Smart label calculation method and system based on multiple rule configuration models
Through intelligent tag calculation methods and systems based on multiple rules configuration models, the problems of poor labeling flexibility and difficulty in adapting to variable business scenarios in the prior art are solved, and efficient and flexible tag generation and application are achieved.
Patent Information
- Application Number
- CN202510089922.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-01-21
- Publication Date
- 2025-05-23
AI Technical Summary
The prior art has problems such as poor flexibility, single rules and difficulty in adapting to variable business scenarios in terms of entity object labeling.
It provides a smart tag calculation method and system based on multiple rule configuration models. It supports multiple rule configuration and flexible application through tag object modeling, tag association model maintenance, tag rule maintenance, tag system establishment and tag application.
It enhances the flexibility and efficiency of labeling of entity objects, can adapt to changing business needs, and achieve efficient data processing and label generation.
Smart Images
Figure CN120030062A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of data processing technology, and in particular to a smart label calculation method and system based on multiple rule configuration models. Background Art
[0002] In today's data-driven era, the labeling of physical objects is essential for information management, tracking and analysis. Existing solutions usually face challenges such as poor flexibility, single rules and difficulty in adapting to changing business scenarios. Therefore, there is an urgent need for a solution that can support multiple rule configurations and can efficiently and intelligently apply labels. Summary of the invention
[0003] The technical task of the present invention is to address the above shortcomings and provide a smart label calculation method and system based on multiple rule configuration models, which can enhance the flexibility and efficiency of entity object labeling and adapt to changing business needs.
[0004] The technical solution adopted by the present invention to solve its technical problem is:
[0005] A smart label calculation method based on multiple rule configuration models, including label object modeling, label association model maintenance, label rule maintenance, label system establishment and label application;
[0006] Provides a user interface that allows users to maintain entity objects, entity object dimensions, and associated models, as well as associated fields, dimensions, time, indicators, and other information of associated models; the maintained information is transmitted back to the backend and maintained in the data table;
[0007] Provides a rule configuration engine, which transmits the rules configured by the user on the front end back to the back end and stores them in the rule data table;
[0008] Provide backend services for tag calculation, generate processing SQL according to rule configuration information, call bean services according to configured service information, and complete data splicing and deduplication;
[0009] Provides a portrait display page, displays tag information in the form of graphics and tables, and allows users to perform operations such as searching and sorting on the displayed data;
[0010] Provide an application page for label application. Users of other business systems can fill out the application form and obtain label usage rights through the application process.
[0011] Provides a calling interface for label services, receives calling parameters and returns label data.
[0012] Furthermore, the specific implementation process of the method includes the following steps:
[0013] 1) Tag object definition: Tag objects are defined based on the entity objects and data models compiled by the data center. Tag object information includes object code, object name, corresponding entity object, data model, associated fields, and description information;
[0014] 2) Label object dimension maintenance: Identify the dimension fields in the entity object model to ensure that each dimension field is accurately captured and defined;
[0015] 3) Tag association model maintenance: maintain the association model of tag entities and support simultaneous management of multiple models;
[0016] 4) Label object rule configuration: supports flexible setting of single rule or multiple rule combinations for label objects; supports maintenance of service beanId for labels that cannot be measured through rule configuration, and performs personalized customization development; the rules and bean services support combination;
[0017] 5) Tag calculation: The system automatically parses the rules or bean services set by the user. During the rule parsing process, the association model is connected to the entity model through the left join operation, and the data is associated using the set association fields;
[0018] When parsing the bean service, the corresponding service is found through the beanId to obtain the entity object, and the final entity object is obtained according to the maintained tag combination method. The final entity object is deduplicated;
[0019] 6) Label portrait generation: trigger label measurement through a timer, save the measurement results, and build a label portrait;
[0020] 7) Label application: The intelligent label calculation method not only provides accurate label generation, but also achieves seamless integration with other business systems through data result synchronization and data service interface.
[0021] Furthermore, the tag association model maintenance requires that each association model maintains key association fields, as well as various dimensions and indicator fields involved, to ensure data integrity and seamless connection between models;
[0022] Related fields: Ensure that the related fields of entity objects are correctly maintained to achieve accurate association between data;
[0023] Dimension field: The field representing a certain dimension is maintained as a dimension field, and dimension settings are performed, that is, the dimension selection range;
[0024] Indicator field: The field representing the data indicator is maintained as an indicator field to facilitate data statistics;
[0025] Time Field: Define the field representing time information as a time field, and select an appropriate time format, such as YYYY, YYYY-mm-dd, YYYY-MM-DDTHH:MM:SS, etc.
