Business card information grading exchange method and system based on rule constraint and artificial intelligence, storage medium and equipment

Abstract

The invention discloses a business card information grading exchange method and system based on rule constraint and artificial intelligence, a storage medium and equipment, and relates to the technical field of artificial intelligence application and computer information security. The method comprises the following steps: a user performs real-name authentication, creates personal hierarchical business cards after the authentication is passed, encrypts the personal hierarchical business cards and stores the personal hierarchical business cards in a hierarchical business card library; constructing a business card information grading exchange index system; under the constraint of a set current information level, carrying out user business card information level-by-level exchange; using an artificial intelligence engine to collect and analyze interaction data between users, and generating a recommendation proposal of information upgrading; and in response to agreement operation of the user on the recommendation proposal, completing information upgrading exchange under authorization and management and control of the business card information grading exchange index system. Through deep cooperation of cryptography, a rule engine and controllable artificial intelligence, potential conflicts in multi-index cooperative work are solved, and high unification of intelligence, safety and compliance is achieved.

Description

Technical Field

[0001] This invention relates to the fields of artificial intelligence applications and computer information security technology, and in particular to a hierarchical exchange method, system, storage medium and device for business card information based on rule constraints and artificial intelligence. Background Technology

[0002] Traditional business networking relies on the exchange of paper business cards, which are static, easily lost, and environmentally unfriendly, and cannot control the degree of information exposure based on the closeness of the social relationship. While existing electronic business card applications (such as vCard and various mini-program business cards) have solved some of the problems of physical media, they still have the following significant drawbacks: 1. "One-size-fits-all" information exchange: When exchanging information, all pre-set information is usually transmitted, which makes it impossible to release information in a tiered manner based on scenarios and relationships, and poses a risk of privacy leakage; 2. Lack of dynamism and intelligence: Business card information is static and cannot be linked to real-time interaction. The exchange process is mostly mechanical, requiring manual selection by the user, and lacks intelligent recommendations and automated processing based on context and interaction history; 3. Disjointed Offline and Online Experiences: Offline paper business card exchange follows the social convention of "handing it over signifies consent," while online systems typically require multiple confirmations, resulting in cumbersome processes and inconsistent user experiences. Furthermore, offline business cards, with their information printed in plain text, fail to provide tiered privacy controls. 4. Lack of systematic governance: There is a lack of automated rule constraints and processing mechanisms embedded in core business processes for platform governance issues such as harassment and illegal content; 5. Lack of rules and constraints on the exchange of contact information: When processing the exchange of information between contacts, existing systems often ignore the principles of information matching verification and privacy parity, which can easily lead to information mismatch or excessive exposure of one party's information.

[0003] Therefore, proposing a hierarchical exchange method, system, storage medium, and device for business card information based on rule constraints and artificial intelligence to solve the problems existing in the prior art is an urgent problem to be solved by those skilled in the art. Summary of the Invention

[0004] In view of this, the present invention provides a hierarchical exchange method, system, storage medium and device for business card information based on rule constraints and artificial intelligence. Through the deep collaboration of cryptography, rule engine and controllable artificial intelligence, it solves the potential conflicts in the collaborative work of multiple indicators and achieves a high degree of unity between intelligence, security and compliance.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: A hierarchical exchange method for business card information based on rule constraints and artificial intelligence includes: S1. Users undergo real-name authentication. After successful authentication, a personal tiered business card is created, encrypted, and stored in the tiered business card library. S2. Construct a hierarchical business card information exchange indicator system with clear priorities, including: basic security indicators, platform governance indicators, scenario routing indicators, and business logic indicators; S3. Under the current information level constraint set by the business card information hierarchical exchange index system, conduct hierarchical exchange of user business card information based on the interaction data between users. S4. Use an artificial intelligence engine to collect and analyze user interaction data, calculate the recommendation probability of relationship upgrade based on machine learning model, and generate information upgrade recommendation suggestions. S5. Responding to the user's explicit consent to the recommendation proposal, and under the authorization and control of the business card information hierarchical exchange indicator system, complete the secure and controllable information upgrade exchange.

