Block chain data processing method and device, equipment and storage medium

Abstract

The embodiment of the invention provides a block chain data processing method and device, equipment and a storage medium. The method comprises the following steps: receiving a transaction request of multimedia data published in a media platform by first equipment for second equipment; according to media attribute information carried by the transaction request, behavior operation data about the multimedia data and first object attribute information of an object corresponding to the second equipment are acquired from the block chain; predicting the asset value of the multimedia data according to the behavior operation data and the first object attribute information; and according to the transaction request and the asset value of the multimedia data, transferring digital assets from the account address corresponding to the first device to the account address corresponding to the second device, generating an update digital certificate of the multimedia data, and storing the update digital certificate to the block chain. According to the method, the reasonable asset value of the multimedia data can be provided, the economic loss of a purchaser of the multimedia data is avoided, and the transaction security of the multimedia data is improved.

Description

Technical Field

[0001] This application relates to the field of computer technology, and in particular, to a blockchain data processing method, apparatus, device, and storage medium. Background Art

[0002] With the rapid development of multimedia data processing technology, multimedia data (such as images, videos) has increasingly become an inseparable part of people's work and study. Multimedia data can not only bring beauty or useful information to users, but also bring economic value to users of multimedia data. For example, users can trade multimedia data to obtain corresponding digital assets. However, in the process of trading multimedia data, there are abnormal situations such as users maliciously inflating the asset value of multimedia data, which brings economic losses to the purchasers of multimedia data, resulting in relatively low transaction security of multimedia data. Summary of the Invention

[0003] Embodiments of this application provide a blockchain data processing method, apparatus, device, and storage medium, which can provide a reasonable asset value for multimedia data, avoid economic losses of purchasers of multimedia data, and thus improve the transaction security of multimedia data.

[0004] On the one hand, an embodiment of this application provides a blockchain data processing method, including:

[0005] Receiving a transaction request from a first device for multimedia data published by a second device on a media platform; the transaction request carries media attribute information of the multimedia data;

[0006] According to the media attribute information carried in the transaction request, obtaining behavior operation data about the multimedia data and first object attribute information of an object corresponding to the second device from the blockchain;

[0007] Predicting the asset value of the multimedia data according to the behavior operation data and the first object attribute information;

[0008] Transferring digital assets from an account address corresponding to the first device to an account address corresponding to the second device according to the transaction request and the asset value of the multimedia data, generating an updated digital certificate for the multimedia data, and storing the updated digital certificate on the blockchain; the updated digital certificate is used to indicate that the multimedia data belongs to an object corresponding to the first device.

[0009] On the one hand, an embodiment of this application provides a blockchain data processing apparatus, including:

[0010] A receiving module, configured to receive a transaction request of the first device for the multimedia data published by the second device on the media platform; the transaction request carries the media attribute information of the multimedia data.

[0011] An obtaining module, configured to obtain, according to the media attribute information carried in the transaction request, the behavior operation data of the multimedia data and the first object attribute information of the object corresponding to the second device from the blockchain.

[0012] A prediction module, configured to predict the asset value of the multimedia data according to the behavior operation data and the first object attribute information.

[0013] A transfer module, configured to transfer digital assets from the account address corresponding to the first device to the account address corresponding to the second device according to the transaction request and the asset value of the multimedia data, generate an updated digital certificate of the multimedia data, and store the updated digital certificate on the blockchain; the updated digital certificate is used to indicate that the multimedia data belongs to the object corresponding to the first device.

[0014] An embodiment of the present application provides a computer device on the one hand, including a memory and a processor, where the memory stores a computer program, and when the processor executes the computer program, the steps of the above method are implemented.

[0015] An embodiment of the present application provides a computer storage medium on the one hand. The computer storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above method are executed. In the present application, by pre-storing the behavior operation data of the multimedia data and the first object attribute information of the owner of the multimedia data (that is, the object corresponding to the second device) on the blockchain, that is, the behavior operation data and the first object attribute information have authenticity and non-tamperability. Therefore, when the first device needs to purchase the multimedia data published by the second device on the multimedia platform, by predicting the asset value of the multimedia data according to the behavior operation data and the first object attribute information on the blockchain, it is beneficial to improve the accuracy of the asset value of the multimedia data, avoid users from maliciously inflating the asset value of the multimedia data, and improve the transaction security of the multimedia data. Further, according to the transaction request and the asset value of the multimedia data, transfer digital assets from the account address corresponding to the first device to the account address corresponding to the second device, generate an updated digital certificate of the multimedia data, and store the updated digital certificate on the blockchain. The updated digital certificate is used to indicate that the multimedia data belongs to the object corresponding to the first device. By generating the updated digital certificate, it is beneficial for the object corresponding to the first device to trade the multimedia data again and is beneficial to realizing the traceability of the multimedia data. Description of the Drawings

[0016] To more clearly illustrate the technical solutions in the embodiments of the present application or the background art, the accompanying drawings required for use in the embodiments of the present application or the background art will be described below.

[0017] Figure 1 Schematic diagram of the structure of a blockchain data processing system provided by the present application;

[0018] Figure 2 Schematic diagram of the interaction scenario between various devices of a blockchain data processing system provided by the present application;

[0019] Figure 3 Schematic diagram of the process of a blockchain data processing method provided by the present application;

[0020] Figure 4 Schematic diagram of the process of another blockchain data processing method provided by the present application;

[0021] Figure 5 Schematic diagram of the structure of a blockchain data processing device provided by the present application;

[0022] Figure 6 Schematic diagram of the structure of a computer device provided by the present application. Detailed implementation manners

[0023] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art without making creative efforts belong to the scope of protection of the present application.

