracted to determine the current investigation stage of the case; for the involved product sub-object, by comparing product pictures and specification parameter information, the authenticity and counterfeiting degree of the product are judged.

[0023] Further, the monitoring and warning module judges whether there is an abnormal progress of the case based on preset progress standards or historical data. If there is an abnormality, the warning mechanism is triggered, progress abnormal information is output, and relevant personnel are notified.

[0024] On the other hand, the present invention also provides a method for supervising and managing counterfeiting and imitation business, including the following steps:

[0025] S1. Receive counterfeiting and imitation case progress monitoring requests from different channels, where the progress monitoring requests include information on the counterfeiting and imitation cases to be monitored;

[0026] S2. Determine the case category according to the information on the counterfeiting and imitation cases to be monitored;

[0027] S3. Determine the sub-objects related to the case and the mapping relationship according to the case category;

[0028] S4. Obtain case-related information from multiple sources, and automatically parse and extract the case-related information;

[0029] S5. Analyze the parsed case-related information to obtain the progress information of the counterfeiting and imitation cases;

[0030] S6. Continuously monitor the progress of the case, and judge whether there is an abnormal progress of the case. If there is an abnormality, trigger the warning mechanism;

[0031] S7. Encode the case using a multi-level coding structure and associate the case information.

[0032] The beneficial effects of the present invention are:

[0033] (1) Precise identification and rapid response:

[0034] Through technologies such as natural language processing and image recognition, the system can accurately identify counterfeiting and imitation cases, greatly reducing manual intervention and misjudgment rates. And based on automatic parsing and extraction of information, it can quickly respond to monitoring requests from different channels, improving the timeliness of case handling.

[0035] (2) Comprehensive coverage and efficient management:

[0036] The system has established a perfect mapping relationship between sub-objects and case categories, ensuring that all key information points can be accurately and comprehensively covered during the case handling process, and improving management efficiency. By integrating multiple resources, it realizes all-round and multi-level monitoring of counterfeiting cases, effectively preventing omissions and evasion of supervision.

[0037] (3) Intelligent analysis and early warning:

[0038] The system has powerful data analysis capabilities. Based on historical data and preset standards, it can conduct intelligent analysis and prediction on the progress of cases. Once abnormal progress of a case is detected, the system can immediately trigger the early warning mechanism to notify relevant personnel to take intervention measures in a timely manner, effectively avoiding the deterioration of the case.

[0039] (4) Data-driven decision support:

[0040] Through big data analysis and machine learning technologies, the system can deeply mine and analyze a large amount of case data, discover the patterns and trends of counterfeiting behaviors, provide scientific decision support for regulatory authorities, optimize resource allocation, and improve regulatory efficiency. Brief description of the drawings

[0041] Figure 1 It is the structural block diagram of the counterfeiting business supervision and management system in the present invention;

[0042] Figure 2 It is the flowchart of the counterfeiting business supervision and management method in the present invention. Detailed implementation manners

[0043] The present invention aims to provide a counterfeiting business supervision and management system and method to achieve accurate identification and rapid response to counterfeiting cases, so as to improve regulatory efficiency and reduce regulatory costs. Its core idea is: by integrating multiple resources and applying advanced information technology means, to achieve accurate identification, rapid response and effective disposal of counterfeiting cases. Through automated and intelligent information processing and analysis means, the need for manual intervention is reduced, the labor cost is lowered, and at the same time, big data analysis and machine learning technologies are used to improve regulatory efficiency and enhance the crackdown intensity.

[0044] See Figure 1 , the counterfeiting business supervision and management system provided by the present invention can adopt a modular design, and it includes the following functional modules:

[0045] Information receiving module: used to receive progress monitoring requests from different channels (such as public reports, enterprise self-checks, transfers from regulatory authorities, etc.). These monitoring requests contain detailed information of the counterfeiting cases to be monitored, such as case numbers, case types, case occurrence locations, involved amounts, etc.

[0046] Case Classification Module: It is used to perform intelligent analysis on the information of counterfeit cases to be monitored by using natural language processing technology, and determine the case category. For cases whose categories cannot be automatically determined, it provides an artificial auxiliary judgment function.

[0047] Sub-object Mapping Module: It is used to determine the sub-objects related to the case and the mapping relationships according to the case category. The sub-objects include involved products, involved persons, investigation progress, legal documents, evidence materials, etc.

[0048] Information Analysis Module: It is used to obtain the information to be monitored related to the case from multiple sources (such as databases, file servers, third-party platforms, etc.), and use technologies such as OCR, speech recognition, and image recognition to automatically analyze and extract the information, generating structured data.