[0006] Optionally, in S1, the user performs real-name authentication by: recognizing the ID card through OCR and comparing it with the liveness detection information; verifying the authenticity of the ID card information and the liveness detection information through the eID interface; and creating a user's personal hierarchical business card after successful verification. Personal tiered business cards include: personal business cards and personal business cards. Personal business cards are divided into three levels: L1, L2, and L3, while personal business cards are divided into four levels: B1, B2, B3, and B4. Personal Business Card: Level 1 information fields include: last name, gender and title; Level 2 information fields include: last name, gender and title, and phone number; Level 3 information fields include: full name, gender and title, phone number, and personal activity. Personal Business Cards: B1 level information fields include: company name, address, telephone number, and company news; B2 level information fields include: last name, gender / title, telephone number, job title, company name, and company news; B3 level information fields include: name, gender / title, photo, telephone number, job title, company name, and company news; B4 level information fields include: name, photo, company name, and employee ID; personal business cards L1, L2, and L3 have progressively higher information content. Personal business cards are categorized into B1, B2, B3, and B4, which differentiate between the levels of disclosure of corporate information and personal information.

[0007] Optionally, in S1, the personal tiered business card can be encrypted using the above method, specifically as follows: The national cryptographic algorithm is used to encrypt the personal business card information, personal business card information, and each information data field of the user.

[0008] Optionally, in S2, a hierarchical business card information exchange indicator system with clear priorities can be constructed as follows: A hierarchical exchange indicator system for business card information is built using the open-source business rules engine Drools; each indicator is written in DRL script form and supports dynamic hot updates.

[0009] Of the methods described above, the basic security indicators in S2 are of the highest priority and are used to forcibly block and intercept sensitive content involving illegal or non-compliant activities. Platform governance metrics are used to maintain a healthy ecosystem, automatically process user reports, and prevent abuse. Business logic metrics include: privacy protection metrics, ensuring that user-unknown or unverified information is not disclosed in any exchange scenario; real-world social metrics, simulating offline social practices to achieve a unified online and offline experience; authorization constraint metrics, managing authorization for all information exchange upgrade behaviors; and address book exchange metrics, triggered when both parties' address books contain each other's information, controlling the level of the exchanged business card through field matching verification, or deciding to terminate the exchange. The scenario routing metric routes requests to a unique corresponding business logic metric based on the source of the exchange request, thus avoiding parallel triggering of metrics.

[0010] Optionally, in S3 of the above method, under the current information level constraint set by the hierarchical exchange index system for business card information, hierarchical exchange of user business card information is performed based on user interaction data, specifically as follows: The basic security indicators trigger the content security review service to forcibly block and intercept user-generated content; The platform uses governance metrics to determine whether user behavior is abnormal, monitors the frequency of user business card delivery, and triggers anti-harassment measures. Requests are routed to a unique business logic indicator by a scenario routing indicator, and hierarchical exchange of business card information is performed at the specified business logic indicator. Based on the information exchange level determined by business logic indicators, send the unique encryption key for the user information data field corresponding to the information exchange level; The user information data field corresponding to the information exchange level is decrypted using the unique encryption key sent, and the information exchange is then performed.

[0011] Optionally, in the above method, in S4, an artificial intelligence engine is used to collect and analyze user interaction data, calculate the recommendation probability of relationship upgrading based on a machine learning model, and generate information upgrading recommendation suggestions, specifically as follows: The AI ​​engine uses the LightGBM model, and the input is a numerical and normalized multimodal feature vector filtered by the rule engine Drools; Calculate and output the recommended probability of relationship escalation, and the output probability is calibrated by Platt Scaling; Before generating recommendations, the rule engine Drools is called to query the "maximum allowed upgrade level" of the current relationship, and the calibrated probability output by the model is compared with the preset upgrade level threshold. When the probability is higher than the threshold and the target upgrade level does not exceed the maximum allowed upgrade level set by the business logic indicator, an information upgrade recommendation proposal is generated.