[0024] First, the blockchain data processing system applied in the present application will be introduced. Please refer to Figure 1 , Figure 1 Schematic diagram of the structure of a blockchain data processing system provided by an embodiment of the present application. The blockchain data processing system may include a blockchain network and one or more terminals. The present application does not limit the number of terminals, and the number of terminals may be set according to requirements. Figure 1 In

[0025] Among them, a multimedia platform can be installed in each of the terminals 111, 112, and 113. The multimedia platform can be used to publish, purchase, and sell multimedia data, and can also be used for users to perform operations such as clicking, viewing, collecting, and commenting on multimedia data. For example, the terminal 111 can publish multimedia data A in the multimedia platform. When there is a social relationship between the object corresponding to the terminal 112 and the object corresponding to the terminal 111, the terminal 112 can display the multimedia data A through the multimedia platform, and in response to a transaction request for the multimedia data A, generate a transaction request for the multimedia data A, and send the transaction request for the multimedia data to the node device in the blockchain network. The node device is used to execute the transaction request to complete the transaction of the multimedia data A. It should be noted that the multimedia data can refer to at least one of image data, video data, audio data, text data, etc., and the multimedia platform can refer to an audio and video player, a content publishing application, a short video application, a live broadcast application, etc.

[0026] It should be noted that the social relationship can refer to a colleague relationship, a friend relationship, a relative relationship, a follow relationship, etc. The follow relationship can refer to that two objects jointly follow the theme corresponding to the same multimedia data, or that two objects belong to the same communication group, etc.

[0027] Among them, the blockchain network is an end-to-end decentralized network jointly composed of multiple node devices (which can also be called blockchain nodes). The number of node devices in the blockchain network can be deployed according to actual needs, and this application does not limit the number of node devices; for Figure 1 example, it is illustrated by taking that there are 4 node devices in the blockchain network. The 4 node devices are respectively the node device 101, the node device 102, the node device 103, and the node device 104.

[0028] It can be understood that the functions involved in each node device in the blockchain network include:

[0029] 1) Routing, which is a basic function of the node device and is used to support communication between node devices.

[0030] For example, as Figure 1 shown, data or blocks can be transmitted between node devices through network connections. The above-mentioned network connection between node devices can perform data transmission based on node identifiers. Each node device has its corresponding node identifier, and each of the above-mentioned node devices can store the node identifiers of other node devices that are connected to itself, so as to broadcast the obtained data or generated blocks to other node devices according to the node identifiers of other node devices in the future. For example, the node device 101 can maintain a node identifier list, and this node identifier list stores the node names and node identifiers of other node devices, as shown in Table 1:

[0031] Table 1

[0032] Node Name Node Identifier Node Device 101 117.xxx.xxx.174 Node Device 102 117.xxx.xxx.145 Node Device 103 117.xxx.xxx.183 Node Device 104 117.xxx.xxx.125 … …

[0033] Among them, the node identifier can be the protocol for interconnection between networks (Internet Protocol, IP) address and any other information that can be used to identify the node device in the blockchain network. Only the IP address is taken as an example in Table 1 for illustration.

[0034] Assume that the node identifier of node device 101 is 117.xxx.xxx.174. Then, node device 101 can send a data synchronization request to node device 102 through 117.xxx.xxx.174, and node device 102 can know that this data synchronization request is sent by node device 101 through the node identifier 117.xxx.xxx.174. Similarly, node device 102 can send transaction data A to node device 101 through the node identifier 117.xxx.xxx.145, and node device 101 can know that this transaction data A is sent by node device 102 through the node identifier 117.xxx.xxx.145. The data transmission between other node devices is also like this, so it will not be elaborated one by one.

[0035] 2) An application, which is used to be deployed in the blockchain, implements specific services according to actual business requirements, records the data related to the implemented functions to form record data, carries a digital signature in the record data to indicate the source of the task data, and sends the record data to other node devices in the blockchain network for other node devices to add the record data to the temporary block when the verification of the record data source and integrity is successful.

[0036] For example, the services implemented by the application include:

[0037] 2.1) Resource management service. The node device can include a resource client, which can be used to implement the resource management service function and realize the communication connection with the decentralized application client based on this resource management service function. The resource client is a tool for managing and storing user digital resources. For example, digital resources can be transferred to other accounts based on the resource client, and digital resources transferred from other accounts can also be received based on the resource client. The resource client can be a hardware device or a software program.

[0038] It is understandable that as various decentralized applications are widely deployed on the blockchain and user activities on the blockchain increase, when ordinary users use decentralized applications, they can use blockchain key management tools for login. The address in the blockchain key management tool corresponds to a user on the blockchain. Decentralized applications can obtain the user address from the key management tool through some interfaces. In order to solve the problem that the Dapp background cannot trust the user address used when the decentralized application logs in.

[0039] 2.2) Shared ledger, which is used to provide functions such as storage, query, and modification of account data (i.e., transaction data), sends the recorded data of the operations on the account data to other nodes in the blockchain network. After other nodes verify its validity, as a response to acknowledging the validity of the account data, they deposit the recorded data into a temporary block and can also send a confirmation to the node device that initiated the operation.

