Data value determination method and device, equipment, storage medium and program product

Abstract

The embodiment of the invention provides a data value determination method and device, equipment, a storage medium and a program product, and relates to the field of block chains. The method comprises the steps of obtaining transaction information of target data, determining an evaluation index of the target data according to the transaction information, obtaining an evaluation model related to the evaluation index, and processing the transaction information through the model to obtain the value of the target data. Through the mode, the evaluation index can be re-determined after the target data is accessed or used, and the data value is automatically calculated through the evaluation model, so that accurate evaluation and real-time updating of the data value in the block chain are realized. Besides, the determined data value can be used for further determining an incentive integral value, so that incentive to the user is realized, the activeness of the block chain community is improved, and the development of the block chain is promoted.

Description

Technical Field

[0001] The present application relates to the field of blockchain technology, and in particular to a method, device, equipment, storage medium and program product for determining data value. Background Art

[0002] With the development of blockchain technology, the application scope of blockchain has gradually expanded from cryptocurrency to other fields. Due to the characteristics of blockchain such as immutability, security and reliability, it has broad application prospects in many fields such as finance.

[0003] In order to increase the activity of the blockchain community, points can be used to motivate users to affirm their behavior and achieve the effect of motivating users. This method requires listing user behaviors, then determining the data value corresponding to each behavior, and determining the points for the incentive based on the value.

[0004] However, user behaviors in the blockchain are diverse. The process of listing a large number of user behaviors and judging the data value of each behavior separately is complex and difficult, which makes it difficult to accurately measure the value of data based on user behaviors, hindering the development of the blockchain. Summary of the invention

[0005] The present application provides a data value determination method, device, equipment, storage medium and program product to solve the technical problem that the data value in the blockchain is difficult to determine.

[0006] In a first aspect, the present application provides a method for determining data value, which is applied to blockchain, and the method comprises:

[0007] Acquiring transaction information of target data, wherein the transaction information includes the number of times the target data is accessed and / or used;

[0008] Determining an evaluation index of the target data according to the transaction information;

[0009] Obtaining a corresponding evaluation model according to the evaluation index, wherein the evaluation model is used to calculate the input data according to preset rules to obtain the data value;

[0010] The transaction information is processed by the evaluation model to obtain the value of the target data.

[0011] In a second aspect, the present application provides a data value determination device, which is applied to a blockchain, and the device includes:

[0012] An acquisition module, used to acquire transaction information of target data, wherein the transaction information includes the number of times the target data is accessed and / or used;

[0013] An indicator determination module, used to determine the evaluation indicator of the target data according to the transaction information;

[0014] A model acquisition module, used to acquire a corresponding evaluation model according to the evaluation index, wherein the evaluation model is used to calculate the input data according to preset rules to obtain the data value;

[0015] The value determination module is used to process the transaction information through the evaluation model to obtain the value of the target data.

[0016] In a third aspect, the present application provides an electronic device, comprising: a processor, and a memory communicatively connected to the processor;

[0017] The memory stores computer-executable instructions;

[0018] The processor executes the computer-executable instructions stored in the memory to implement the data value determination method as described in any one of the first aspects.

[0019] In a fourth aspect, the present application provides a computer-readable storage medium, comprising: the computer-readable storage medium stores computer execution instructions, and the computer execution instructions, when executed by a processor, are used to implement the data value determination method as described in any one of the first aspects.

[0020] In a fifth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the data value determination method as described in any one of the first aspects.

[0021] The data value determination method, device, equipment, storage medium and program product provided by the present application can obtain the transaction information of the target data, determine the evaluation index of the target data according to the transaction information, and obtain the evaluation model related to the evaluation index, and then process the transaction information through the model to obtain the value of the target data. In this way, the evaluation index can be re-determined after the target data is accessed or used, and the data value can be automatically calculated through the evaluation model, so as to achieve accurate evaluation and real-time update of the data value in the blockchain. In addition, the determined data value can be used to further determine the incentive point value to achieve incentives for users, which will help to increase the activity of the blockchain community and promote the development of blockchain. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0023] Figure 1 A schematic diagram of an application scenario provided for an embodiment of the present application;