[0012] The above methods, optionally, include multimodal feature vectors, including: Breadth feature: Number of mutual contacts; In-depth feature: Average viewing time for business cards; Scene characteristics: interaction time period and method.

[0013] A hierarchical business card information exchange system based on rule constraints and artificial intelligence, applied to any of the aforementioned hierarchical business card information exchange methods based on rule constraints and artificial intelligence, includes, The rules engine module is used to store and execute the hierarchical exchange indicator system and layered adjudication logic for business card information, and is implemented using the Drools engine. Artificial Intelligence Engine Module: Used to perform data analysis and generate recommendation proposals within the constraints established by the Rules Engine Module, with a built-in LightGBM machine learning model; Access control module: Used to execute access control decision logic based on relationship hierarchy; Scene routing module: Used to receive exchange requests and route them to the corresponding single business logic metric in the rule engine according to the request source.

[0014] Optionally, the above system may implement distributed transaction management based on the Saga pattern using the Seata framework. Each module of the system is deployed independently and communicates with other systems via the gRPC interface. mTLS communication and traffic governance are implemented through the Istio service mesh, and system observability is achieved by integrating Prometheus, Grafana, and Jaeger.

[0015] A computer-readable storage medium storing executable instructions, which, when executed by a processor, implement the hierarchical exchange method for business card information based on rule constraints and artificial intelligence as described above.

[0016] A hierarchical business card information exchange device based on rule constraints and artificial intelligence includes: a processor, a memory, and a communication interface; The memory stores the processor's executable instructions; When the processor executes instructions, it implements any of the above-mentioned methods for hierarchical exchange of business card information based on rule constraints and artificial intelligence.

[0017] As can be seen from the above technical solutions, compared with the prior art, this invention provides a hierarchical exchange method, system, storage medium, and device for business card information based on rule constraints and artificial intelligence, which has the following beneficial effects: Through cryptographic protection, from the information source (real-name authentication) to static storage (field-level encryption), it ensures that the data foundation analyzed by artificial intelligence is highly secure and privacy-protected, eliminating the risk of data leakage or misuse; it constructs a controllable artificial intelligence application paradigm of "rules first, intelligence empowerment," fundamentally solving the unpredictability and security risks of artificial intelligence decision-making; it achieves the safe, reliable, and controllable implementation of artificial intelligence in the field of business social networking; and it adopts the LightGBM interpretable model, combined with… Rule logs ensure that the reasons for each AI recommendation are traceable and analyzable, enhancing the system's transparency and credibility. All core exchange logic (such as the first exchange being L1 and a push notification upon scanning a B3 code) is solidified and executed by the Drools rule engine, avoiding inconsistencies in behavior caused by complex code logic or AI misjudgments. Adjustments to platform governance strategies (such as anti-harassment thresholds) or business logic can take effect in real time by updating the DRL script in the configuration center without requiring service shutdown and restart, greatly improving the system's operational efficiency and response speed. Through the construction of a layered adjudication system and a scenario routing mechanism, the inherent conflict problem of multi-indicator systems is fundamentally solved, improving the overall robustness and maintainability of the system. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0019] Figure 1 A flowchart illustrating a hierarchical exchange method for business card information based on rule constraints and artificial intelligence, provided by this invention; Figure 2 This invention provides a structural diagram of a hierarchical business card information exchange system based on rule constraints and artificial intelligence. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] In this application, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. The terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0022] Reference Figure 1 As shown, this invention discloses a hierarchical exchange method for business card information based on rule constraints and artificial intelligence, comprising: S1. Users undergo real-name authentication. After successful authentication, a personal tiered business card is created, encrypted, and stored in the tiered business card library. S2. Construct a hierarchical business card information exchange indicator system with clear priorities, including: basic security indicators, platform governance indicators, scenario routing indicators, and business logic indicators; S3. Under the current information level constraint set by the business card information hierarchical exchange index system, conduct hierarchical exchange of user business card information based on the interaction data between users. S4. Use an artificial intelligence engine to collect and analyze user interaction data, calculate the recommendation probability of relationship upgrade based on machine learning model, and generate information upgrade recommendation suggestions. S5. Responding to the user's explicit consent to the recommendation proposal, and under the authorization and control of the business card information hierarchical exchange indicator system, complete the secure and controllable information upgrade exchange.