[0049] Data Analysis Module: It is used to analyze the parsed information based on the sub-objects to obtain the progress information of the counterfeit case, such as the investigation stage, product authenticity, etc.

[0050] Monitoring and Early Warning Module: It is used to continuously monitor the progress of the case, and judge whether there is an abnormal progress according to the preset progress standard or historical data. Once an anomaly is detected, it immediately triggers the early warning mechanism to notify relevant personnel so as to take intervention measures in a timely manner.

[0051] Coding Management Module: It is used to encode the cases using a multi-level coding structure, associate the case information, so that the category and sub-objects can be quickly determined later, obtain and analyze the information from multiple sources according to the code, and trigger an early warning if necessary according to the case status / progress monitoring.

[0052] Big Data Processing Module: It is used to deeply mine and analyze a large amount of case data, discover the laws and trends of counterfeit behaviors, and provide decision-making support for regulatory authorities.

[0053] In the specific implementation of the counterfeit business supervision and management system in the present invention, its system architecture design is as follows:

[0054] Front-end Interface: By designing a simple, clear, and easy-to-operate user interface, it supports access from multiple devices (such as PCs, mobile phones, etc.). The interface provides functions such as case information entry, query, and statistics, and at the same time supports API interface docking to facilitate data interaction with other systems.

[0055] Back-end Service: By building a high-performance and scalable back-end service, it is responsible for receiving the case information transmitted from the front end, and performing processing such as case classification, sub-object determination, information acquisition and analysis. The back-end service is also responsible for the real-time monitoring and early warning functions of the case progress.

[0056] Database: By constructing a complete database system, it is used to store data such as case information, sub-object information, progress information, etc. Database design needs to consider factors such as data integrity, consistency, and security.

[0057] Third-party interfaces: By cooperating with advanced technology providers such as OCR, speech recognition, and image recognition, integrating their API interfaces, and realizing the automatic parsing and extraction of information to be monitored. At the same time, establish data connections with databases, file servers, third-party platforms, etc. to ensure the comprehensive acquisition of information.

[0058] The implementation methods of the core functional modules are as follows:

[0059] Receive progress monitoring requests: Design a case information entry interface that supports both manual input and file upload. Write an API interface to receive case information from other systems. Conduct preliminary verification on the received case information to ensure the integrity and accuracy of the information.

[0060] Determine the categories of cases to be monitored: Preset case classification criteria, including types such as trademark counterfeiting, patent infringement, and copyright infringement. Use natural language processing technology to conduct intelligent analysis on case information and automatically judge the case category. For cases that cannot be automatically judged, provide a manual assistance judgment function.

[0061] Determine sub-objects and mapping relationships: According to the case category, preset a list of sub-objects related to the case. Establish a mapping relationship table between sub-objects and case categories to ensure that each case can be accurately associated with the corresponding sub-objects. During the case processing, dynamically adjust the sub-object list and mapping relationships according to actual needs.

[0062] Obtain information to be monitored: Design an information acquisition module that supports obtaining case-related information from multiple sources such as databases, file servers, and third-party platforms. Use technologies such as OCR, speech recognition, and image recognition to conduct automatic parsing and extraction of the obtained information. Store the parsed information in the database to generate structured data.

[0063] Parse information to be monitored: Write an information parsing algorithm to conduct in-depth analysis on the obtained information based on sub-objects. For the sub-object of investigation progress, extract key information from the investigation report to determine the current investigation stage of the case. For the sub-object of involved products, judge the authenticity and counterfeiting degree of the products by comparing information such as product pictures and specification parameters.

[0064] Continuous monitoring and early warning: Design a progress monitoring module to monitor the progress of cases in real time. According to the preset progress standards or historical data, judge whether there are progress anomalies in the cases. Once an anomaly is detected, immediately trigger the early warning mechanism, output progress anomaly information, and notify relevant personnel through methods such as text messages, emails, and APP push.

[0065] In addition, the system can also introduce a big data processing module, which uses technologies such as data mining and machine learning to deeply mine and analyze massive case data, discover the patterns and trends of counterfeiting and imitation behaviors, and provide decision-making support for regulatory authorities. For example, by introducing deep learning network structures (such as convolutional neural network CNN, recurrent neural network RNN and its variants LSTM, GRU, etc.) and training with a large amount of labeled data, a more refined classification of case types can be achieved, improving the accuracy and robustness of classification.

[0066] After the system design is completed, it is also necessary to test the system in terms of function, performance, and security respectively.

[0067] Function testing: Conduct detailed tests on each functional module of the system to ensure the correctness and integrity of the functions.