[0024] Figure 2 A flowchart of a method for determining data value provided in an embodiment of the present application;

[0025] Figure 3 A schematic diagram of a process for determining an evaluation index provided in an embodiment of the present application;

[0026] Figure 4 A schematic diagram of a flow chart of a model processing process provided in an embodiment of the present application;

[0027] Figure 5 A flowchart of another model processing process provided in an embodiment of the present application;

[0028] Figure 6 A schematic diagram of the structure of a data value determination device provided in an embodiment of the present application;

[0029] Figure 7 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0030] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0031] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0032] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of the relevant data comply with the relevant laws, regulations and standards of the relevant countries and regions, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0033] In addition, this application involves conducting big data analysis of user information (including but not limited to personal biometrics, identity data, consumption data, asset data, electronic terminal operation data, etc.), and using artificial intelligence technology to make automated decisions, and making technical solutions that have a significant impact on personal rights and interests based on the results of automated decisions. The application provides users with corresponding operation entrances for them to choose to agree or reject the results of automated decisions; if the user chooses to reject, the expert decision-making process will be entered.

[0034] It should be noted that the data value determination method, device, equipment, storage medium and program product provided in this application can be used in the blockchain field, and can also be used in any field other than blockchain. The application field of the data value determination method, device, equipment, storage medium and program product in this application is not limited.

[0035] In this application, it should be understood that the terms involved have the following meanings:

[0036] Blockchain: Blockchain is a distributed database accounting system that encrypts and hashes data and data operation records through cryptographic methods, thereby forming an open, transparent, tamper-proof, and traceable technology. This technology can be widely used in payment and settlement, evidence storage and collection, value transfer, supply chain finance, user credit, regulatory auditing, etc. Blockchain records all transaction records since the genesis block. When the block size reaches a certain level, historical transaction records will not be tampered with.

[0037] Smart Contract: A smart contract is a computer protocol designed to communicate, verify or execute contracts in an information-based manner. Smart contracts have the advantages of decentralization, verifiability, security and transparency. It allows for trusted transactions without a third party, which are traceable and irreversible. The purpose of smart contracts is to provide a security method that is superior to traditional contracts and reduce other transaction costs associated with contracts.

[0038] The blockchain points mechanism is a points system based on blockchain technology, which has the advantages of decentralization, transparency, security and traceability. This mechanism can solve the problems existing in the traditional e-commerce consumer points system and improve the freedom of use and supervision of points.

[0039] Using points to motivate users and affirm their behavior can achieve the effect of motivating users and increasing the activity of the blockchain community. The point value for setting incentives must be reasonable, which requires listing a large number of user behaviors, judging the data value corresponding to each behavior, and determining the incentive point value based on the data value.

[0040] Figure 1 A schematic diagram of an application scenario provided by an embodiment of the present application. Figure 1As shown in the figure, the blockchain can include several nodes such as A1, A2, A3, ..., An, etc. Nodes (data providers) can provide data, and data is valuable only when it can be used by other nodes (data demanders). The object of value evaluation is the data in the blockchain, which is the account data. It is more reasonable to determine the points value used to motivate users based on the value of the data. However, the relationship between user behavior and data value is more complicated, and it is difficult to accurately measure the value of data.

[0041] The inventors have found through research that the reasons for the above problems are that, first, the value of the data provided by the data provider is difficult to measure, and second, the impact of user behavior (such as the use of data by the data demander) on the data is difficult to determine, and user behavior may cause the value of the data to increase. The inventors therefore thought that for the target data whose value needs to be determined, the number of times it is accessed and used by other nodes can be obtained, and the evaluation indicators can be determined based on the source IP and time of the access and use, and then the value of the data can be calculated based on the evaluation model related to these indicators. In this way, the data value can be updated in real time by monitoring the number of times the data is accessed and used. The updated data value can be made public in the blockchain or used to calculate the integral value for incentives, etc., so that not only the value of the data can be accurately measured, but also it can be used to determine the integral value and incentivize user behavior, thereby promoting the development of blockchain.

