User behavior monitoring method of intellectual property trading platform based on smart contract

Abstract

The present invention relates to the technical field of intellectual property transaction management, and discloses a user behavior monitoring method of an intellectual property transaction platform based on a smart contract, including: deploying a smart contract on the intellectual property transaction platform; recording the transaction behavior of a transaction user in the smart contract; reading the multidimensional performance information in the transaction behavior according to a preset interface protocol; generating the performance deviation of the transaction user according to the multidimensional performance information and a preset performance deviation generation algorithm; obtaining the historical reputation score of the transaction user based on the smart contract, updating the user reputation of the historical reputation score according to the performance deviation and a preset time decay factor, and obtaining the reputation update score of the transaction user; and hierarchically managing the transaction user according to the reputation update score and a preset contact map of responsible persons. The present invention can improve the efficiency of user behavior monitoring of the intellectual property transaction platform.

Description

Technical Field

[0001] The present invention relates to the technical field of intellectual property transaction management, and in particular to a method for monitoring user behavior of an intellectual property transaction platform based on a smart contract. Background Art

[0002] As an intangible asset, the value of intellectual property depends on legal transactions and use. If violations are not monitored in a timely manner, it will not only damage the rights and interests of the intellectual property owner, but also undermine the fairness and healthy order of the entire trading market. On the other hand, by efficiently monitoring user behavior, the platform can better understand user needs and trading habits, provide users with more accurate services and recommendations, thereby improving user experience, enhancing the competitiveness of the platform, and promoting the activity and success rate of intellectual property transactions.

[0003] Traditional monitoring systems often rely on manual inspection of transaction records or use simple rule matching algorithms. Faced with massive transaction data and complex user behaviors, it is difficult to achieve real-time and comprehensive monitoring. For example, when dealing with complex transactions involving multiple types of intellectual property (such as patents, trademarks, copyrights, etc.), manual inspection is not only time-consuming and laborious, but also prone to omissions. Secondly, intellectual property transactions involve multiple links and multiple participants, and the data formats and storage methods of different links and participants are different. For example, contract information, capital flow information, intellectual property rights change information, etc. in the transaction process are stored in different systems respectively, and there is a lack of unified data interfaces and standards, resulting in low efficiency in collecting and analyzing these data. Previous monitoring methods have difficulty in conducting in-depth analysis and modeling of user behavior, and cannot accurately predict potential risks and problems. Therefore, it is urgent to improve the efficiency of user behavior monitoring on intellectual property trading platforms. Summary of the invention

[0004] The present invention provides a method for monitoring user behavior of an intellectual property trading platform based on a smart contract, the main purpose of which is to solve the problem of low efficiency in monitoring user behavior of the intellectual property trading platform.

[0005] To achieve the above purpose, the present invention provides a method for monitoring user behavior of an intellectual property transaction platform based on a smart contract, comprising:

[0006] Deploy smart contracts on the intellectual property trading platform;

[0007] Record the transaction behavior of transaction users based on the smart contract;

[0008] Reading the multi-dimensional performance information in the transaction behavior according to a preset interface protocol;

[0009] The performance deviation of the transaction user is generated according to the multi-dimensional performance information and a preset performance deviation generation algorithm, wherein the preset performance deviation generation algorithm is:

[0010]

[0011] in, is the performance deviation of the transaction user, It is the identifier of the fulfillment information type of multi-dimensional fulfillment information. is the total number of fulfillment information types, It belongs to The total number of dimensions of fulfillment information types, It is The first type of fulfillment information The weight of the dimension, It is Dimension identifier of the fulfillment information type, It is Of the fulfillment information types The actual value of the dimension, It is Of the fulfillment information types The expected value of the dimension, is the penalty coefficient;

[0012] Acquire the historical reputation score of the transaction user based on the smart contract, perform user reputation update on the historical reputation score according to the contract performance deviation and a preset time decay factor, and obtain an updated reputation score of the transaction user;

[0013] The transaction users are managed in a hierarchical manner according to the credit update score and the preset responsible person contact map.

[0014] Optionally, the deploying of smart contracts on the intellectual property trading platform includes:

[0015] Create smart contract templates for intellectual property trading platforms;

[0016] The smart contract template is associated with the transaction users of the intellectual property transaction platform, and the transaction rules and transaction terms of the transaction behavior are defined in the smart contract template.

[0017] Optionally, recording the transaction behavior of the transaction user based on the smart contract includes:

[0018] When there is a transaction on the intellectual property trading platform, the smart contract verifies the transaction conditions of the transaction behavior generated by the intellectual property trading platform;

[0019] The transaction behavior verified by the transaction conditions is updated to the smart contract.

[0020] Optionally, the reading of the multi-dimensional performance information in the transaction behavior according to a preset interface protocol includes:

[0021] Extract key information from the transaction behavior according to the rules in the preset interface protocol to obtain behavior information of the transaction behavior;

[0022] The behavior information is classified to obtain multi-dimensional performance information in the transaction behavior, wherein the multi-dimensional performance information includes: time performance information, scope performance information, quality performance information and quantity performance information.