[0026] Furthermore, in the label object rule configuration, users can select dimensions, time and indicators according to their needs, and multiple selections and free combinations are supported to adapt to diverse business scenarios;
[0027] After selecting a dimension, the system will automatically push the dimension range for the user to choose from, and also supports the setting of custom dimension ranges;
[0028] After selecting the time, the system will push the time statistical period, such as by day, month, or year, and then maintain a threshold. When calculating the label, the system will automatically fill in the time range according to the settings;
[0029] After selecting the indicator, the system will push the indicator statistics method, including sum (sum), average (avg), count (count), etc., and allow users to set thresholds.
[0030] Furthermore, the tag calculation is
[0031] The dimensions, time and indicators will be combined into where conditions according to the conditions set by the user. The system will perform a group by operation for the existence of indicators, count the indicator values of each entity, and filter out entity objects that meet the conditions through the set indicator threshold.
[0032] Furthermore, the label image is generated.
[0033] Through tag portraits, users can view specific entity objects and their associated tags, and support global search functions. By entering the name of the entity object, matching tags can be quickly found, providing users with an intuitive and convenient tag management and query experience.
[0034] Furthermore, for the label application, each business system applies for the permission to use the label data according to its own needs, and selects one of the following two synchronization methods to integrate the label data:
[0035] Data synchronization: The business system directly applies for synchronization permissions for label data to achieve real-time or periodic data updates. This method is suitable for scenarios that require local processing and analysis of label data, ensuring that the business system can obtain the latest label information in a timely manner.
[0036] Service synchronization: The business system obtains label data on demand by calling the provided API service interface; this method is suitable for scenarios with high real-time requirements, allowing the business system to obtain label data instantly when needed, reducing the burden of data storage and processing.
[0037] To ensure data security and compliance, all applications and access to label data will follow strict data management and access control policies. When applying for label data, the business system must clearly define the purpose and scope of data use, as well as data processing and protection measures.
[0038] In addition, by providing detailed API documentation and developer support, we help business systems quickly integrate labeling services to ensure smooth technical implementation.
[0039] The present invention also claims protection for a smart label calculation system based on multiple rule configuration models, including a label object definition module, a label object dimension maintenance module, a label association model maintenance module, a label object rule configuration module, a label measurement module, a label portrait generation module and a label application module;
[0040] The system specifically implements smart tag calculation through the above method.
[0041] The present invention also claims protection for a smart tag computing device based on multiple rule configuration models, characterized in that it includes: at least one memory and at least one processor;
[0042] The at least one memory is used to store a machine-readable program;
[0043] The at least one processor is used to call the machine-readable program to implement the above method.
[0044] The present invention also claims protection for a computer-readable medium, characterized in that computer instructions are stored on the computer-readable medium, and when the computer instructions are executed by a processor, the above method can be implemented.
[0045] Compared with the prior art, the intelligent tag calculation method and system based on multiple rule configuration models of the present invention have the following beneficial effects:
[0046] (1) Enhanced adaptability and flexibility: The intelligent label calculation method based on the data center can adapt to different business scenarios and dynamically changing environments, which means that the system can flexibly generate or update labels across business areas.
[0047] (2) Efficient data processing capability: With the powerful computing power of the data center, the present invention can efficiently process large amounts of data and perform complex data screening, aggregation and other operations. This ensures that even when the amount of data is huge, it can respond quickly and generate accurate label information.
[0048] (3) Easy to expand and maintain: As the business develops, rules can be easily added or modified on the data platform to meet new requirements. This makes the system easy to expand and maintain. BRIEF DESCRIPTION OF THE DRAWINGS
[0049] Figure 1 It is a flowchart of a smart tag calculation method based on multiple rule configuration models provided by an embodiment of the present invention. DETAILED DESCRIPTION
[0050] The present invention will be further described below in conjunction with specific embodiments.
[0051] The embodiment of the present invention provides a smart label calculation method based on multiple rule configuration models, including label object modeling, label association model maintenance, label rule maintenance, label system establishment and label application.