[0023] Furthermore, in S1, users undergo real-name authentication, specifically by: recognizing ID documents through OCR and comparing them with liveness detection information; verifying the authenticity of the ID document information and liveness detection information through an authoritative identity data source (eID interface); and creating a user's personal hierarchical business card after successful verification. Personal tiered business cards include: personal business cards and personal business cards. Personal business cards are divided into three levels: L1, L2, and L3, while personal business cards are divided into four levels: B1, B2, B3, and B4. Personal Business Card: Level 1 information fields include: last name, gender and title; Level 2 information fields include: last name, gender and title, and phone number; Level 3 information fields include: full name, gender and title, phone number, and personal activity. Personal Business Cards: B1 level information fields include: company name, address, telephone number, and company news; B2 level information fields include: last name, gender / title, telephone number, job title, company name, and company news; B3 level information fields include: name, gender / title, photo, telephone number, job title, company name, and company news; B4 level information fields include: name, photo, company name, and employee ID; personal business cards L1, L2, and L3 have progressively higher information content. Personal business cards are categorized into B1, B2, B3, and B4, which differentiate between the levels of disclosure of corporate information and personal information.

[0024] Furthermore, in S1, the personal hierarchical business cards are encrypted, specifically by using the national cryptographic algorithm to encrypt the personal business card information, personal business card information, and each information data field of the user. Furthermore, the real-name authentication chain based on the national cryptographic algorithm adopts the SM2 elliptic curve algorithm and the SM4 block cipher algorithm. In a TEE environment, the SM2 elliptic curve algorithm generates a master key for the user, which is protected by the TEE hardware. For personal business card information, it is encrypted and stored using SM4-CTR mode. CTR mode supports streaming encryption and random access. For personal business card information, which is variable in length and may be quite large, the more efficient SM4-GCM mode is used for encrypted storage. For each user information data field, the HMAC-based Key Derivation Function algorithm is used, with the master key as input and the name of each user information data field as the salt, to derive a unique encryption key for each user information data field.

[0025] Furthermore, in S2, a hierarchical business card information exchange indicator system with clear priorities is constructed, specifically as follows: A hierarchical exchange indicator system for business card information is built using the open-source business rules engine Drools; each indicator is written in DRL script form and supports dynamic hot updates. Furthermore, the core of the open-source business rules engine Drools is the Rete algorithm. This algorithm caches intermediate results of pattern matching by building network nodes, avoiding repeated calculations, which is very suitable for the scenario in this invention where the rules are fixed but the request volume is large. Each metric is written in the form of a DRL script. When the threshold of the anti-harassment rule needs to be updated, you only need to modify the DRL file in the configuration center, and the engine cluster will dynamically reload the rule without restarting the service, thus realizing hot update of business rules.

[0026] Furthermore, in S2, basic security indicators are given the highest priority and are used to forcibly block and intercept sensitive content involving illegal or non-compliant activities. Platform governance metrics are used to maintain a healthy ecosystem, automatically process user reports, and prevent abuse. Business logic metrics include: privacy protection metrics, ensuring that user-unknown or unverified information is not disclosed in any exchange scenario; real-world social metrics, simulating offline social practices to achieve a unified online and offline experience; authorization constraint metrics, managing authorization for all information exchange upgrade behaviors; and address book exchange metrics, triggered when both parties' address books contain each other's information, controlling the level of the exchanged business card through field matching verification, or deciding to terminate the exchange. The scenario routing metric routes requests to a unique corresponding business logic metric based on the source of the exchange request, thus avoiding parallel triggering of metrics.