[0042] The data value determination method, device, equipment, storage medium and program product provided in this application are intended to solve the above technical problems in the prior art.

[0043] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0044] Figure 2 A flow chart of a method for determining data value provided in an embodiment of the present application. Figure 2 As shown, the method includes:

[0045] Step S201, obtaining transaction information of target data.

[0046] The transaction information includes the number of times the target data is accessed and / or used.

[0047] The data value determination method provided in the embodiment of the present application can be applied to a blockchain, which may include multiple nodes. The user, data provider, and data demander mentioned in the embodiment of the present application may refer to the nodes of the blockchain.

[0048] Step S202: determining evaluation indicators of target data according to transaction information.

[0049] Among them, the evaluation indicators may include the IP (Internet Protocol Address) of the data demander, access time, etc.

[0050] For example, it is possible to determine whether the target data has been accessed multiple times by the same IP based on the access records of the target data. If so, it can be considered that the IP has a greater impact on the value of the data, and the access source IP can be used as an evaluation indicator of the target data.

[0051] For example, based on the access and use of the target data, if it can be determined that other nodes' access and use of the target data have a relatively obvious regularity in time distribution, the access time can be used as an evaluation indicator of the target data.

[0052] Step S203, obtaining a corresponding evaluation model according to the evaluation index.

[0053] Among them, the evaluation model is used to calculate the input data according to preset rules to obtain the data value.

[0054] For example, evaluation rules and calculation formulas can be designed in advance based on various indicators and combinations of various indicators, and the evaluation rules and formulas can be converted into a model form to obtain a corresponding evaluation model. For example, the access source IP and access time can be selected as evaluation indicators at the same time, and a formula can be designed considering the source IP and access time to calculate the number of times the target data is accessed.

[0055] Step S204, the transaction information is processed through the evaluation model to obtain the value of the target data.

[0056] Exemplarily, based on the transaction information, it can be determined that the target data has been accessed 100 times in total, of which the first 80 times are concentrated in the same hour of the same day. The evaluation index of the target data may include the access time, and the evaluation model may include two formulas. The first formula is used to calculate the first 80 visits, and the second formula is used to calculate the next 20 visits. The sum of the calculation results of the two formulas is then added as the value of the target data.

[0057] In some possible implementations, after obtaining the value of the target data, the following steps are also included:

[0058] The incentive point value is determined according to the value of the target data; and points incentives are provided to the data provider and / or data demander of the target data according to the incentive point value.

[0059] It should be noted that after determining the value of the data, the points used for incentives can be determined based on the data value. The points can not only be used to reward data providers, but also can be converted according to a certain ratio and rewarded to data demanders, thereby achieving incentives for both parties of data transactions in the blockchain. The data value of the data is updated in real time to increase the sharing enthusiasm of data holders and data demanders.

[0060] The data value determination method provided in this embodiment can obtain the transaction information of the target data, determine the evaluation index of the target data based on the transaction information, and obtain the evaluation model related to the evaluation index, and then process the transaction information through the model to obtain the value of the target data. In this way, the evaluation index can be re-determined after the target data is accessed or used, and the data value can be automatically calculated through the evaluation model, thereby realizing accurate evaluation and real-time update of the data value in the blockchain. In addition, the determined data value can be used to further determine the incentive point value to achieve incentives for users, which helps to improve the activity of the blockchain community and promote the development of blockchain.

[0061] In one embodiment, obtaining transaction information of target data includes:

[0062] Obtain target data in the blockchain; call the preset target smart contract to query the number of times the target data has been accessed and / or used.

[0063] Among them, the target smart contract is the system smart contract of the blockchain.

[0064] Specifically, a system smart contract can be pre-written and deployed to the blockchain, and the system smart contract can be used to read the situations in which data in the blockchain is accessed and used.

[0065] In the blockchain, user behavior may trigger corresponding business smart contracts through the business system. The business smart contracts will access and use the data in the blockchain. The data link can be expressed as: business system → business smart contract → blockchain.

[0066] In the embodiment of the present application, a system smart contract can be deployed to record the situation where a business smart contract calls data in the blockchain, and its data link can be expressed as: business system → business smart contract → system smart contract → blockchain.