[0068] Performance testing: Test performance metrics such as the response time and throughput of the system to ensure that the system can operate stably under high concurrency.

[0069] Security testing: Test the security of the system, including aspects such as data encryption and permission control, to ensure the security of the system.

[0070] In addition, a perfect user feedback mechanism can also be established in the system to encourage users to put forward opinions and suggestions. The system developers regularly collect and analyze user feedback, continuously optimize the system functions and service quality, and ensure that the system always meets user needs and market changes. Adopt an agile development model to quickly respond to user needs and market changes, and regularly release system updates and upgrades. Encourage users to participate in the planning and design of system functions, and continuously improve the practicality and user experience of the system through the way of user co-creation.

[0071] Based on the above counterfeiting and imitation business supervision and management system, for the counterfeiting and imitation business supervision and management method process implemented by the present invention, see Figure 2 and it includes the following steps:

[0072] S1. Receive counterfeiting and imitation case progress monitoring requests from different channels, and the progress monitoring requests contain information on the counterfeiting and imitation cases to be monitored;

[0073] S2. Determine the case category according to the information on the counterfeiting and imitation cases to be monitored;

[0074] S3. Determine the sub-objects and mapping relationships related to the case according to the case category;

[0075] S4. Obtain case-related information from multiple sources, and automatically parse and extract the case-related information;

[0076] S5. Analyze the parsed case-related information to obtain the progress information of the counterfeiting case;

[0077] S6. Continuously monitor the case progress and determine whether there is any abnormal progress. If there is an abnormality, trigger the early warning mechanism;

[0078] S7. Encode the case using a multi-level coding structure and associate the case information.

[0079] It should be noted that since the above steps in the management method are all implemented by the corresponding functional modules in the management system, and the specific implementation means of each functional module have been detailed in the previous part, the specific implementation of each step in the management method will not be elaborated here.

[0080] Embodiment

[0081] In this example, taking a well-known liquor company A discovering that there are a large number of counterfeit products of a certain high-end liquor under its brand in the market, and these counterfeit products infringe on the trademark rights of liquor company A as an example, the implementation process is specifically described as follows:

[0082] Liquor company A submitted a progress monitoring request through the system's user interface or API interface.

[0083] The request contains detailed case information, including case number (such as JJ20230501001), case type (trademark counterfeiting), place where the case occurred (multiple places across the country), involved amount (estimated to be tens of millions of RMB), etc.

[0084] The system automatically received and analyzed the case information in the request. Using natural language processing technology, the system quickly determined that the specific category of the case is "trademark counterfeiting - counterfeiting high-end liquor".

[0085] Based on the case category, the system determined the sub-objects related to the case, including involved products (high-end liquor), involved persons (counterfeiters, sellers), investigation progress, legal documents, evidence materials, etc.

[0086] The system established the mapping relationship between the sub-objects and the case category, such as involved product (P) - high-end liquor, involved person (S) - counterfeiter / seller, etc.

[0087] The system obtained the information to be monitored related to the case from various sources such as the database of liquor company A, third-party e-commerce platforms, and social media.

[0088] This information includes pictures of counterfeit products, sales records, consumer complaints, etc.

[0089] The system used technologies such as OCR and image recognition to automatically parse and extract this information, generating structured data.

[0090] The system further analyzed the acquired structured data. By comparing the pictures and specification parameters of the counterfeit products, the system judged the authenticity and degree of counterfeiting of the products. Meanwhile, the system also analyzed the investigation progress and determined the current investigation stage of the case (such as some counterfeiting locations have been locked and the sales channels of counterfeit products are being tracked, etc.).

[0091] The system continuously monitors the progress of the case and judges whether there is an abnormal progress according to the preset progress standards (such as investigation time limit, processing flow specifications, etc.). Suppose the system detects that the investigation progress is seriously lagging behind, and immediately triggers the early warning mechanism. The system notifies the relevant persons in charge of Enterprise A of liquor and law enforcement officers by means of text messages, emails, etc., reminding them to take intervention measures in a timely manner.

[0092] The system encodes the case by using a multi-level coding structure and associates the case information. For example, a four-level coding structure is adopted. Among them, the first-level coding represents the case type, the second-level coding represents the case subcategory, the third-level coding represents the case status / progress, and the fourth-level coding represents the key elements of the case.

[0093] According to this coding rule, the code of this case is: M-JJ-D-P001-S001-E001

[0094] M: The first-level coding indicates that the case type is trademark counterfeiting.

[0095] JJ: The second-level coding indicates that the case subcategory is counterfeiting high-end liquor.

[0096] D: The third-level coding indicates that the case status is under investigation.