[0023] Optionally, obtaining the historical credit score of the transaction user based on the smart contract includes:

[0024] A unique identifier for identifying the transaction user;

[0025] Perform node search on key nodes in the smart contract according to the unique identifier;

[0026] The historical credit score of the transaction user is determined according to the search result of the node search.

[0027] Optionally, performing user reputation updating on the historical reputation score according to the performance deviation and a preset time decay factor to obtain an updated reputation score of the transaction user includes:

[0028] The historical reputation score is updated according to a preset reputation update algorithm, the performance deviation and a preset time decay factor to obtain a reputation update score for the transaction user, wherein the preset reputation update algorithm is:

[0029]

[0030] in, is the credit update score of the transaction user, is the historical reputation score, is The time decay factor at time, is the performance deviation, is the weight factor of the performance deviation on the reputation score.

[0031] Optionally, the time decay factor is:

[0032]

[0033] in, is The time decay factor at time, is the decay rate, It is a time stamp.

[0034] Optionally, the step of performing hierarchical management on the transaction users according to the reputation update score and a preset responsible person contact map includes:

[0035] Performing reputation grading on the transaction user according to the reputation update score to obtain the reputation level of the transaction user;

[0036] generating a management strategy for the transaction user according to the credit rating and a pre-generated warning threshold;

[0037] Transaction management is performed on the transaction users according to a preset responsible person contact map and the management strategy.

[0038] Optionally, the pre-generated warning threshold is:

[0039]

[0040] in, is the pre-generated warning threshold, is the historical warning threshold of the transaction user, is the adjustment factor, is the magnitude of change in the credit score.

[0041] Optionally, before performing hierarchical management on the transaction users according to the reputation update score and the preset responsible person contact map, the method further includes:

[0042] Define the person responsible for the intellectual property trading platform;

[0043] Establishing an association model between the responsible person and the transaction user, wherein the association model defines communication paths, division of responsibilities and priority of matters;

[0044] A hierarchical graph structure of the intellectual property trading platform is generated according to the role attributes of the responsible persons and the association model, and a preset responsible person contact graph is determined according to the hierarchical graph structure.

[0045] The present invention realizes automatic and real-time recording of transaction user behaviors through the deployment platform of smart contracts, and efficiently reads multi-dimensional performance information in transaction behaviors according to the preset interface protocol. This information covers multiple types and dimensions, providing rich data support for subsequent analysis. By using the preset performance deviation generation algorithm, with the help of penalty factors, combined with different performance information types, the total number of dimensions, the weight of each dimension, and the actual value and expected value, the performance deviation is quickly and accurately calculated, so that the platform can timely detect the user's performance status. At the same time, the user's historical reputation score is obtained with the help of smart contracts, and it is adjusted according to the time decay factor, and then the user's reputation is updated in combination with the performance deviation. Finally, according to the reputation update score and the preset responsible person contact map, the transaction users are accurately graded and managed. This whole set of processes, from information collection, analysis and calculation to management decision-making, makes full use of multi-dimensional performance information, performance deviation, time decay factor, penalty factor, responsible person map and other technical points, which are linked together to realize the efficient operation of user behavior monitoring and significantly improve the efficiency of the intellectual property transaction platform based on smart contracts in user behavior monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 A flowchart of a method for monitoring user behavior of an intellectual property transaction platform based on a smart contract provided by an embodiment of the present invention;

[0047] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0048] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0049] The embodiment of the present application provides a method for monitoring user behavior of an intellectual property trading platform based on a smart contract. The execution subject of the method for monitoring user behavior of an intellectual property trading platform based on a smart contract includes but is not limited to at least one of the electronic devices such as a server and a terminal that can be configured to execute the method provided by the embodiment of the present application. In other words, the method for monitoring user behavior of an intellectual property trading platform based on a smart contract can be executed by software or hardware installed on a terminal device or a server device. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc. The server can be an independent server, or it can be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and big data and artificial intelligence platforms.

[0050] Reference Figure 1 FIG. 1 is a flow chart of a method for monitoring user behavior of an intellectual property transaction platform based on a smart contract according to an embodiment of the present invention. In this embodiment, the method for monitoring user behavior of an intellectual property transaction platform based on a smart contract includes:

[0051] S1. Deploy smart contracts on the intellectual property trading platform.

[0052] In an embodiment of the present invention, the smart contract deployment on the intellectual property transaction platform includes:

[0053] Create smart contract templates for intellectual property trading platforms;

[0054] The smart contract template is associated with the transaction users of the intellectual property transaction platform, and the transaction rules and transaction terms of the transaction behavior are defined in the smart contract template.

[0055] In detail, the smart contract template for creating an intellectual property transaction platform is the basic framework for building the entire smart contract system. The smart contract template specifies common elements such as the basic format of the contract, data storage method, function call interface, etc., ensuring a unified and standardized starting point in different intellectual property transaction scenarios.