[0067] Business smart contracts may be different, but system smart contracts can be shared in the blockchain. In this way, system smart contracts suitable for different scenarios can be obtained to record the access and use of target data. These records can be obtained quickly and accurately by calling system smart contracts.

[0068] In one embodiment, Figure 3As shown, the evaluation indicators of the target data are determined according to the transaction information, including:

[0069] Step S301, obtaining data call records of the data demander for target data.

[0070] Among them, the data demander is the blockchain node that accesses and / or uses the target data.

[0071] Exemplarily, information such as the access time of the data demander to the target data and the IP address of the data demander accessing the target data can be obtained by calling a system smart contract or the like.

[0072] For example, A initiates a transfer of 100 resource value to B, then the business smart contract transaction parameter input is a key-value pair set {A, -100; B, +100}, and the invoke method is called. The public communication area includes the transaction initiator's source IP, transaction channel, transaction timestamp, etc. The business smart contract asynchronously calls the system smart contract, and its input is the same as that of calling the system smart contract, but the system smart contract can record the call locally, call the evaluation model and calculate the data value.

[0073] Step S302, determining whether there is any abnormality in the transaction information according to the data call information.

[0074] In some possible implementations, the data call record includes the network protocol address of the data demander, and determining whether the transaction information is abnormal based on the data call record includes:

[0075] Determine, based on the transaction information, whether there is a situation where the number of times the same network protocol address accesses and / or uses the target data exceeds a first threshold; if so, determine that there is an abnormality in the transaction information.

[0076] In some other possible implementations, the data call record includes time information when the data demander accesses and / or uses the target data, and determining whether the transaction information is abnormal based on the data call record includes:

[0077] Determine whether the number of times the target data is accessed and / or used exceeds a second threshold value within a preset period of time according to the transaction information and time information; if so, determine that the transaction information is abnormal.

[0078] Step S303: If there is an anomaly, determine the evaluation index of the target data according to the type of anomaly.

[0079] Specifically, the abnormality judgment conditions can be pre-set according to factors such as the access source IP and the access time. If the situation in which the target data is called meets the abnormal conditions, it is confirmed that there is an abnormality, and the type of abnormality can be further determined.

[0080] The source IP may represent the IP address of the data demander who accesses or uses the target data.

[0081] For example, if different source IPs add, delete, modify, and check the same transaction multiple times in a short period of time, it can be confirmed that there is an anomaly in the target data involved in the transaction, and the anomaly type is an access time anomaly.

[0082] For example, if the same source IP adds, deletes, modifies, or checks the same transaction multiple times in a short period of time, it can be confirmed that there is an anomaly in the target data involved in the transaction, and the anomaly type is IP anomaly.

[0083] In the blockchain, there may be some abnormal or illegal behaviors, which may include using the same IP to use a large amount of certain data in a short period of time. These behaviors cannot reflect the actual usage of the data, but may be used to calculate the value of the data, resulting in inaccurate data value.

[0084] In the above embodiment, by setting abnormal judgment conditions according to factors such as the access source IP or access time, target data that may have abnormal behavior can be screened out in advance, and corresponding evaluation indicators can be determined so that the corresponding evaluation model can be used for calculation. The model can be designed to avoid abnormal behavior in advance, thereby playing a role in resisting abnormal behavior and reflecting the actual usage of data.

[0085] In one embodiment, the evaluation index includes the network protocol address of the data demander and the time information of the data demander accessing and / or using the target data, such as Figure 4 As shown, the transaction information is processed through the evaluation model, including:

[0086] Step S401, mapping the network protocol address to a first positive constant variable.

[0087] Step S402: Map the time information into a second positive constant variable.

[0088] Step S403, calculating the first normal number variable, the second normal number variable and the transaction information using a preset first formula.

[0089] In the first formula, the number of times the target data is accessed and / or used by the data demander within a preset time period is logarithmically related to the first normal constant variable.

[0090] For example, the evaluation model can calculate the value of the data by formula based on the transaction behaviors such as access and use of the target data, and the parameters of the formula can be derived from the constant variables after the evaluation index is converted. For example, the first formula can be expressed as the following formula (1).