[0052] Provides a user interface that allows users to maintain entity objects, entity object dimensions, and associated models, as well as associated fields, dimensions, time, indicators, and other information of associated models. The maintained information is transmitted back to the backend for maintenance in the data table.
[0053] Provides a rule configuration engine that transmits the rules configured by the user on the front end back to the back end and stores them in the rule data table.
[0054] Provide a backend service for label measurement, generate processing SQL according to the rule configuration information, call the bean service according to the configured service information, and complete data splicing and deduplication.
[0055] Provides a portrait display page that displays tag information in the form of graphics and tables, and allows users to perform operations such as searching and sorting on the displayed data.
[0056] Provide an application page for label application, where users of other business systems can fill out an application form and obtain label usage permissions through the application process.
[0057] Provides a calling interface for a tag service, receives calling parameters and returns tag data.
[0058] Combined with Figure 1 As shown, the specific implementation process of this method is as follows:
[0059] 1. Tag object definition:
[0060] The label object is defined based on the entity objects and data models organized by the data center. The label object information includes the object code, object name, corresponding entity object, data model, associated fields, and description information.
[0061] 2. Label object dimension maintenance:
[0062] Identify the dimension fields in the entity object model to ensure that each dimension field is accurately captured and defined.
[0063] 3. Label association model maintenance:
[0064] Maintain the association model of the tag entity and support the simultaneous management of multiple models. Each association model needs to maintain key association fields, as well as various dimensions and indicator fields involved, to ensure data integrity and seamless connection between models.
[0065] Related fields: Ensure that the related fields with entity objects are correctly maintained to achieve accurate association between data.
[0066] Dimension field: The field representing a certain dimension is maintained as a dimension field, and dimension settings are performed, that is, the dimension selection range.
[0067] Indicator field: The field representing the data indicator is maintained as an indicator field to facilitate data statistics.
[0068] Time Field: Define the field representing time information as a time field, and select an appropriate time format, such as YYYY, YYYY-mm-dd, YYYY-MM-DDTHH:MM:SS, etc.
[0069] 4. Label object rule configuration:
[0070] It provides powerful rule configuration capabilities and supports flexible setting of single rules or multiple rule combinations for tag objects. Users can select dimensions, time, and indicators according to their needs, and supports multiple selections and free combinations to adapt to diverse business scenarios.
[0071] After selecting a dimension, the system will automatically push the dimension range for the user to choose from, and also supports the setting of a custom dimension range.
[0072] After selecting the time, the system will push the time statistical period such as by day, month, or year, and then maintain a threshold. When calculating the label, the system will automatically fill in the time range according to the settings.
[0073] After selecting the indicator, the system will push the indicator statistics method, including sum (sum), average (avg), count (count), etc., and allow users to set thresholds.
[0074] For tags that cannot be measured through rule configuration, the beanId of the maintenance service is supported for personalized customization and development. The rule and bean service support combination.
[0075] 5. Label calculation:
[0076] The system automatically parses the rules or bean services set by the user. During the rule parsing process, the association model is connected to the entity model through the left join operation, and the data association is realized using the set association fields.
[0077] The dimensions, time and indicators will be combined into where conditions according to the conditions set by the user. The system will perform a group by operation for the existence of indicators, count the indicator values of each entity, and filter out entity objects that meet the conditions through the set indicator threshold.
[0078] When parsing the bean service, the corresponding service is found through the beanId to obtain the entity object, and the final entity object is obtained according to the maintained tag combination method. The final entity object is deduplicated.
[0079] 6. Label portrait generation:
[0080] The tag calculation is triggered by a timer, the calculation results are saved, and a tag portrait is constructed. Users can view specific entity objects and their associated tags through the tag portrait, and the global search function is supported. By entering the name of the entity object, matching tags can be quickly found, providing users with an intuitive and convenient tag management and query experience.
[0081] 7. Label application:
[0082] The smart label calculation method not only provides accurate label generation, but also achieves seamless integration with other business systems through data result synchronization and data service interface. Each business system applies for the right to use label data according to its own needs, and chooses one of the following two synchronization methods to integrate label data:
[0083] Data synchronization: Business systems can directly apply for synchronization permissions for label data to achieve real-time or periodic data updates. This method is suitable for scenarios where label data needs to be processed and analyzed locally, ensuring that business systems can obtain the latest label information in a timely manner.