[0040] For example, each node device can receive the data to be recorded during normal operation and maintain the shared ledger (i.e., the blockchain) based on the received data to be recorded. To ensure information interconnection within the shared ledger network, there can be network connections between each node device in the shared ledger network, and data transmission can be carried out between node devices through the above network connections. For example, when any node device in the shared ledger network receives the data to be recorded, other node devices in the shared ledger network will verify the data to be recorded according to the consensus algorithm. After successful verification (i.e., after reaching a consensus), the data to be recorded is stored as data in the shared ledger, so that the data stored on all node devices in the shared ledger network is consistent.

[0041] 2.3) Smart contract, a computerized protocol that can execute the terms of a certain contract, implemented through code deployed on the shared ledger and used to execute when certain conditions are met. According to actual business requirements, the code is used to complete automated transactions, such as querying the logistics status of the goods purchased by the buyer and transferring the buyer's digital resources to the merchant's address after the buyer signs for the goods; of course, smart contracts are not limited to executing contracts for transactions, but can also execute contracts for processing the received information.

[0042] It should be noted that the node device 101, node device 102, node device 103, and node device 104 can be an independent physical server, or a server cluster or distributed system composed of at least two physical servers. They can also be cloud servers that provide 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 Network (CDN), and big data and artificial intelligence platforms. The terminal can include: smart phones, tablets, laptop computers, desktop computers, intelligent voice interaction devices, smart home appliances (such as smart TVs), wearable devices, vehicle-mounted terminals, and other intelligent terminals with data processing functions.

[0043] In this application, any node device in the blockchain network can be used to conduct transactions on multimedia data. Specifically, taking the node device 101 as an example, the node device 101 can obtain the behavior operation data of each multimedia data in the multimedia platform, as well as the object attribute information of the owner of each multimedia data. The consensus node device in the blockchain network can conduct consensus on the behavior operation data and object attribute information. When the consensus is passed, the obtained behavior operation data and object attribute information are stored on the blockchain. Here, the consensus can refer to verifying the authenticity and integrity of the behavior operation data and object attribute information, and when it is determined that the behavior operation data and object attribute information are authentic and complete, it is determined that the behavior operation data and object attribute information have passed the consensus.

[0044] Furthermore, when the first device needs to purchase the multimedia data B published by the second device in the multimedia platform, the node device 101 can receive the transaction request of the first device for the multimedia data B published by the second device in the media platform, read the behavior operation data of the multimedia data B from the blockchain according to the transaction request, as well as the first object attribute information of the object corresponding to the second device. According to the behavior operation data and the first object attribute information on the blockchain, predict the asset value of the multimedia data B, which is beneficial to improving the accuracy of the asset value of the multimedia data, avoiding users from maliciously inflating the asset value of the multimedia data, and improving the transaction security of the multimedia data. Further, according to the transaction request and the asset value of the multimedia data B, transfer digital assets from the account address corresponding to the first device to the account address corresponding to the second device, generate an updated digital certificate for the multimedia data B, and store the updated digital certificate on the blockchain. The updated digital certificate is used to indicate that the multimedia data B belongs to the object corresponding to the first device. By generating the updated digital certificate, it is beneficial for the object corresponding to the first device to conduct transactions on the multimedia data B again, and it is beneficial to realize the traceability of the multimedia data B.

[0045] It should be noted that the first device here can refer to a device for purchasing multimedia data. The first device can be any one of terminals 111, 112, and 113. The second device can refer to a device for selling multimedia data. The second device can be any one of terminals 111, 112, and 113. The first device and the second device are different.

[0046] Please refer to Figure 2 , Figure 2 which is a schematic diagram of the interaction scenario among the devices of a blockchain data processing system provided by an embodiment of the present application. Figure 2 The node device 203 in Figure 1 can refer to any node device in the blockchain network in Figure 2 The terminals 201 and 202 in Figure 1 can refer to different terminals in . There is a blockchain 204 stored in the node device 203. Multimedia platforms are installed in both the terminal 201 and the terminal 202. The object corresponding to the terminal 201 is Xiao Wang, and the object corresponding to the terminal 202 is Xiao Zhang. There is a social relationship between Xiao Zhang and Xiao Wang, and they can operate on each other's published multimedia data (viewing, purchasing, clicking, favoriting, commenting, etc.).

[0047] In a specific implementation, the terminal 201 can respond to a publishing request for the multimedia data C and display the published multimedia data C on the media page 205 in the multimedia platform. The multimedia page 205 also includes a selling option for the multimedia data C. The selling option is used to sell the multimedia data C to other users. The multimedia data C is a work completed by Xiao Wang, that is, the multimedia data C is an original work of Xiao Wang. After the multimedia data C is published on the multimedia platform, the background service device of the multimedia platform can send the multimedia data C to the associated terminal corresponding to the object having a social relationship with Xiao Wang. The associated terminal can display the multimedia data C on the multimedia platform, generate behavior operation data in response to the behavior operation for the multimedia data C. The behavior operations include liking, collecting, commenting, etc. The behavior operation data includes the behavior operation, the corresponding number of times of the behavior operation, and the object attribute information of the object performing the behavior operation, etc. Then, the behavior operation data is synchronized to the terminal 201. The terminal 201 displays the behavior operation data on the media page 205. The terminal 201 can also send the behavior operation data of the multimedia data C and the object attribute information of Xiao Wang to the node device 203. The node device 203 can send the behavior operation data and the object attribute information of Xiao Wang to the consensus node device in the blockchain network. The consensus node device conducts consensus on the behavior operation data and the object attribute information of Xiao Wang. When the behavior operation data and the object attribute information of Xiao Wang pass the consensus, the node device 203 can store the behavior operation data and the object attribute information of Xiao Wang on the blockchain 204.