[0091] (1)

[0092] For example, the input source IP is mapped to a positive constant variable X1 (0 < X1 < 1), the trading time can be accurately mapped to a positive constant variable X2 (0 < X2 < 1) after seconds, t is the number of accesses, and the output is the variable Y, where Y can represent the value of the data.

[0093] In formula (1), the number of accesses to data at a certain time has a logarithmic relationship with the source IP, that is, at the same time for the same IP, the greater the number of accesses, the lower the data value.

[0094] In one embodiment, the evaluation index further includes the trading channel of the target data, such as Figure 5 As shown, processing the transaction information through the evaluation model includes:

[0095] Step S501, mapping the trading channel to a third positive constant variable.

[0096] Step S502, calculating the first positive constant variable, the second positive constant variable, the third positive constant variable and the transaction information through a preset second formula.

[0097] Wherein, in the second formula, the number of times the target data is accessed and / or used by the data requester within a preset time period has a logarithmic relationship with the first positive constant variable and the third positive constant variable.

[0098] Exemplarily, the second formula can be expressed as the following formula (2).

[0099] (2)

[0100] For example, the input source IP is mapped to a positive constant variable X1 (0 < X1 < 1 / 2), the trading channel can be mapped to a positive constant variable X3 (0 < X3 < 1 / 2), the trading time can be accurately mapped to a positive constant variable X2 (0 < X2 < 1) after seconds, t is the number of accesses, and the output is the variable Y, where Y can represent the value of the data.

[0101] In formula (2), the number of accesses to data at a certain time has a logarithmic relationship with the source IP and the trading channel, that is, at the same time for the same IP, the greater the number of accesses, the lower the data value, and the data value in a single transaction at a specific time point is completely equivalent. The mapping of the source IP and the trading channel to constant variables follows the idempotency property, that is, the same value is always mapped to the same constant.

[0102] Through the above method, based on the smart contract for reading the accessed and used data and the data value evaluation model for obtaining the data value according to the accessed and used situation of the data, it is possible to measure the value of the data generated based on user behavior, so that for the same behavior of different users, the value can be measured separately, and the data value brought by the user behavior of different users can be evaluated more accurately.

[0103] In some possible implementations, the evaluation indicators corresponding to different evaluation models may be different, and the input parameters of the formula used in the evaluation model may not be limited to the source IP and transaction channel, and may be adjusted dynamically. It should be noted that when the number of input parameters increases, the range of their values ​​is adjusted accordingly. For example, if the input parameter increases the source physical Mac address, the source physical Mac address can be mapped to the fourth normal constant variable X4, and the value ranges of the input parameters X1, X2, and X4 are 0<X<1 / 3, that is, 0<X1+X2+X4<1.

[0104] The above embodiment can be used to incentivize user behavior based on the latest data value for a single data access to target data, and to give users long-term point incentives based on a single user behavior, thereby increasing user activity and enthusiasm.

[0105] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily required by the present application.

[0106] It should be further noted that, although the various steps in the flowchart are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowchart may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these sub-steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0107] Figure 6 A schematic diagram of a data value determination device provided in an embodiment of the present application is shown in FIG. Figure 6 As shown, the data value determination device 600 includes:

[0108] The acquisition module 601 is used to acquire transaction information of target data, where the transaction information includes the number of times the target data is accessed and / or used.

[0109] The indicator determination module 602 is used to determine the evaluation indicator of the target data according to the transaction information.

[0110] The model acquisition module 603 is used to acquire a corresponding evaluation model according to the evaluation index, and the evaluation model is used to calculate the input data according to preset rules to obtain the data value.

[0111] The value determination module 604 is used to process the transaction information through the evaluation model to obtain the value of the target data.

[0112] In one embodiment, the indicator determination module 602 can also be used to: obtain the data call record of the data demander for the target data, where the data demander is a blockchain node that accesses and / or uses the target data; determine whether there is an abnormality in the transaction information based on the data call information; if so, determine the evaluation indicator of the target data based on the type of the abnormality.