[0027] Furthermore, in S3, under the current information level constraint set by the hierarchical exchange index system for business card information, hierarchical exchange of user business card information is performed based on user interaction data, specifically as follows: The basic security indicators trigger the content security review service to forcibly block and intercept user-generated content; The platform uses governance metrics to determine whether user behavior is abnormal, monitors the frequency of user business card delivery, and triggers anti-harassment measures. Requests are routed to a unique business logic indicator by a scenario routing indicator, and hierarchical exchange of business card information is performed at the specified business logic indicator. Based on the information exchange level determined by business logic indicators, send the unique encryption key for the user information data field corresponding to the information exchange level; The user information data field corresponding to the information exchange level is decrypted using the unique encryption key sent for the user information data field, and the information exchange is then performed. Furthermore, the information exchange level, determined based on business logic indicators, is specifically as follows: Force the output of the lowest level information L1 during the first exchange; When scanning a specific offline business card that is bound to a dynamically encrypted QR code, the system simulates the "submit and agree" logic to push complete information unilaterally to the scanning party. Implement a dual confirmation and authorization mechanism for all information upgrade actions; When both parties have each other's contact information, the system rigidly controls the level of the business card to be exchanged or terminates the exchange based on the intelligent field matching verification results using Jaro-Winkler and cosine similarity weighted average. It also supports non-peer-to-peer output based on enterprise information error downgrade rules to protect privacy.

[0028] Furthermore, in S4, an artificial intelligence engine is used to collect and analyze user interaction data, calculate the recommendation probability of relationship escalation based on a machine learning model, and generate information escalation recommendation suggestions, specifically: The AI ​​engine uses the LightGBM model, with input consisting of numerical and normalized multimodal feature vectors filtered by the rule engine Drools. The LightGBM model offers fast training speed and provides feature importance. Calculate and output the recommendation probability of relationship upgrade, and calibrate the output probability using Platt Scaling; use Platt Scaling to calibrate the original prediction score of the model so that the output upgrade probability is closer to the true distribution. Before generating recommendations, the rule engine Drools is called to query the "maximum allowed upgrade level" of the current relationship, and the calibrated probability output by the model is compared with the preset upgrade level threshold. When the probability is higher than the threshold and the target upgrade level does not exceed the maximum allowed upgrade level set by the business logic indicator, an information upgrade recommendation proposal is generated. The artificial intelligence engine operates within a rules-based "sandbox," where its inputs, processing, and outputs are all subject to technical constraints.

[0029] Furthermore, multimodal feature vectors include: Breadth feature: Number of mutual contacts; In-depth feature: Average viewing time for business cards; Scene characteristics: interaction time period and method.

[0030] Reference Figure 2 As shown, a hierarchical business card information exchange system based on rule constraints and artificial intelligence, applied to any of the aforementioned hierarchical business card information exchange methods based on rule constraints and artificial intelligence, includes, The rules engine module is used to store and execute the hierarchical exchange indicator system and layered adjudication logic for business card information, and is implemented using the Drools engine. Artificial Intelligence Engine Module: Used to perform data analysis and generate recommendation proposals within the constraints established by the Rules Engine Module, with a built-in LightGBM machine learning model; Access control module: Used to execute access control decision logic based on relationship hierarchy; Scene routing module: Used to receive exchange requests and route them to the corresponding single business logic metric in the rule engine according to the request source.

[0031] Optionally, the above system may implement distributed transaction management based on the Saga pattern using the Seata framework. Each module of the system is deployed independently and communicates with other systems via the gRPC interface. mTLS communication and traffic governance are implemented through the Istio service mesh, and system observability is achieved by integrating Prometheus, Grafana, and Jaeger.

[0032] A computer-readable storage medium storing executable instructions, which, when executed by a processor, implement the hierarchical exchange method for business card information based on rule constraints and artificial intelligence as described above.