[0048] As Figure 2 shown in, the associated terminal includes the terminal 202. After receiving the multimedia data C, the terminal 202 can display the multimedia data C and the behavior operation data of the multimedia data C on the multimedia page 206. The multimedia page 206 also includes a purchase option. The terminal 202 generates a transaction request for the multimedia data C in response to a trigger operation for the purchase option. The transaction request carries the media attribute information of the multimedia data C. The media attribute information includes at least one of the media identifier, media type, data size, publishing time, etc. of the multimedia data C. The terminal 202 can send the transaction request for the multimedia data C to the terminal 201. The terminal 201 can verify whether the terminal 202 has the purchase permission for the multimedia data C. For example, when it is verified that the terminal 202 has the purchase permission for the multimedia data C, the transaction request for the multimedia data C can be sent to the node device 203. In particular, here the terminal 202 can also directly send the transaction request for the multimedia data C to the node device 203 in the blockchain network.

[0049] As Figure 2After the node device 203 receives a transaction request for the multimedia data C, according to the media attribute information carried in the transaction request, it reads the behavioral operation data of the multimedia data C and the object attribute information of Xiao Wang from the blockchain 204, and predicts the asset value of the multimedia data C based on the behavioral operation data and the object attribute information. According to the asset value and the transaction request, digital assets are transferred from Xiao Zhang's account address to Xiao Zhang's account address, and an updated digital voucher 207 for the multimedia data is generated and stored on the blockchain. The updated digital voucher is used to indicate that the multimedia data belongs to Xiao Zhang.

[0050] Optionally, when the behavioral operation data and the object attribute information of Xiao Wang are consensus-passed, the node device 203 can generate an original digital voucher for the multimedia data C and store the original digital voucher in the blockchain 204. The original digital voucher can be used to indicate that the multimedia data C belongs to Xiao Wang. After the node device 203 generates the updated digital voucher, the original digital voucher of the multimedia data C becomes invalid.

[0051] In summary, by pre-storing the behavioral operation data of the multimedia data and the object attribute information of the owner of the multimedia data on the blockchain, the authenticity and immutability of the behavioral operation data and the first object attribute information can be ensured. During the process of trading multimedia data, by predicting the asset value of the multimedia data based on the behavioral operation data and the object attribute information on the blockchain, it is beneficial to improve the accuracy of the asset value of the multimedia data, avoid users maliciously inflating the asset value of the multimedia data, and improve the transaction security of the multimedia data. At the same time, during the process of trading multimedia data, by generating an updated digital voucher for the multimedia data, it is beneficial to trade the multimedia data again and facilitate the traceability of the multimedia data.

[0052] Please refer to Figure 3 which is a schematic flowchart of a blockchain data processing method provided by an embodiment of the present application. The present application can be executed by Figure 1 any node device in the blockchain network in

[0053] S301. Receive a transaction request from a first device for multimedia data published by a second device on a media platform; the transaction request carries media attribute information of the multimedia data.

[0054] It should be noted that the above transaction request further includes the account address of the object corresponding to the first device, the IP address of the first device, the account address of the object corresponding to the second device, the IP address of the second device, etc. The media attribute information of the multimedia data may include the media identifier, media type, size, etc. of the multimedia data.

[0055] It should be noted that the multimedia data can be an original work of the object corresponding to the second device, that is, it is first displayed on the multimedia platform by the second device. The multimedia data is obtained by shooting with the second device, or the multimedia data can be generated by the second device. The multimedia data can be a non-original work of the object corresponding to the second device. For example, the multimedia data can be purchased by the object corresponding to the second device.

[0056] It can be understood that when the first device detects a trigger operation of the object corresponding to the first device for the transaction option regarding the multimedia data on the media platform, it can generate a transaction request for the multimedia data published by the second device on the media platform and send the transaction request to the node device in the blockchain network. The node device can receive the transaction request of the first device for the multimedia data published by the second device on the media platform.

[0057] Optionally, obtain a second similarity between the above multimedia data and the historical multimedia data in the second database; the above historical multimedia data is the multimedia data for which the corresponding digital certificate is recorded on the above blockchain; when the above second similarity is less than the similarity threshold, determine that the above multimedia data belongs to the object corresponding to the above second device; generate an original digital certificate for the above multimedia data according to the first object attribute information of the object corresponding to the above second device and the above media attribute information, and store the above original digital certificate in the above blockchain; the above original digital certificate is used to indicate that the above multimedia data belongs to the object corresponding to the above second device.

[0058] It should be noted that the second database is used to store the multimedia data for which the corresponding digital certificate is recorded on the blockchain; the second similarity can be obtained by a similarity algorithm, and the similarity algorithm specifically includes cosine similarity, Jaccard similarity coefficient, Euclidean distance, etc.; the similarity threshold can be set by the node device or stored in the blockchain. The first object attribute information can include the user information of the object corresponding to the second device, and the user information includes user name, user level, etc.

[0059] It is understandable that after the second device publishes the multimedia data to the multimedia platform, the node device can obtain the historical multimedia data in the second database, and use a similarity algorithm to calculate the similarity between the multimedia data and the historical multimedia data, which is denoted as the second similarity. When the second similarity is less than the similarity threshold, it indicates that the multimedia data has not generated a digital certificate, and the multimedia data is an original work of the object corresponding to the second device. The node device can determine that the above multimedia data belongs to the object corresponding to the second device, and generate an original digital certificate for the above multimedia data according to the first object attribute information of the object corresponding to the second device and the above media attribute information, and store the above original digital certificate in the above blockchain; the above original digital certificate is used to indicate that the above multimedia data belongs to the object corresponding to the second device, and the original digital certificate can prevent the multimedia data from being used by illegal users, realizing the copyright protection and security of the multimedia data.