[0056] In detail, in a smart contract template for a software copyright transaction, general structures such as the format for recording software version information, the storage location for software function descriptions, and the entry area for basic information of both parties to the transaction may be pre-set, so that personalized improvements can be made for specific software transactions later.

[0057] In detail, the smart contract template is associated with the trading users of the intellectual property trading platform, so that each trading user's operation on the platform can correspond to a specific smart contract instance, and all trading behaviors of the user on the platform can be accurately recorded and managed. This association ensures that the user's behavioral data can be accurately captured and processed by the smart contract, realizing a close connection between the user and the contract.

[0058] For example, when user A is preparing to sell a patent on the platform, the system will automatically bind user A’s account information to the corresponding smart contract template instance. After that, user A’s operations such as listing, bargaining, and transaction confirmation for the patent will be recorded in this associated contract instance.

[0059] In detail, the transaction rules and transaction terms that define transaction behaviors in the smart contract template set specific norms and constraints for intellectual property transactions. The transaction rules clarify the transaction process and conditions, such as the transaction initiation method, the validity period of the quotation, the transaction confirmation mechanism, etc.; the transaction terms involve the rights and obligations of the two parties to the transaction, such as the time of transfer of intellectual property rights, the scope of use license, the payment method and time node of the transaction price, confidentiality clauses, breach of contract liability, etc.

[0060] For example, in a smart contract for a trademark rights transaction, the transaction rules may stipulate that the buyer must complete the quotation within 48 hours after submitting the purchase intention, and the seller must respond within 24 hours after receiving the quotation. The transaction terms may include that the trademark transfer procedures must be completed by the seller with the assistance of the buyer within 7 working days after the completion of the transaction. If one party breaches the contract, it must pay liquidated damages to the other party in accordance with a certain percentage of the transaction amount. At the same time, both parties must keep confidential the commercial secrets involved during the transaction.

[0061] S2. Record the transaction behavior of the transaction user based on the smart contract.

[0062] In an embodiment of the present invention, recording the transaction behavior of the transaction user based on the smart contract includes:

[0063] When there is a transaction on the intellectual property trading platform, the smart contract verifies the transaction conditions of the transaction behavior generated by the intellectual property trading platform;

[0064] The transaction behavior verified by the transaction conditions is updated to the smart contract.

[0065] In detail, the smart contract pre-sets a series of conditions that comply with the intellectual property transaction norms and platform requirements, such as whether the qualifications of both parties to the transaction are compliant, whether the intellectual property status of the transaction subject is clear (whether there is an infringement dispute, whether it has been authorized to others, etc.), whether the transaction price is within a reasonable range, etc. By verifying these conditions, it is ensured that the transaction behavior recorded in the smart contract is legal and complies with the platform operation rules.

[0066] For example, in a patent transaction scenario, if company A wants to purchase a patent from company B, the smart contract will first verify whether company A has the legal qualifications to engage in transactions in the relevant technical field, and whether the patent sold by company B is valid and not involved in any legal proceedings. If company A does not have the relevant qualifications or there are legal issues with company B's patent, the transaction will not pass the verification.

[0067] In detail, once the transaction behavior passes the previous condition verification, the smart contract, as a reliable and tamper-proof data storage and processing mechanism, will completely record the transaction behavior information that meets the requirements, including the transaction time, participants, and specific content of the transaction (such as detailed information on intellectual property rights, transaction amount, transaction method, etc.). These records not only provide data support for the subsequent process of the current transaction, but also provide basic data for the platform's statistical analysis, reputation evaluation and other functions, which helps to achieve comprehensive management and supervision of intellectual property transactions.

[0068] For example, suppose that Enterprise C successfully sells a software copyright it owns to Enterprise D, and the transaction behavior passes the conditional verification of the smart contract. The smart contract will record the transaction time as October 1, 2023, the transaction parties are Enterprise C and Enterprise D, the detailed information of the software copyright (such as software name, version number, function description, etc.), the transaction amount is 500,000 yuan, and the transaction method is a one-time payment. These records will be securely stored in the smart contract for subsequent query and call at any time.

[0069] S3. Read the multi-dimensional performance information in the transaction behavior according to the preset interface protocol.

[0070] In the embodiment of the present invention, the reading of the multi-dimensional performance information in the transaction behavior according to the preset interface protocol includes:

[0071] Extract key information from the transaction behavior according to the rules in the preset interface protocol to obtain behavior information of the transaction behavior;

[0072] The behavior information is classified to obtain multi-dimensional performance information in the transaction behavior, wherein the multi-dimensional performance information includes: time performance information, scope performance information, quality performance information and quantity performance information.

[0073] In detail, the preset interface protocol stipulates specific rules and methods for filtering out important information from complex transaction behavior data. These rules are formulated based on the characteristics and management needs of intellectual property transactions and aim to accurately obtain data related to the core elements of the transaction.

[0074] For example, in a copyright transaction, the transaction behavior may include a large amount of data such as the communication records of both parties, various operation logs during the contract signing process, etc. According to the interface protocol, key information such as the transaction initiation time, the name of the copyrighted work involved in the transaction, and the identity of both parties to the transaction may be extracted. This information constitutes the behavior information of the copyright transaction behavior.