[0033] A hierarchical business card information exchange device based on rule constraints and artificial intelligence includes: a processor, a memory, and a communication interface; The memory stores the processor's executable instructions; When the processor executes instructions, it implements any of the above-mentioned methods for hierarchical exchange of business card information based on rule constraints and artificial intelligence.

[0034] In one specific embodiment, the user has agreed to the relevant agreement; user A frequently sends advertising information to user B; the system monitors that A's daily delivery frequency exceeds a threshold (e.g., 10 times), the anti-harassment indicator is triggered, and the system sends an immediate confirmation and authorization request to B for this behavior; if B confirms that this is harassment behavior, the system will temporarily mute A's delivery function to B.

[0035] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, for system or system embodiments, since they are basically similar to method embodiments, the description is relatively simple, and relevant parts can be referred to the descriptions in the method embodiments. The systems and system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0036] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A hierarchical exchange method for business card information based on rule constraints and artificial intelligence, characterized in that, include: S1. Users undergo real-name authentication. After successful authentication, a personal tiered business card is created, encrypted, and stored in the tiered business card library. S2. Construct a hierarchical business card information exchange indicator system with clear priorities, including: basic security indicators, platform governance indicators, scenario routing indicators, and business logic indicators; S3. Under the current information level constraint set by the business card information hierarchical exchange index system, conduct hierarchical exchange of user business card information based on the interaction data between users. S4. Use an artificial intelligence engine to collect and analyze user interaction data, calculate the recommendation probability of relationship upgrade based on machine learning model, and generate information upgrade recommendation suggestions. S5. Responding to the user's explicit consent to the recommendation proposal, and under the authorization and control of the business card information hierarchical exchange indicator system, complete the secure and controllable information upgrade exchange.

2. The hierarchical exchange method for business card information based on rule constraints and artificial intelligence according to claim 1, characterized in that, In S1, users undergo real-name authentication, specifically by: recognizing ID documents through OCR and comparing them with liveness detection information; verifying the authenticity of the ID document information and liveness detection information through the eID interface; and creating a user's personal hierarchical business card after successful verification. Personal tiered business cards include: personal business cards and personal business cards. Personal business cards are divided into three levels: L1, L2, and L3, while personal business cards are divided into four levels: B1, B2, B3, and B4. Personal Business Card: Level 1 information fields include: last name, gender and title; Level 2 information fields include: last name, gender and title, and phone number; Level 3 information fields include: full name, gender and title, phone number, and personal activity. Personal Business Cards: B1 level information fields include: company name, address, telephone number, and company news; B2 level information fields include: last name, gender / title, telephone number, job title, company name, and company news; B3 level information fields include: name, gender / title, photo, telephone number, job title, company name, and company news; B4 level information fields include: name, photo, company name, and employee ID; personal business cards L1, L2, and L3 have progressively higher information content. Personal business cards are categorized into B1, B2, B3, and B4, which differentiate between the levels of disclosure of corporate information and personal information.

3. The hierarchical exchange method for business card information based on rule constraints and artificial intelligence according to claim 2, characterized in that, In S1, the personal tiered business cards are encrypted, specifically as follows: The national cryptographic algorithm is used to encrypt the personal business card information, personal business card information, and each information data field of the user.

4. The hierarchical exchange method for business card information based on rule constraints and artificial intelligence according to claim 3, characterized in that, In S2, a hierarchical business card information exchange indicator system with clear priorities is constructed, specifically as follows: A hierarchical exchange indicator system for business card information is built using the open-source business rules engine Drools; each indicator is written in DRL script form and supports dynamic hot updates.