[0060] It should be noted that the original digital certificate can include an ownership certificate for the multimedia data. The original digital certificate has verifiability, transparent execution, validity, immutability, accessibility, and tradability; the original digital certificate includes the unique identifier of the multimedia data, as well as the object attribute information corresponding to the second device and the media attribute information of the multimedia data.

[0061] Optionally, obtain the historical behavior operation data and the marked asset value of the sample multimedia data, as well as the third object attribute information of the publisher of the above sample multimedia data; call the initial value recognition model to perform label recognition on the above sample multimedia data to obtain the predicted label of the above sample multimedia data; obtain the second correlation degree between the predicted label of the above sample multimedia data and the second marked label; the second marked label is obtained from the description information of the above sample multimedia data; predict the additional value of the above sample multimedia data according to the above historical behavior operation data and the above third object attribute information; predict the asset value of the above sample multimedia data according to the above second correlation degree and the above additional value; adjust the above initial value recognition model according to the asset value of the above sample multimedia data and the above marked asset value to obtain a value recognition model.

[0062] It is understandable that the initial value recognition model is a value recognition model with a low accuracy rate, that is, there are large errors in the asset value of the multimedia data predicted by the initial value recognition model. To improve the prediction accuracy of the initial value model and reduce the prediction error, the node device can obtain a value recognition model with higher accuracy by training the initial value recognition model. Specifically, the node device can obtain the historical behavior operation data and labeled asset value of the sample multimedia data from the blockchain, as well as the third object attribute information of the publisher of the above sample multimedia data. Input the sample multimedia data into the initial value recognition model, and through the initial value recognition model, perform label recognition on the above sample multimedia data to obtain the predicted label of the above sample multimedia data. The predicted label of the sample multimedia data here is used to reflect the media type of the sample multimedia data. Using a similarity algorithm, obtain the second correlation degree between the predicted label of the above sample multimedia data and the second labeled label; the second labeled label is obtained from the description information of the above sample multimedia data, that is, the second labeled label can be a keyword in the description information that reflects the media type of the sample multimedia data.

[0063] Furthermore, according to the above historical behavior operation data and the above third object attribute information, predict the additional value of the above sample multimedia data. According to the above second correlation degree and the above additional value, predict the asset value of the above sample multimedia data. If the asset value of the sample multimedia data is relatively similar to the labeled asset value, it indicates that the value prediction accuracy of the initial value recognition model is relatively high; if the asset value of the sample multimedia data differs greatly from the labeled asset value, it indicates that the value prediction accuracy of the initial value recognition model is relatively low. Therefore, the computer device can adjust the above initial value recognition model according to the asset value of the above sample multimedia data and the above labeled asset value to obtain a value recognition model. By training the initial value recognition model, a value recognition model is obtained, and the value recognition accuracy of the value recognition model is improved.

[0064] It should be noted that the historical time period can refer to the last week, last month, last day, etc.; the above third object attribute information can include the user name, user level, etc. of the publisher of the sample multimedia data.

[0065] Optionally, determine the asset prediction error of the above initial value recognition model according to the asset value of the above sample multimedia data and the above labeled asset value; determine the convergence state of the above initial value recognition model according to the above asset prediction error; when the convergence state of the above initial value recognition model is the non-converged state, adjust the model parameters of the above initial value recognition model according to the above asset prediction error; determine the adjusted initial value recognition model as the value recognition model.

[0066] It is understandable that the node device inputs the asset value annotating the asset value and the sample multimedia data into the loss function of the initial value recognition model, and obtains the asset prediction error of the initial value recognition model. The asset prediction error is used to reflect the value recognition accuracy of the initial value recognition model, that is, the greater the asset prediction error, the lower the value recognition accuracy of the initial value recognition model; the lower the asset prediction error, the higher the value recognition accuracy of the initial value recognition model. Further, the node device can determine the convergence state of the initial value recognition model according to the above asset prediction error; the converged state of the initial value recognition model includes the converged state and the non-converged state. The converged state reflects that the asset prediction error of the initial value recognition model reaches the lowest, and the non-converged state reflects that the asset prediction error of the initial value recognition model does not reach the lowest. When the convergence state of the initial value recognition model is the converged state, the node device can use the initial value recognition model as the value recognition model. When the convergence state of the initial value recognition model is the non-converged state, the node device can adjust the model parameters of the initial value recognition model according to the above asset prediction error until the convergence state of the adjusted initial value recognition model is the converged state, or when the number of adjustments to the model parameters of the initial value recognition model is greater than the number threshold, the node device can determine the adjusted initial value recognition model as the value recognition model to improve the value recognition accuracy of the value recognition model.

[0067] S302. According to the media attribute information carried in the transaction request, obtain the behavioral operation data on the multimedia data from the blockchain, and the first object attribute information of the object corresponding to the second device.

[0068] It should be noted that the above first object attribute information may include the user information of the object corresponding to the second device, and the user information includes the user name, user level, etc. The above behavioral operation data includes data such as the number of comments, likes, forwards, etc. on the multimedia data.

[0069] It is understandable that after the node device receives the transaction request from the first device for the multimedia data published by the second device on the media platform, it can obtain the behavioral operation data on the multimedia data from the blockchain according to the media attribute information of the multimedia data, and the first object attribute information of the object corresponding to the second device. Among them, the behavioral operation data can reflect the degree of preference of users on the media platform for the media data, and the first object attribute information can reflect the popularity of the object corresponding to the second device on the media platform. In this way, through the behavioral operation data and the first object attribute information, the multimedia data can be comprehensively understood.