[0075] Specifically, classifying behavioral information helps to more systematically evaluate the performance of transactions. Time performance information can reflect whether the transaction is carried out on time, such as whether the effective time of copyright authorization and the deadline for payment are in compliance with the agreement; scope performance information involves the scope of the object of the transaction, such as the scope of the use of patent licenses and the geographical scope of trademark use; quality performance information targets the quality standards of intellectual property rights, such as whether the functional integrity and technological advancement of software copyrights meet expectations; quantity performance information focuses on the quantity of transactions, such as the number of intellectual property licenses purchased. Through this classification, each key dimension of the transaction can be monitored comprehensively and meticulously.

[0076] For example, in a trademark licensing transaction, the time performance information may show that the effective date agreed in the licensing contract is May 1, 2023, and the actual effective date is consistent with it, indicating that the time performance is good; the scope performance information shows that the authorized use of the trademark is limited to a certain type of specific products and does not exceed the agreed scope; the quality performance information can be used through market feedback and other channels to determine whether the quality image of the trademark in consumers' cognition is maintained at the expected level; the quantity performance information shows that the number of authorized trademark uses is 10 product categories, which is consistent with the contract agreement. These multi-dimensional performance information comprehensively reflects the performance status of the trademark licensing transaction.

[0077] S4. Generate the performance deviation of the transaction user according to the multi-dimensional performance information and a preset performance deviation generation algorithm.

[0078] In the embodiment of the present invention, the performance deviation generation algorithm is the core part of the entire user behavior monitoring system for accurately quantifying the performance of transaction users.

[0079] In detail, the preset performance deviation generation algorithm is:

[0080]

[0081] in, is the performance deviation of the transaction user, It is the identifier of the fulfillment information type of multi-dimensional fulfillment information. is the total number of fulfillment information types, It belongs to The total number of dimensions of fulfillment information types, It is The first type of fulfillment information The weight of the dimension, It is Dimension identifier of the fulfillment information type, It is Of the fulfillment information types The actual value of the dimension, It is Of the fulfillment information types The expected value of the dimension, is the penalty coefficient.

[0082] In detail, first, for each fulfillment information type (given by logo), we must consider its internal multiple dimensions (by For example, in intellectual property transactions, for the time performance information type, suppose , whose dimensions include contract signing time, delivery time, and payment time, respectively .

[0083] In detail, for each dimension , by calculating the actual value With expected value The absolute value of the difference is multiplied by the weight corresponding to the dimension , which can measure the degree of deviation on this dimension. The setting reflects the relative importance of different dimensions in the overall performance evaluation. For example, in a patent technology transfer transaction, the completeness of technology delivery (a dimension in the quality performance information type) may be slightly more important than the time of delivery, so the weight of the quality dimension will be relatively high.

[0084] In detail, for each fulfillment information type Sum the deviations of all dimensions within , and obtain the overall deviation of this fulfillment information type.

[0085] In detail, all performance information types ( The total deviations of the ) are summed and multiplied by the penalty coefficient ( ), and the final performance deviation is obtained ( ). Penalty coefficient ( ) is to adjust the overall deviation based on the platform’s risk appetite and management strategy to more accurately reflect the impact of users’ performance on the platform.

[0086] In detail, assuming that in a software copyright transaction, the penalty coefficient ( ) is 1.2, there are two types of performance information, namely time performance information and quality compliance information ,Right now .

[0087] Information about time performance , there are two dimensions: delivery time and payment time , assuming that the expected value of the delivery time is October 1, 2023, and the actual value is October 5, 2023; the expected value of the payment time is October 10, 2023, and the actual value is October 12, 2023. And set the weight of the delivery time dimension to 0.4, the weight of the payment time dimension to 0.6, and assume that the daily quantitative value is 1.

[0088] For quality performance information , there are three dimensions: software functional completeness , Software Stability , Software Compatibility . Assume that the expected value of software functional completeness is 90 points (full score 100), and the actual value is 80 points; the expected value of software stability is 85 points, and the actual value is 80 points; the expected value of software compatibility is 90 points, and the actual value is 85 points. And set the weight of software functional completeness dimension to 0.5, the weight of software stability dimension to 0.3, and the weight of software compatibility dimension to 0.2.

[0089] First, calculate the deviation of the time fulfillment information type:

[0090]

[0091] Then, the deviation of the quality compliance information type is calculated:

[0092]

[0093] Finally, calculate the performance deviation :

[0094]

[0095] S5. Obtain the historical reputation score of the transaction user based on the smart contract, and perform user reputation update on the historical reputation score according to the performance deviation and a preset time decay factor to obtain an updated reputation score of the transaction user.

[0096] In the embodiment of the present invention, the step of obtaining the historical reputation score of the transaction user based on the smart contract includes:

[0097] A unique identifier for identifying the transaction user;

[0098] Perform node search on key nodes in the smart contract according to the unique identifier;

[0099] The historical credit score of the transaction user is determined according to the search result of the node search.