[0113] In one embodiment, the indicator determination module 602 can also be used to: determine based on the transaction information whether the same network protocol address accesses and / or uses the target data more than a first threshold number of times; if so, determine that the transaction information is abnormal.

[0114] In one embodiment, the indicator determination module 602 can also be used to: determine whether the number of times the target data is accessed and / or used within a preset period exceeds a second threshold based on the transaction information and the time information; if so, determine that there is an abnormality in the transaction information.

[0115] In one embodiment, the value determination module 604 can also be used to: map the network protocol address into a first normal number variable; map the time information into a second normal number variable; calculate the first normal number variable, the second normal number variable and the transaction information through a preset first formula, wherein the number of times the target data is accessed and / or used by the data demander within a preset time period in the first formula is logarithmically related to the first normal number variable.

[0116] In one embodiment, the value determination module 604 can also be used to: map the transaction channel into a third normal number variable; calculate the first normal number variable, the second normal number variable, the third normal number variable and the transaction information through a preset second formula, wherein the number of times the target data is accessed and / or used by the data demander within a preset time period in the second formula is in a logarithmic relationship with the first normal number variable and the third normal number variable.

[0117] In one embodiment, the acquisition module 601 can also be used to: obtain the target data in the blockchain; call a preset target smart contract to query the number of times the target data is accessed and / or used, and the target smart contract is a system smart contract of the blockchain.

[0118] In one embodiment, the value determination module 604 may also be used to: determine an incentive point value according to the value of the target data; and provide point incentives to the data provider and / or data demander of the target data according to the incentive point value.

[0119] The data value determination device provided in this embodiment is used to execute the technical solution in any of the aforementioned method embodiments. Its implementation principle and technical effects are similar and will not be repeated here.

[0120] It should be understood that the above-mentioned device embodiments are only illustrative, and the device of the present application can also be implemented in other ways. For example, the division of units / modules in the above-mentioned embodiments is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units, modules or components can be combined, or can be integrated into another system, or some features can be ignored or not executed.

[0121] In addition, unless otherwise specified, each functional unit / module in each embodiment of the present application may be integrated into one unit / module, each unit / module may exist physically separately, or two or more units / modules may be integrated together. The above-mentioned integrated unit / module may be implemented in the form of hardware or in the form of a software program module.

[0122] Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 7 As shown, the electronic device 70 includes:

[0123] Processor 71, memory 72, and communication interface 73;

[0124] The memory 72 is used to store executable instructions of the processor 71; the executable instructions may be computer-executable instructions;

[0125] The processor 71 is configured to execute the technical solution in any of the aforementioned method embodiments by executing the executable instructions.

[0126] Optionally, the memory 72 can be independent or integrated with the processor 71.

[0127] Optionally, when the memory 72 is a device independent of the processor 71, the electronic device 70 may further include:

[0128] The bus 74 , the memory 72 and the communication interface 73 are connected to the processor 71 via the bus 74 and communicate with each other. The communication interface 73 is used to communicate with other devices.

[0129] Optionally, the communication interface 73 may be implemented by a transceiver. The communication interface is used to implement communication between the database access device and other devices (such as a client, a read-write library, and a read-only library). The memory may include a random access memory (RAM) and may also include a non-volatile memory (non-volatile memory), such as at least one disk storage.

[0130] The bus 74 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one line is used in the figure, but it does not mean that there is only one bus or one type of bus.

[0131] The above-mentioned processor can be a general-purpose processor, including a central processing unit CPU, a network processor (NP), etc.; it can also be a digital signal processor DSP, an application-specific integrated circuit ASIC, a field programmable gate array FPGA or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0132] The electronic device is used to execute the technical solution in any of the aforementioned method embodiments, and its implementation principle and technical effect are similar and will not be repeated here.

[0133] An embodiment of the present application also provides a readable storage medium, which may be a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the technical solution provided by any of the aforementioned method embodiments is implemented.

[0134] An embodiment of the present application also provides a computer program product, including a computer program, which is used to implement the technical solution provided by any of the aforementioned method embodiments when executed by a processor.