[0070] S303. Predict the asset value of the multimedia data according to the behavioral operation data and the first object attribute information.

[0071] It is understandable that the node device can analyze the degree of preference of users of the media platform for multimedia data based on the behavioral operation data; analyze the popularity of the object corresponding to the second device on the media platform according to the first object attribute information; and predict the asset value of the multimedia data based on the above analysis. The asset value may refer to the number of assets corresponding to the digital assets required to purchase the multimedia data. In this way, the multimedia data is analyzed from multiple aspects, thereby improving the accuracy of predicting the asset value of the multimedia data.

[0072] S304. Transfer digital assets from the account address corresponding to the first device to the account address corresponding to the second device according to the transaction request and the asset value of the multimedia data, generate an updated digital certificate for the multimedia data, and store the updated digital certificate on the blockchain.

[0073] It should be noted that the above account address can be used to receive and store digital assets and is generated by a specific algorithm using a private key. The above updated digital certificate may include the unique identifier of the multimedia data, as well as the object attribute information and media attribute information possessed by the object corresponding to the first device.

[0074] It is understandable that after the node device predicts the asset value of the multimedia data, it transfers the number of digital assets indicated by the asset value of the multimedia data from the account address corresponding to the first device to the account address corresponding to the second device; after transferring the digital assets, the node device can generate an updated digital certificate according to the media attribute information in the transaction request of the multimedia data and the object attribute information possessed by the object corresponding to the first device, and store the updated digital certificate on the blockchain. The updated digital certificate is used to indicate that the multimedia data belongs to the object corresponding to the first device. In this way, according to the predicted asset value of the multimedia data, the digital assets in the account address corresponding to the first device are directly transferred to the account address corresponding to the second device. By generating an updated digital certificate, it is beneficial for the object corresponding to the first device to trade the multimedia data again and is beneficial to realizing the traceability of the multimedia data.

[0075] Optionally, according to the above transaction request, obtain the distribution strategy of the value-added assets of the above multimedia data from the above blockchain; determine the number of assets of the digital assets that the object corresponding to the first device needs to pay to purchase the above multimedia data according to the above distribution strategy and the asset value of the above multimedia data; transfer the number of digital assets of the above assets from the account address corresponding to the first device to the account address corresponding to the second device.

[0076] It should be noted that the above-mentioned value-added assets can be the increased part of the asset value of the multimedia data over a period of time; the above-mentioned distribution strategy can be a distribution ratio. The value-added assets can be determined according to the newly added behavioral operation data of the multimedia data, and the newly added behavioral operation data can refer to the data generated after the updated digital certificate of the multimedia data is generated.

[0077] It can be understood that when the object corresponding to the first device purchases multimedia data, there can be multiple purchase methods, including purchasing the right to use the multimedia data, purchasing the right to adapt the multimedia data, etc.; under different purchase methods, the value-added assets of the multimedia data that the object corresponding to the first device can obtain are different, and the amount of digital assets that the object corresponding to the first device needs to pay when purchasing is also different. Therefore, when transferring digital assets to the account address of the object corresponding to the second device, the node device can obtain the distribution strategy of the value-added assets of the multimedia data corresponding to this purchase method from the blockchain according to the purchase method of the object corresponding to the first device, and determine the distribution ratio of the value-added assets of the multimedia data for the object corresponding to the first device according to the distribution ratio recorded in the distribution strategy. The node device determines the amount of digital assets that the object corresponding to the first device needs to pay for purchasing the multimedia data according to the asset value of the multimedia data and the above-mentioned distribution ratio, and transfers the digital assets of this asset amount from the account address corresponding to the first device to the account address corresponding to the second device. By determining the distribution strategy of the value-added assets of the multimedia data through the purchase method, and thus determining the amount of digital assets that the object corresponding to the first device needs to pay for purchasing the multimedia data, the transaction fairness of the multimedia data can be improved.

[0078] For example, the object corresponding to the first device purchases the right to adapt the multimedia data, and the distribution ratio of the value-added assets of the multimedia data corresponding to the right to adapt is 1:1. Therefore, the distribution ratio of the value-added assets of the multimedia data for the object corresponding to the first device and the object corresponding to the second device is 1:1. If the asset value of the multimedia data is 100, then the node device determines that the amount of digital assets that the object corresponding to the first device needs to pay for purchasing the multimedia data is 50% of the asset value (i.e., 50); the node device transfers digital assets with an asset amount of 50 from the account address corresponding to the first device to the account address corresponding to the second device.

[0079] Optionally, according to the above-mentioned distribution strategy, determine the share of the multimedia data held by the object corresponding to the first device; generate an initial digital certificate according to the above-mentioned media attribute information and the second object attribute information of the object corresponding to the first device; add the share held by the object corresponding to the first device to the initial digital certificate to obtain the updated digital certificate of the multimedia data.

[0080] It should be noted that the above second object attribute information may include the user information of the object corresponding to the above first device, and the user information includes user name, user level, etc. The above initial digital certificate may include the second object attribute information, the attribute information of the multimedia data, and a unique identifier. The unique identifier is used to indicate the uniqueness of the initial digital certificate.