[0084] Service synchronization: Business systems can obtain label data on demand by calling the provided API service interface. This method is suitable for scenarios with high real-time requirements, allowing business systems to obtain label data instantly when needed, reducing the burden of data storage and processing.
[0085] To ensure data security and compliance, all applications and access to label data will follow strict data management and access control policies. When applying for label data, the business system must clearly define the purpose and scope of data use, as well as data processing and protection measures.
[0086] In addition, by providing detailed API documentation and developer support, we help business systems quickly integrate labeling services to ensure smooth technical implementation.
[0087] The embodiment of the present invention also provides a smart label calculation system based on multiple rule configuration models, including a label object definition module, a label object dimension maintenance module, a label association model maintenance module, a label object rule configuration module, a label calculation module, a label portrait generation module and a label application module;
[0088] The system specifically implements smart tag calculation through the smart tag calculation method based on multiple rule configuration models described in the above embodiments.
[0089] Provides a user interface that allows users to maintain entity objects, entity object dimensions, and associated models, as well as associated fields, dimensions, time, indicators, and other information of associated models. The maintained information is transmitted back to the backend for maintenance in the data table.
[0090] Provides a rule configuration engine that transmits the rules configured by the user on the front end back to the back end and stores them in the rule data table.
[0091] Provide a backend service for label measurement, generate processing SQL according to the rule configuration information, call the bean service according to the configured service information, and complete data splicing and deduplication.
[0092] Provides a portrait display page that displays tag information in the form of graphics and tables, and allows users to perform operations such as searching and sorting on the displayed data.
[0093] Provide an application page for label application, where users of other business systems can fill out an application form and obtain label usage permissions through the application process.
[0094] Provides a calling interface for a tag service, receives calling parameters and returns tag data.
[0095] The tag object definition module:
[0096] The label object is defined based on the entity objects and data models organized by the data center. The label object information includes the object code, object name, corresponding entity object, data model, associated fields, and description information.
[0097] The label object dimension maintenance module:
[0098] Identify the dimension fields in the entity object model to ensure that each dimension field is accurately captured and defined.
[0099] The tag association model maintenance module:
[0100] Maintain the association model of the tag entity and support the simultaneous management of multiple models. Each association model needs to maintain key association fields, as well as various dimensions and indicator fields involved, to ensure data integrity and seamless connection between models.
[0101] Related fields: Ensure that the related fields with entity objects are correctly maintained to achieve accurate association between data.
[0102] Dimension field: The field representing a certain dimension is maintained as a dimension field, and dimension settings are performed, that is, the dimension selection range.
[0103] Indicator field: The field representing the data indicator is maintained as an indicator field to facilitate data statistics.
[0104] Time Field: Define the field representing time information as a time field, and select an appropriate time format, such as YYYY, YYYY-mm-dd, YYYY-MM-DDTHH:MM:SS, etc.
[0105] The tag object rule configuration module:
[0106] It provides powerful rule configuration capabilities and supports flexible setting of single rules or multiple rule combinations for tag objects. Users can select dimensions, time and indicators according to their needs. The system supports multiple selections and free combinations to adapt to diverse business scenarios.
[0107] After selecting a dimension, the system will automatically push the dimension range for the user to choose from, and also supports the setting of a custom dimension range.
[0108] After selecting the time, the system will push the time statistical period such as by day, month, or year, and then maintain a threshold. When calculating the label, the system will automatically fill in the time range according to the settings.
[0109] After selecting the indicator, the system will push the indicator statistics method, including sum (sum), average (avg), count (count), etc., and allow users to set thresholds.
[0110] For tags that cannot be measured through rule configuration, the system also supports maintaining the beanId of the service for personalized customization and development. The rule and bean service support combination.
[0111] The label calculation module:
[0112] The system automatically parses the rules or bean services set by the user. During the rule parsing process, the system connects the association model with the entity model through the leftjoin operation and realizes the data association using the set association fields.
[0113] The dimensions, time and indicators will be combined into where conditions according to the conditions set by the user. The system will perform a group by operation for the existence of indicators, count the indicator values of each entity, and filter out entity objects that meet the conditions through the set indicator threshold.
[0114] When parsing the bean service, the system will find the corresponding service through the beanId to obtain the entity object, and get the final entity object based on the maintained tag combination. The final entity object is deduplicated.