[0135] If the integrated unit / module is implemented in the form of a software program module and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a memory, including a number of instructions to enable a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or CD-ROM and other media that can store program codes.

[0136] In the above embodiments, the description of each embodiment has its own emphasis. For the part not described in detail in a certain embodiment, please refer to the relevant description of other embodiments. The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, all possible combinations of the technical features in the above embodiments are not described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0137] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. The present application is intended to cover any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary techniques in the art that are not disclosed in the present application. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present application are indicated by the following claims.

[0138] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A method for determining data value, characterized in that: Applied to blockchain, the method includes: Acquiring transaction information of target data, wherein the transaction information includes the number of times the target data is accessed and / or used; Determining an evaluation index of the target data according to the transaction information; Obtaining a corresponding evaluation model according to the evaluation index, wherein the evaluation model is used to calculate the input data according to preset rules to obtain the data value; The transaction information is processed by the evaluation model to obtain the value of the target data.

2. The method according to claim 1, characterized in that The step of determining the evaluation index of the target data according to the transaction information includes: Obtaining a data call record for the target data by a data demander, where the data demander is a blockchain node that accesses and / or uses the target data; Determining whether the transaction information is abnormal according to the data call information; If so, the evaluation index of the target data is determined according to the type of the anomaly.

3. The method according to claim 2, characterized in that The data call record includes the network protocol address of the data demander, and determining whether the transaction information is abnormal according to the data call record includes: Determining, based on the transaction information, whether there is a situation where the number of times the same network protocol address accesses and / or uses the target data exceeds a first threshold; If so, it is determined that there is an abnormality in the transaction information.

4. The method according to claim 2, characterized in that: The data call record includes time information of the data demander accessing and / or using the target data, and determining whether the transaction information is abnormal according to the data call record includes: determining, according to the transaction information and the time information, whether the number of times the target data is accessed and / or used within a preset period exceeds a second threshold; If so, it is determined that there is an abnormality in the transaction information.

5. The method according to claim 2, characterized in that: The evaluation index includes the network protocol address of the data demander and the time information of the data demander accessing and / or using the target data. The processing of the transaction information by the evaluation model includes: Mapping the network protocol address to a first positive constant variable; Mapping the time information into a second positive constant variable; The first normal number variable, the second normal number variable and the transaction information are calculated using a preset first formula, wherein the number of times the target data in the first formula is accessed and / or used by the data demander within a preset time period is logarithmically related to the first normal number variable.

6. The method according to claim 5, characterized in that The evaluation index also includes the transaction channel of the target data, and the processing of the transaction information by the evaluation model includes: Mapping the transaction channel to a third positive constant variable; The first normal number variable, the second normal number variable, the third normal number variable and the transaction information are calculated by a preset second formula, and the number of times the target data is accessed and / or used by the data demander within a preset time period in the second formula is in a logarithmic relationship with the first normal number variable and the third normal number variable.

7. The method according to any one of claims 1 to 6, characterized in that: The acquiring of transaction information of target data includes: Obtaining target data in the blockchain; A preset target smart contract is called to query the number of times the target data is accessed and / or used, and the target smart contract is a system smart contract of the blockchain.

8. The method according to any one of claims 1 to 6, characterized in that: After obtaining the value of the target data, it also includes: Determining an incentive point value according to the value of the target data; Point incentives are provided to the data provider and / or data demander of the target data according to the incentive point value.

9. A data value determination device, characterized in that: Applied to blockchain, the device comprises: An acquisition module, used to acquire transaction information of target data, wherein the transaction information includes the number of times the target data is accessed and / or used; An indicator determination module, used to determine the evaluation indicator of the target data according to the transaction information; A model acquisition module, used to acquire a corresponding evaluation model according to the evaluation index, wherein the evaluation model is used to calculate the input data according to preset rules to obtain the data value; The value determination module is used to process the transaction information through the evaluation model to obtain the value of the target data.

10. An electronic device, characterized in that: include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 8 when executed by a processor.

12. A computer program product, characterized in that The invention comprises a computer program, which implements the method according to any one of claims 1 to 8 when being executed by a processor.

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