[0081] It can be understood that the distribution policy can also indicate the ownership share of the owner for the multimedia data. Therefore, the node device can determine the ownership share of the object corresponding to the first device for the multimedia data according to the distribution policy; the node device can generate an initial digital certificate according to the media attribute information and the second object attribute information of the object corresponding to the first device, and the initial digital certificate includes the unique identifier of the multimedia data; adding the ownership share of the object corresponding to the first device for the multimedia data to the initial digital certificate can obtain the updated digital certificate of the multimedia data.

[0082] For example, if the distribution policy of the object corresponding to the first device and the object corresponding to the second device for the multimedia data is 1:1, then the ownership share of the object corresponding to the first device for the multimedia data is 50%. The above second object attribute information is that the user name of the object corresponding to the first device is A. Therefore, the node device generates a unique identifier, generates an initial digital certificate according to the media attribute information, the second object attribute information of the object corresponding to the first device, and the unique identifier, and adds the ownership share (i.e., 50%) to the initial digital certificate, then the updated digital certificate of the multimedia data can be obtained.

[0083] Optionally, obtain the updated behavior operation data of the above multimedia data; determine the value-added assets of the above multimedia data according to the above updated behavior operation data; obtain the latest digital certificate of the above multimedia data from the above blockchain; the above latest digital certificate is the digital certificate with the smallest time interval between the recording time on the above blockchain and the current time; determine the owner of the above multimedia data and the ownership share of the owner for the above multimedia data according to the above latest digital certificate; distribute the above value-added assets to the owner according to the ownership share of the owner for the above multimedia data.

[0084] It should be noted that the update behavior operation data can be the behavior operation data of the multimedia data within the update time period; the update time period can be the time period from the time node when the update digital certificate is generated to the current time node. The above-mentioned latest digital certificate is used to indicate the current owner of the multimedia data. The owner can be one object or multiple objects, and the owner can obtain the value-added assets of the multimedia data; the latest digital certificate includes the share of ownership of the owner for the above-mentioned multimedia data. It can be understood that after the update digital certificate is generated, the asset value of the multimedia data will change over time. Therefore, value-added assets of the multimedia data may be generated. In order to determine accurate value-added assets and reasonably distribute the value-added assets to the owners, the node device obtains the behavior operation data of the multimedia data within the update time period from the blockchain, that is, data such as the number of comments, the number of likes, and the number of forwards generated after the update digital certificate, and determines the value-added assets of the multimedia data. Furthermore, the node device obtains the latest digital certificate of the multimedia data from the above-mentioned blockchain, determines the user name of the current owner of the multimedia data and the account address of the owner from the latest digital certificate. In addition, the node device can also obtain the share of ownership of the owner for the multimedia data from the latest digital certificate. The node device determines the amount of the value-added assets of the multimedia data that the owner can obtain according to the share of ownership of the owner for the above-mentioned multimedia data and the amount of the value-added assets; the node device transfers the digital assets corresponding to the amount of assets of the owner to the account address of the corresponding owner. This can avoid distributing the value-added assets to the account addresses of irrelevant objects and improve the fairness of the distribution of the value-added assets of the multimedia data.

[0085] In this application, by pre-storing the behavior operation data of the multimedia data and the first object attribute information of the owner of the multimedia data (i.e., the object corresponding to the second device) on the blockchain, that is, the behavior operation data and the first object attribute information have authenticity and immutability. Therefore, when the first device needs to purchase the multimedia data published by the second device on the media platform, by predicting the asset value of the multimedia data according to the behavior operation data and the first object attribute information on the blockchain, it is beneficial to improve the accuracy of the asset value of the multimedia data, avoid users maliciously inflating the asset value of the multimedia data, and improve the transaction security of the multimedia data. Further, according to the transaction request and the asset value of the multimedia data, digital assets are transferred from the account address corresponding to the first device to the account address corresponding to the second device, an update digital certificate of the multimedia data is generated, and the update digital certificate is stored on the blockchain. The update digital certificate is used to indicate that the multimedia data belongs to the object corresponding to the first device. By generating the update digital certificate, it is beneficial for the object corresponding to the first device to trade the multimedia data again and is beneficial to realizing the traceability of the multimedia data.

[0086] Please refer to Figure 4 , which is a schematic flowchart of a blockchain data processing method provided by an embodiment of the present application. The present application can be executed by any node device in the Figure 1 blockchain network. Among them, the method may include the following steps:

[0087] S401. Receive a transaction request from a first device for multimedia data published by a second device on a media platform; the transaction request carries media attribute information of the multimedia data.

[0088] S402. According to the media attribute information carried in the transaction request, obtain behavioral operation data about the multimedia data and first object attribute information of the object corresponding to the second device from the blockchain.

[0089] S403. Invoke a value recognition model to perform label recognition on the multimedia data to obtain a predicted label of the multimedia data.

[0090] It should be noted that the above value recognition model can be used to predict the asset value of the multimedia data. The above predicted label is used to reflect the media type of the sample multimedia data.

[0091] It can be understood that, in order to more accurately predict the asset value of the multimedia data, after the node device obtains the behavioral operation data about the multimedia data and the first object attribute information from the blockchain; the multimedia data is input into the value recognition model, and through the value recognition model, label recognition is performed on the multimedia data, and then the predicted label of the multimedia data can be obtained.

[0092] S404. Obtain a first correlation degree between the predicted label of the multimedia data and a first labeled label.

[0093] It should be noted that the first labeled label is the label concerned by the object corresponding to the first device, that is, the media type of the multimedia data concerned by the object corresponding to the first device on the media platform. The above first correlation degree can be obtained through a correlation degree algorithm, and the above correlation degree algorithm may include a cosine similarity algorithm, a Pearson correlation coefficient algorithm, an Euclidean distance algorithm, etc.