[0115] The label image generation module:
[0116] The system triggers tag calculation through a timer, saves the calculation results, and builds a tag portrait. Users can view specific entity objects and their associated tags through the tag portrait, and supports global search function. By entering the name of the entity object, matching tags can be quickly found, providing users with an intuitive and convenient tag management and query experience.
[0117] The label application module:
[0118] The smart label calculation method not only provides accurate label generation, but also achieves seamless integration with other business systems through data result synchronization and data service interface. Each business system applies for the right to use label data according to its own needs, and chooses one of the following two synchronization methods to integrate label data:
[0119] Data synchronization: Business systems can directly apply for synchronization permissions for label data to achieve real-time or periodic data updates. This method is suitable for scenarios where label data needs to be processed and analyzed locally, ensuring that business systems can obtain the latest label information in a timely manner.
[0120] Service synchronization: Business systems can obtain label data on demand by calling the provided API service interface. This method is suitable for scenarios with high real-time requirements, allowing business systems to obtain label data instantly when needed, reducing the burden of data storage and processing.
[0121] To ensure data security and compliance, all applications and access to label data will follow strict data management and access control policies. When applying for label data, the business system must clearly define the purpose and scope of data use, as well as data processing and protection measures.
[0122] In addition, by providing detailed API documentation and developer support, we help business systems quickly integrate labeling services to ensure smooth technical implementation.
[0123] An embodiment of the present invention further provides an intelligent label calculation device based on multiple rule configuration models, which is characterized by including: at least one memory and at least one processor;
[0124] The at least one memory is used for storing machine-readable programs;
[0125] The at least one processor is used for calling the machine-readable program to implement the intelligent label calculation method based on multiple rule configuration models described in the above embodiments.
[0126] An embodiment of the present invention further provides a computer-readable medium, on which computer instructions are stored. When the computer instructions are executed by a processor, the processor is enabled to execute the intelligent label calculation method based on multiple rule configuration models described in the above embodiments. Specifically, a system or device equipped with a storage medium can be provided, on which software program code for implementing the functions of any one of the above embodiments is stored, and the computer (or CPU or MPU) of the system or device is enabled to read and execute the program code stored in the storage medium.
[0127] In this case, the program code read from the storage medium itself can implement the functions of any one of the above embodiments, so the program code and the storage medium storing the program code constitute a part of the present invention.
[0128] Embodiments of the storage medium for providing program code include floppy disks, hard disks, magneto-optical disks, optical disks (such as CD-ROM, CD-R, CD-RW, DVD-ROM, DVD-RAM, DVD-RW, DVD+RW), magnetic tapes, non-volatile memory cards, and ROMs. Optionally, the program code can be downloaded from a server computer via a communication network.
[0129] In addition, it should be clear that not only can the functions of any one of the above embodiments be realized by executing the program code read by the computer, but also by the operating system or the like operating on the computer based on the instructions of the program code to complete part or all of the actual operations.
[0130] In addition, it can be understood that the program code read from the storage medium is written into the memory provided in the expansion board inserted into the computer or the memory provided in the expansion unit connected to the computer, and then the CPU or the like installed on the expansion board or the expansion unit is enabled to execute part and all of the actual operations based on the instructions of the program code, so as to realize the functions of any one of the above embodiments.
[0131] The present invention is shown and described in detail above through the accompanying drawings and preferred embodiments. However, the present invention is not limited to these disclosed embodiments. Based on the above multiple embodiments, those skilled in the art can know that the code review methods in the above different embodiments can be combined to obtain more embodiments of the present invention, and these embodiments are also within the protection scope of the present invention.
Claims
1. A smart label calculation method based on multiple rule configuration models, characterized in that: Including label object modeling, label association model maintenance, label rule maintenance, label system establishment and label application; Provide a user interface that allows users to maintain entity objects, entity object dimensions, and associated models, as well as associated fields, dimensions, time, and indicator information of associated models; the maintained information is transmitted back to the backend and maintained in the data table; Provides a rule configuration engine, which transmits the rules configured by the user on the front end back to the back end and stores them in the rule data table; Provide backend services for tag calculation, generate processing SQL according to rule configuration information, call bean services according to configured service information, and complete data splicing and deduplication; Provides a portrait display page, displays tag information in the form of graphics and tables, and allows users to perform operations such as search and sorting on the displayed data; Provide an application page for label application. Users of other business systems can fill out the application form and obtain label usage rights through the application process. Provides a calling interface for label services, receives calling parameters and returns label data.