5. A hierarchical exchange method for business card information based on rule constraints and artificial intelligence according to claim 4, characterized in that, In S2, basic security indicators are the highest priority and are used to forcibly block and intercept sensitive content involving illegal or irregular activities. Platform governance metrics are used to maintain a healthy ecosystem, automatically process user reports, and prevent abuse. Business logic metrics include: privacy protection metrics, ensuring that user-unknown or unverified information is not disclosed in any exchange scenario; real-world social metrics, simulating offline social practices to achieve a unified online and offline experience; authorization constraint metrics, managing authorization for all information exchange upgrade behaviors; and address book exchange metrics, triggered when both parties' address books contain each other's information, controlling the level of the exchanged business card through field matching verification, or deciding to terminate the exchange. The scenario routing metric routes requests to a unique corresponding business logic metric based on the source of the exchange request, thus avoiding parallel triggering of metrics.

6. The hierarchical exchange method for business card information based on rule constraints and artificial intelligence according to claim 5, characterized in that, In S3, under the current information level constraint set by the hierarchical exchange index system for business card information, hierarchical exchange of user business card information is carried out based on user interaction data, specifically as follows: The basic security indicators trigger the content security review service to forcibly block and intercept user-generated content; The platform uses governance metrics to determine whether user behavior is abnormal, monitors the frequency of user business card delivery, and triggers anti-harassment measures. Requests are routed to a unique business logic indicator by a scenario routing indicator, and hierarchical exchange of business card information is performed at the specified business logic indicator. Based on the information exchange level determined by business logic indicators, send the unique encryption key for the user information data field corresponding to the information exchange level; The user information data field corresponding to the information exchange level is decrypted using the unique encryption key sent, and the information exchange is then performed.

7. A hierarchical exchange method for business card information based on rule constraints and artificial intelligence according to claim 6, characterized in that, In S4, an artificial intelligence engine is used to collect and analyze user interaction data, calculate the recommendation probability of relationship escalation based on a machine learning model, and generate information escalation recommendation suggestions, specifically: The AI ​​engine uses the LightGBM model, and the input is a numerical and normalized multimodal feature vector filtered by the rule engine Drools; Calculate and output the recommended probability of relationship escalation, and the output probability is calibrated by Platt Scaling; Before generating recommendations, the rule engine Drools is called to query the maximum allowed upgrade level of the current relationship, and the calibrated probability output by the model is compared with the preset upgrade threshold. When the probability is higher than the threshold and the target upgrade level does not exceed the maximum allowed upgrade level set by the business logic indicator, an information upgrade recommendation proposal is generated.

8. A hierarchical exchange method for business card information based on rule constraints and artificial intelligence according to claim 7, characterized in that, Multimodal feature vectors include: Breadth feature: Number of mutual contacts; In-depth feature: Average viewing time for business cards; Scene characteristics: interaction time period and method.

9. A hierarchical business card information exchange system based on rule constraints and artificial intelligence, applied to the hierarchical business card information exchange method based on rule constraints and artificial intelligence as described in any one of claims 1-8, comprising, The rules engine module is used to store and execute the hierarchical exchange indicator system and layered adjudication logic for business card information, and is implemented using the Drools engine. Artificial Intelligence Engine Module: Used to perform data analysis and generate recommendation proposals within the constraints established by the Rules Engine Module, with a built-in LightGBM machine learning model; Access control module: Used to execute access control decision logic based on relationship hierarchy; Scene routing module: Used to receive exchange requests and route them to the corresponding single business logic metric in the rule engine according to the request source.

10. A hierarchical business card information exchange system based on rule constraints and artificial intelligence according to claim 9, characterized in that, The system implements distributed transaction management based on the Saga pattern using the Seata framework; Each module of the system is deployed independently and communicates with other systems via the gRPC interface. mTLS communication and traffic governance are implemented through the Istio service mesh, and system observability is achieved by integrating Prometheus, Grafana, and Jaeger.

11. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores executable instructions that, when executed by a processor, implement a hierarchical exchange method for business card information based on rule constraints and artificial intelligence as described in any one of claims 1-8.

12. A hierarchical business card information exchange device based on rule constraints and artificial intelligence, characterized in that, include: Processor, memory, and communication interface; The memory stores the processor's executable instructions; When the processor executes instructions, it implements a hierarchical exchange method for business card information based on rule constraints and artificial intelligence as described in any one of claims 1-8.

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