[0100] Specifically, in the user behavior monitoring and management system of the intellectual property trading platform, each user needs to have a unique identifier, which is the key information to distinguish different users, similar to the ID number of an individual in society. It can be a user's registered account, a unique user number, or other identifier that can clearly distinguish users. Through this unique identifier, the platform can accurately associate various transaction behaviors, performance information, and reputation data with specific users, ensuring the accuracy and consistency of user information processing.

[0101] For example, in an online patent trading platform, user A is assigned a user ID of "user12345" when registering. This "user12345" is the unique identifier of user A. Regardless of whether user A sells his own patents or buys other people's patents, all information related to user A will be associated and managed through this unique identifier.

[0102] In detail, smart contracts store a large amount of information, which is distributed on different nodes in a structured manner. For a specific user, based on its unique identifier, the system will search for key nodes related to it in the storage structure of the smart contract. These key nodes may contain the user's past transaction records, historical reputation information, and other relevant data. The process of finding key nodes is like locating the exclusive information area belonging to the user based on the user's unique identifier in a huge information network to obtain the required information.

[0103] For example, when the information of user A needs to be found, the system will use the unique identifier "user12345" to search in the network stored in the smart contract. It may look for nodes containing "user12345", which may contain patent transaction records conducted by user A in the past, such as transaction information on the sale of patent X in 2022, transaction information on the purchase of patent Y in 2023, and information nodes such as evaluations and feedback related to these transactions.

[0104] In detail, once the key nodes of a user are found, the historical reputation score of the user can be extracted and determined. This historical reputation score is obtained by evaluating the user's previous transaction behavior and performance. By quantifying the user's past performance on the platform, it can intuitively reflect the user's reputation on the platform, providing an important basis for subsequent transaction decisions, risk assessment, and user classification management.

[0105] For example, after finding the key node of user A, it is found that the historical reputation score contained therein is 85 points (out of 100 points). This 85 points may be the result of comprehensive consideration of factors such as timely delivery of patents, compliance with contract terms, and the quality of the intellectual property provided in previous transactions of user A. For example, user A has been able to deliver relevant documents of patents to buyers on time in previous transactions, and there are no infringement disputes in the patents provided, so it has obtained a high historical reputation score, which shows that user A has a high reputation on the intellectual property trading platform. In future transactions, he may get more trust and convenience, and other users or platforms may be more willing to trade with user A.

[0106] Furthermore, the performance deviation may take a negative value depending on the circumstances.

[0107] In the embodiment of the present invention, the updating of the user reputation of the historical reputation score according to the performance deviation and the preset time decay factor to obtain the updated reputation score of the transaction user includes:

[0108] The historical reputation score is updated according to a preset reputation update algorithm, the performance deviation and a preset time decay factor to obtain a reputation update score for the transaction user, wherein the preset reputation update algorithm is:

[0109]

[0110] in, is the credit update score of the transaction user, is the historical reputation score, is The time decay factor at time, is the performance deviation, is the weight factor of the performance deviation on the reputation score.

[0111] In detail, the reputation update algorithm comprehensively considers the user's historical reputation score, current performance deviation and time decay factor, and calculates the updated reputation score.

[0112] In detail, the historical reputation score reflects the user's comprehensive performance on the platform in the past, and is a long-term cumulative evaluation of the user's reputation. However, as time goes by, the impact of past performance on current reputation will gradually weaken, which is the role of the time decay factor.

[0113] In detail, the performance deviation represents the performance of the user in the current transaction. It is calculated based on the performance deviation generation algorithm mentioned above and reflects the degree of difference between the user's current transaction behavior and expectations. It is multiplied by the weight factor and added to the decay part of the historical reputation score to jointly determine the user's latest reputation status.

[0114] In detail, the existence of the weight factor can adjust the impact of performance deviation on reputation update according to the platform's strategy. For example, if the platform pays more attention to the user's current performance, the value of the weight factor can be set relatively large, otherwise it can be small.

[0115] Assume that user B's historical reputation score on the intellectual property trading platform is 80 points (out of 100 points). In the most recent patent transaction, the performance deviation is calculated to be 10 points, and the platform sets the weight factor of the performance deviation to the reputation score to 0.5.

[0116] Assume that when the transaction occurs, the time identifier is 10 units (the specific unit can be set according to the platform, such as months or years), and the decay rate is 0.1.

[0117] In detail, the time decay factor is:

[0118]

[0119] in, is The time decay factor at time, is the decay rate, It is a time stamp.

[0120] For the case of user B above, substituting t=10 and λ=0.1 into the time decay factor formula yields: .

[0121] Further, .

[0122] In detail, the reputation update mechanism embodies a dynamic and comprehensive reputation evaluation method. It not only takes into account the long-term reputation accumulation of users, but also combines the current performance of fulfillment, and uses the time decay factor to make the historical reputation reasonably affect the current reputation evaluation over time, avoiding the limitation of relying on a single factor for reputation evaluation, making the reputation evaluation more scientific and accurate.