2. The smart tag calculation method based on multiple rule configuration models according to claim 1, characterized in that: The specific implementation process of this method includes the following steps: 1) Tag object definition: Tag objects are defined based on the entity objects and data models compiled by the data center. Tag object information includes object code, object name, corresponding entity object, data model, associated fields, and description information; 2) Label object dimension maintenance: Identify the dimension fields in the entity object model to ensure that each dimension field is accurately captured and defined; 3) Tag association model maintenance: maintain the association model of tag entities and support simultaneous management of multiple models; 4) Label object rule configuration: supports flexible setting of single rule or multiple rule combinations for label objects; supports maintenance of service beanId for labels that cannot be measured through rule configuration, and performs personalized customization development; the rules and bean services support combination; 5) Tag calculation: The system automatically parses the rules or bean services set by the user. During the rule parsing process, the association model is connected to the entity model through the leftjoin operation, and the data is associated using the set association fields; When parsing the bean service, the corresponding service is found through the beanId to obtain the entity object, and the final entity object is obtained according to the maintained tag combination method. The final entity object is deduplicated; 6) Label portrait generation: trigger label measurement through a timer, save the measurement results, and build a label portrait; 7) Tag application: Achieve seamless integration with other business systems through data result synchronization and data service interface.
3. The smart tag calculation method based on multiple rule configuration models according to claim 2, characterized in that: The tag association model maintenance mentioned above requires that each association model maintains key association fields, as well as various dimensions and indicator fields involved, to ensure data integrity and seamless connection between models; Related fields: Ensure that the related fields of entity objects are correctly maintained to achieve accurate association between data; Dimension field: The field representing a certain dimension is maintained as a dimension field, and dimension settings are performed, that is, the dimension selection range; Indicator field: The field representing the data indicator is maintained as an indicator field to facilitate data statistics; Time Field: Define the field representing time information as a time field and select an appropriate time format.
4. The method for calculating smart tags based on multiple rule configuration models according to claim 2, characterized in that: The label object rule configuration allows users to select dimensions, time, and indicators as needed, supporting multiple selections and free combinations to adapt to diverse business scenarios; After selecting a dimension, the system will automatically push the dimension range for the user to choose from, and also supports the setting of custom dimension ranges; After selecting the time, the system will push the time statistical period and maintain a threshold. When calculating the label, the system will automatically fill in the time range according to the settings; After selecting the indicator, the system will push the indicator statistics method, including sum, average, count, and allow users to set thresholds.
5. The method for calculating smart tags based on multiple rule configuration models according to claim 2, characterized in that: The tag is calculated, The dimensions, time and indicators will be combined into where conditions according to the conditions set by the user. The system will perform a group by operation for the existence of indicators, count the indicator values of each entity, and filter out entity objects that meet the conditions through the set indicator threshold.
6. The method for calculating smart tags based on multiple rule configuration models according to claim 2, characterized in that: The label portrait is generated, Users can view specific entity objects and their associated tags through tag portraits, and support global search functions, which allow users to quickly find matching tags by entering the name of the entity object.
7. The method for calculating smart tags based on multiple rule configuration models according to claim 2, characterized in that: For the label application, each business system applies for the permission to use the label data according to its own needs, and selects one of the following two synchronization methods to integrate the label data: Data synchronization: The business system directly applies for synchronization permissions for tag data to achieve real-time or regular data updates; Service synchronization: The business system obtains label data on demand by calling the provided API service interface; By providing detailed API documentation and developer support, we help business systems quickly integrate labeling services.
8. A smart label computing system based on multiple rule configuration models, characterized in that: It includes label object definition module, label object dimension maintenance module, label association model maintenance module, label object rule configuration module, label measurement module, label portrait generation module and label application module; The system specifically implements smart tag calculation through the method described in any one of claims 1 to 7.
9. A smart tag computing device based on multiple rule configuration models, characterized in that: include: at least one memory and at least one processor; The at least one memory is used to store a machine-readable program; The at least one processor is used to call the machine-readable program to implement the method described in any one of claims 1 to 7.
10. A computer-readable medium, characterized in that The computer readable medium stores computer instructions, which, when executed by a processor, can implement the method described in any one of claims 1 to 7.