[0097] P001: The fourth-level coding indicates that the product number involved in the case is the first counterfeit product of high-end liquor.

[0098] S001: The fourth-level coding indicates that the ID of the person involved in the case is the first counterfeiter locked.

[0099] E001: The fourth-level coding indicates that the evidence number is the first key evidence.

[0100] Accordingly, this embodiment realizes a more efficient and intelligent supervision means for enterprise products.

[0101] Finally, it should be noted that the above embodiments are only preferred implementation manners and do not limit the present invention. It should be pointed out that for those of ordinary skill in the art in this technical field, without departing from the spirit and scope protected by the claims of the present invention, several modifications, equivalent replacements, improvements, etc. can still be made, and all of them should be included in the protection scope of the present invention.

Claims

1. A fake and counterfeit business supervision and management system, characterized in that Comprising: An information receiving module, configured to receive requests for monitoring the progress of counterfeiting cases from different channels, where the progress monitoring requests contain information about the counterfeiting cases to be monitored; A case classification module, configured to determine the case category according to the information of the counterfeiting cases to be monitored; A sub-object mapping module, configured to determine the sub-objects related to the case and the mapping relationship according to the case category; An information parsing module, configured to obtain information related to the case from multiple sources and perform automated parsing and extraction on the information related to the case; A data analysis module, configured to analyze the information related to the case after parsing to obtain the progress information of the counterfeiting case; A monitoring and early warning module, configured to continuously monitor the progress of the case and determine whether there is an abnormal progress in the case. If there is an abnormality, an early warning mechanism is triggered; A coding management module, configured to code the case using a multi-level coding structure and associate the case information.

2. The counterfeiting business supervision and management system according to claim 1, characterized in that The system further comprises: A big data processing module, configured to deeply mine and analyze a large amount of case data, discover the laws and trends of counterfeiting behaviors, and provide decision-making support for the regulatory authorities.

3. The counterfeiting business supervision and management system according to claim 1, characterized in that The information receiving module supports requests for monitoring the progress of counterfeiting cases from multiple channels such as public reports, enterprise self-inspections, and transfers by regulatory authorities.

4. The counterfeiting business supervision and management system according to claim 1, characterized in that The information parsing module supports obtaining information related to the case from multiple sources such as databases, file servers, and third-party platforms, and uses technologies such as OCR, speech recognition, and image recognition to perform automated parsing and extraction on the information related to the case.

5. The counterfeiting business supervision and management system according to claim 1, characterized in that The case classification module performs intelligent analysis on the information of the counterfeiting cases to be monitored by using natural language processing technology, and determines the case category. For cases that cannot be automatically judged, a manual assistance judgment function is provided.

6. The counterfeiting business supervision and management system according to claim 1, characterized in that The sub-object mapping module presets a list of sub-objects related to the case according to the case category, establishes a mapping relationship table between the sub-objects and the case category, and dynamically adjusts the sub-object list and the mapping relationship during the case processing.

7. The counterfeiting business supervision and management system according to claim 1, characterized in that The multi-level coding structure adopted by the coding management module includes four levels of coding. Among them, the first-level coding represents the case type, the second-level coding represents the case sub-type, the third-level coding represents the case status / progress, and the fourth-level coding represents the key elements of the case.

8. The counterfeiting business supervision and management system according to claim 1, characterized in that The data analysis module analyzes the information related to the case after parsing based on the sub-objects: for the sub-object of the investigation progress, extracts the key information in the investigation report to determine the current investigation stage of the case; for the sub-object of the involved products, judges the authenticity and counterfeiting degree of the products by comparing the product pictures and specification parameter information.

9. A supervision and management system for counterfeiting business as claimed in claim 1, wherein the monitoring and early warning module determines whether there is an abnormal progress of a case based on a preset progress standard or historical data. If there is an abnormality, it triggers an early warning mechanism, outputs progress abnormality information, and notifies relevant personnel.

10. A method for supervising and managing counterfeiting and imitating businesses, characterized in that, It includes the following steps: S1. Receive requests for monitoring the progress of counterfeiting cases from different channels, where the progress monitoring requests contain information about the counterfeiting cases to be monitored; S2. Determine the case category according to the information of the counterfeiting case to be monitored; S3. Determine the sub-objects related to the case and the mapping relationship according to the case category; S4. Obtain information related to the case from multiple sources, and automatically analyze and extract the information related to the case; S5. Analyze the parsed information related to the case to obtain the progress information of the counterfeiting case; S6. Continuously monitor the progress of the case and determine whether there is an abnormal progress of the case. If there is an abnormality, trigger an early warning mechanism; S7. Encode the case using a multi-level coding structure and associate the case information.

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