[0123] In detail, on the intellectual property trading platform, this updated reputation score can affect the various rights and treatments of users. For example, if user B's reputation update score drops from 80 points to 55.56 points, it may result in restrictions on some of its advanced functions on the platform, such as not being able to participate in high-value patent transactions, or needing to pay a higher deposit to continue trading, because the decline in its reputation indicates that it has performance deviations in recent transactions, which may bring higher risks to the platform. At the same time, the platform can also use the updated reputation score to show more accurate information to other users, helping them make more informed decisions when choosing trading partners.

[0124] S6. Perform hierarchical management on the transaction users according to the credit update score and the preset responsible person contact map.

[0125] In the embodiment of the present invention, the step of performing hierarchical management on the transaction users according to the reputation update score and the preset responsible person contact map includes:

[0126] Performing reputation grading on the transaction user according to the reputation update score to obtain the reputation level of the transaction user;

[0127] generating a management strategy for the transaction user according to the credit rating and a pre-generated warning threshold;

[0128] Transaction management is performed on the transaction users according to a preset responsible person contact map and the management strategy.

[0129] In detail, the reputation update score is a comprehensive evaluation result of the user's reputation. Grading the user's reputation based on this score helps the platform implement differentiated management strategies for users with different reputation levels. Different reputation levels can represent different levels of trust and reliability of users on the platform. For example, a user with a high reputation level may indicate that the user has consistently performed well in past intellectual property transactions, can abide by transaction rules, and has good performance capabilities; while a user with a low reputation level may have more breaches of contract or bad behaviors. Through reputation grading, the platform can intuitively understand the user's reputation status and provide a basis for subsequent management and transaction decisions.

[0130] In detail, this grading method can be based on preset score segments. For example, 85 to 100 points are classified as Class A credit level, representing high-credit users; 70 to 84 points are classified as Class B, representing medium-credit users; 60 to 69 points are classified as Class C, representing lower-credit users; and less than 60 points are classified as Class D, representing low-credit users, etc.

[0131] For example, after a transaction, user C's credit score is updated to 88 points. According to the platform's credit grading rules, the user will be classified as A-level credit, indicating that the user is a trustworthy trading partner and can enjoy some privileges or conveniences on the platform, such as priority recommendation, lower transaction fees, etc.

[0132] Specifically, the warning threshold is calculated based on the user's historical warning threshold, the change range of the reputation score and the adjustment coefficient. When the user's reputation changes, by adjusting the warning threshold, users who may be at risk can be discovered in a timely manner and corresponding management measures can be taken.

[0133] Specifically, for users with high credit ratings, a more relaxed warning threshold may be set, as they are generally considered to be of lower risk; whereas for users with low credit ratings, the warning threshold may be set more strictly to closely monitor their behavior and prevent them from engaging in possible bad trading behaviors. For example, for users with A-level credit ratings, the warning threshold may be relatively high, allowing for slight credit fluctuations within a certain range without triggering management measures; whereas for users with D-level credit ratings, even minor credit fluctuations may trigger a warning, leading to measures such as restricting transactions and freezing accounts.

[0134] In detail, management strategies may include adjustments to transaction permissions (such as limiting transaction amounts, transaction frequencies, types of intellectual property that can be traded, etc.), the degree of information disclosure (more information may be disclosed to high-credibility users to facilitate their transactions, while information disclosure may be restricted for low-credibility users), and differences in regulatory intensity (more frequent monitoring of low-credibility users).

[0135] In detail, the responsible person contact map defines the relationship and responsibility distribution between different responsible persons and users in the platform. Responsible persons may include customer service personnel, risk management personnel, legal personnel, etc. of the platform, who manage users in a targeted manner according to their credit rating and management strategies.

[0136] Specifically, when actions need to be taken based on the user's reputation level and management strategy, the responsible person can quickly locate his or her responsibilities and the corresponding user through the contact map to ensure that the management actions for the user are timely and effective. For example, for high-reputation users, customer service staff can provide better services, while for low-reputation users, risk management staff may need to pay closer attention to their transaction behavior, and legal staff may need to prepare in advance to deal with potential disputes.

[0137] In detail, assuming that user E is classified as a C-level credit user, according to its management strategy, the risk management personnel of the platform know from the contact map of responsible persons that they need to pay special attention to this user. The risk management personnel will regularly check the transaction records of user E. Once it is found that his transaction behavior is close to or exceeds the warning threshold, corresponding measures will be taken, such as requiring user E to provide more guarantees or temporarily freezing some of his transaction permissions, in order to protect the interests of the platform and other users.

[0138] In detail, the pre-generated warning threshold is:

[0139]

[0140] in, is the pre-generated warning threshold, is the historical warning threshold of the transaction user, is the adjustment factor, is the magnitude of change in the credit score.

[0141] For example, suppose user D's original historical warning threshold is 50, and his credit score drops from 70 to 60. The change in credit score is -10 points. The adjustment coefficient ( ) is 0.1. The new warning threshold is calculated to be 0, which means that after the reputation of user D decreases, his new warning threshold is 0. Once there is any situation that may affect his reputation, the platform will take stricter management measures, such as restricting some of his transaction permissions, because his decline in reputation makes him a high-risk user.

[0142] In the embodiment of the present invention, before performing hierarchical management on the transaction users according to the reputation update score and the preset responsible person contact map, the method further includes:

[0143] Define the person responsible for the intellectual property trading platform;

[0144] Establishing an association model between the responsible person and the transaction user, wherein the association model defines communication paths, division of responsibilities and priority of matters;

[0145] A hierarchical graph structure of the intellectual property trading platform is generated according to the role attributes of the responsible persons and the association model, and a preset responsible person contact graph is determined according to the hierarchical graph structure.

[0146] In detail, the responsible persons are key personnel to ensure the normal operation and transaction management of the platform, and they play an important role in the user classification management process. The responsible persons can include different roles, such as the platform's operation management personnel, customer service personnel, risk assessment personnel, legal personnel, etc. They each bear different responsibilities related to the platform operation and user transactions, ensuring that the platform's intellectual property transactions comply with laws and regulations, the transaction process is smooth, user problems can be solved in a timely manner, and risks are effectively controlled.

[0147] For example, operations managers are responsible for the overall operation of the platform, including formulating the platform's operating rules and policies; customer service staff are responsible for handling user inquiries and complaints; risk assessors are responsible for assessing and monitoring users' transaction risks; and legal personnel ensure that the platform's transactions comply with relevant legal provisions and handle possible legal disputes.

[0148] In detail, the association model is established to clarify how the responsible person interacts with the transaction users during the intellectual property transaction process, as well as how to divide responsibilities and determine the priority of handling matters. The communication path stipulates how the responsible person contacts the user, whether through the platform's internal messaging system, email or phone, etc. The division of responsibilities clarifies which responsible person is responsible for handling which issues in different situations. The priority of matters ensures which issues need to be handled first when multiple matters occur at the same time, so as to ensure the normal operation of the platform and the good experience of users.

[0149] Specifically, there will be different communication paths and division of responsibilities for different types of trading behaviors and user issues. For example, during the trading process, the user's consultation on the trading process may be mainly answered by the customer service staff through the platform's internal messaging system, and the responsibility mainly lies with the customer service staff; while for issues that may involve legal risks, legal personnel need to intervene and will be set as a higher priority, because legal issues may bring serious consequences to the platform.

[0150] For example, when user A sells a software copyright on the platform, there is a dispute over the transaction amount. According to the association model, customer service staff Xiao C will first communicate with user A through the platform's internal messaging system to try to resolve the issue. This is a communication path. If a possible ownership dispute involving software copyright is discovered during the communication process, the responsibility will be transferred to the legal staff lawyer Zhao, because this involves legal risks, which is a reflection of the division of responsibilities. In addition, since the legal issue is more serious, it will be set as a higher priority and needs to be handled first, while other general user inquiries can be handled with a slight delay.

[0151] In detail, the hierarchical graph structure presents the responsible persons and their relationships with users in a hierarchical manner to facilitate management and decision-making. According to the different role attributes of the responsible persons (such as operations, customer service, risk, legal affairs, etc.) and the association model established earlier, a hierarchical graph structure similar to an organizational chart can be constructed. This structure shows the positions and relationships of different responsible persons in the platform, as well as how they are related to users, forming a complete contact graph of responsible persons. It helps the platform to clearly find the corresponding responsible persons and their relationships with users according to the graph when it needs to manage users, and then implement corresponding management strategies.

[0152] In detail, the map may place senior management at the top level, responsible for overall decision-making and coordination; customer service personnel, risk assessors, legal personnel, etc. are distributed at different levels, responsible for affairs in their respective fields, and associated with users through different paths and priorities.

[0153] In detail, in the hierarchical map structure, the senior management of the platform is at the top level, responsible for coordinating the overall situation. The next level is the different business departments, among which the customer service department includes customer service personnel such as Li Customer Service, who are mainly responsible for handling users' daily inquiries and simple disputes; the risk assessment department includes Wang Risk Assessor and others, who are responsible for monitoring users' transaction risks; the legal department includes Zhao Lawyer and others, who are responsible for handling legal affairs. For user A's transactions, according to this hierarchical map structure, when user problems arise, you can clearly see the relationship from customer service personnel to risk assessors and then to legal personnel, as well as the responsibility transfer and processing procedures in different situations, which makes it convenient for the platform to quickly find the corresponding responsible person for processing according to the different situations of users.

[0154] The present invention realizes automatic and real-time recording of transaction user behaviors through the deployment platform of smart contracts, and efficiently reads multi-dimensional performance information in transaction behaviors according to the preset interface protocol. This information covers multiple types and dimensions, providing rich data support for subsequent analysis. By using the preset performance deviation generation algorithm, with the help of penalty factors, combined with different performance information types, the total number of dimensions, the weight of each dimension, and the actual value and expected value, the performance deviation is quickly and accurately calculated, so that the platform can timely detect the user's performance status. At the same time, the user's historical reputation score is obtained with the help of smart contracts, and it is adjusted according to the time decay factor, and then the user's reputation is updated in combination with the performance deviation. Finally, according to the reputation update score and the preset responsible person contact map, the transaction users are accurately graded and managed. This whole set of processes, from information collection, analysis and calculation to management decision-making, makes full use of multi-dimensional performance information, performance deviation, time decay factor, penalty factor, responsible person map and other technical points, which are linked together to realize the efficient operation of user behavior monitoring and significantly improve the efficiency of the intellectual property transaction platform based on smart contracts in user behavior monitoring.

[0155] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0156] In addition, each functional module in each embodiment of the present invention may be integrated into one processing unit, each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0157] It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0158] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence is the theory, method, technology and application device that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0159] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A method for monitoring user behavior of an intellectual property transaction platform based on smart contracts, characterized in that: The method comprises: Deploy smart contracts on the intellectual property trading platform; Record the transaction behavior of transaction users based on the smart contract; Reading the multi-dimensional performance information in the transaction behavior according to a preset interface protocol, wherein the multi-dimensional performance information includes time performance information, scope performance information, quality performance information and quantity performance information; The performance deviation of the transaction user is generated according to the multi-dimensional performance information and a preset performance deviation generation algorithm, wherein the preset performance deviation generation algorithm is: Where ΔP is the performance deviation of the transaction user, s is the identifier of the performance information type of the multi-dimensional performance information, N is the total number of performance information types, and D s is the total number of dimensions belonging to the sth fulfillment information type, w sd is the weight of the dth dimension of the sth fulfillment information type, d is the dimension identifier of the sth fulfillment information type, is the actual value of the dth dimension in the sth fulfillment information type, is the expected value of the dth dimension in the sth performance information type, and C is the penalty coefficient; Based on the smart contract, the historical reputation score of the transaction user is obtained, and the user reputation is updated for the historical reputation score according to the performance deviation and the preset time decay factor to obtain the reputation update score of the transaction user, wherein the time decay factor is h(t)=e -λt , where h(t) is the time decay factor at time t, λ is the decay rate, t is the time identifier, and the reputation update algorithm is: S new =(S old ×(1-h(t)))+(ΔP×α), where S new is the reputation update score of the transaction user, S old is the historical reputation score, ΔP is the performance deviation, and α is the weight factor of the performance deviation on the reputation score; The responsible person of the intellectual property trading platform is defined, and an association model between the responsible person and the trading user is established, wherein the association model defines a communication path, a division of responsibilities, and a priority of matters; a hierarchical graph structure of the intellectual property trading platform is generated according to the role attributes of the responsible person and the association model; a preset responsible person contact graph is determined according to the hierarchical graph structure; and the trading users are hierarchically managed according to the reputation update score and the preset responsible person contact graph, including: generating a pre-generated warning threshold θ according to the reputation update score; new =θ old ×(1+β×ΔS), where θ new is the pre-generated warning threshold, θ old is the historical warning threshold of the transaction user, β is the adjustment coefficient, and ΔS is the change range of the credit score.

2. The method for monitoring user behavior of an intellectual property transaction platform based on a smart contract as claimed in claim 1, characterized in that: The deployment of smart contracts on the intellectual property trading platform includes: Create smart contract templates for intellectual property trading platforms; The smart contract template is associated with the transaction users of the intellectual property transaction platform, and the transaction rules and transaction terms of the transaction behavior are defined in the smart contract template.

3. The method for monitoring user behavior of an intellectual property transaction platform based on a smart contract as claimed in claim 2, characterized in that: The recording of the transaction behavior of the transaction user based on the smart contract includes: When there is a transaction on the intellectual property trading platform, the smart contract verifies the transaction conditions of the transaction behavior generated by the intellectual property trading platform; The transaction behavior verified by the transaction conditions is updated to the smart contract.

4. The method for monitoring user behavior of an intellectual property transaction platform based on a smart contract as claimed in claim 1, characterized in that: The reading of the multi-dimensional performance information in the transaction behavior according to the preset interface protocol includes: Extract key information from the transaction behavior according to the rules in the preset interface protocol to obtain behavior information of the transaction behavior; The behavior information is classified to obtain multi-dimensional performance information in the transaction behavior.

5. The method for monitoring user behavior of an intellectual property transaction platform based on a smart contract as claimed in claim 1, characterized in that: The obtaining of the historical credit score of the transaction user based on the smart contract includes: A unique identifier for identifying the transaction user; Perform node search on key nodes in the smart contract according to the unique identifier; The historical credit score of the transaction user is determined according to the search result of the node search.

6. The method for monitoring user behavior of an intellectual property transaction platform based on a smart contract as claimed in claim 1, characterized in that: The hierarchical management of the transaction users according to the reputation update score and the preset responsible person contact map includes: Performing reputation grading on the transaction user according to the reputation update score to obtain the reputation level of the transaction user; generating a management strategy for the transaction user according to the credit rating and a pre-generated warning threshold; Transaction management is performed on the transaction users according to a preset responsible person contact map and the management strategy.

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