[0094] It can be understood that after the node device obtains the predicted label of the multimedia data, the first labeled label is obtained from the media types to which the content multimedia data concerned by the object corresponding to the first device belongs, and a similarity algorithm is used to obtain the first correlation degree between the above predicted label and the above first labeled label.

[0095] S405. Predict the additional value of the multimedia data according to the behavioral operation data and the first object attribute information.

[0096] It is understandable that the node device analyzes the degree of preference of users of the media platform for multimedia data based on behavioral operation data; analyzes the popularity of the object corresponding to the second device on the media platform according to the first object attribute information; and predicts the added value of the multimedia data based on the above analysis. Through the behavioral operation data and the first object attribute information, the popularity of the multimedia data can be understood. The higher the popularity, the higher the asset value of the multimedia data, which is conducive to obtaining a high-accuracy asset value.

[0097] S406. Predict the asset value of the multimedia data according to the first correlation degree and the added value.

[0098] It should be noted that the first correlation degree can be used to indicate the correlation between the multimedia data and the multimedia data concerned by the object corresponding to the first device. The asset value of multimedia data with a high correlation can provide a reference for predicting the asset value of the multimedia data.

[0099] It is understandable that the node device inputs the first correlation degree and the added value into the value recognition model, and through the value recognition model, the asset value of the multimedia data can be obtained.

[0100] Optionally, call the above value recognition model, determine the content value of the multimedia data according to the above first correlation degree; obtain the weights corresponding to the above content value and the above added value respectively; perform a weighted summation process on the above content value and the above added value according to the weights corresponding to the above content value and the above added value respectively to obtain the asset value of the multimedia data.

[0101] It should be noted that the above weights can refer to the proportion of the content value and the added value in the asset value respectively, and the weights can be set by the value recognition model.

[0102] It is understandable that the asset values of multimedia data of the same media type are not necessarily the same. Therefore, the asset values of multimedia data with high relevance are not necessarily the same. In order to predict a more accurate asset value, the node device can determine the content value of the multimedia data through the first association degree, and obtain the weights corresponding to the content value and the additional value respectively, that is, obtain the proportion of the content value and the additional value in the asset value; multiply the content value by the corresponding proportion, multiply the additional value by the corresponding proportion, and then add the multiplied results to obtain the asset value of the multimedia data. For example, the content value is 100, the additional value is 120, and the proportions of the content value and the additional value in the asset value are 40% and 60% respectively; therefore, multiply the content value by the corresponding proportion (i.e., 100 multiplied by 40%), multiply the additional value by the corresponding proportion (i.e., 120 multiplied by 60%), and then add the multiplied results to obtain the asset value of the multimedia data as 112. Determining the asset value of multimedia data through the weights corresponding to the content value and the additional value respectively avoids the situation where the asset value of multimedia data is too high or too low due to either the content value or the additional value being too high or too low, and improves the accuracy of the asset value of multimedia data.

[0103] Optionally, perform a weighted summation process on the content value and the additional value according to the weights corresponding to the content value and the additional value respectively to obtain the initial asset value of the multimedia data; obtain the first similarity between the multimedia data and the reference media data in the first database; the reference media data is the multimedia data that has been published on the media platform; predict the original value of the multimedia data according to the first similarity; perform a summation process on the original value and the initial asset value to obtain the asset value of the multimedia data.

[0104] It should be noted that the first database is used to store the multimedia data that has been published on the media platform, and the first similarity can be obtained by a similarity algorithm, which specifically includes cosine similarity, Jaccard similarity coefficient, Euclidean distance, etc. The original value is used to indicate the originality of the multimedia data; the higher the originality of the multimedia data, the higher the original value of the multimedia data.

[0105] It is understandable that the node device determines the proportions of the content value and the additional value in the asset value according to the weights corresponding to the content value and the additional value respectively, and performs a weighted summation process on the content value and the additional value to obtain the initial asset value of the multimedia data. The node device can obtain the reference multimedia data in the first database, and use the similarity algorithm to obtain the first similarity between the multimedia data and the reference media data in the first database. The node device predicts the original value of the multimedia data according to the first similarity. Among them, the lower the first similarity, the more original the multimedia data is, and the higher the original value of the multimedia data; on the contrary, the higher the first similarity, the less original the multimedia data is, and the lower the original value of the multimedia data. The node device adds the original value and the initial asset value to obtain the asset value of the multimedia data. In this way, it avoids the problem that due to the high originality of the multimedia data, there are too few associated multimedia data, and the object corresponding to the first device has not paid attention to the multimedia data associated with the multimedia data, so the content value is inaccurate, resulting in inaccurate asset value of the multimedia data, and improves the accuracy of the asset value of the multimedia data.

[0106] S407. According to the transaction request and the asset value of the multimedia data, transfer the digital assets from the account address corresponding to the first device to the account address corresponding to the second device, generate an updated digital certificate for the multimedia data, and store the updated digital certificate on the blockchain.

[0107] In this application, by pre-storing the behavior operation data of the multimedia data and the first object attribute information of the owner of the multimedia data (that is, the object corresponding to the second device) on the blockchain, that is, the behavior operation data and the first object attribute information have authenticity and non-tamperability. Therefore, when the first device needs to purchase the multimedia data published by the second device on the media platform, by predicting the asset value of the multimedia data according to the behavior operation data and the first object attribute information on the blockchain, it is beneficial to improve the accuracy of the asset value of the multimedia data, avoid maliciously inflating the asset value of the multimedia data by users, and improve the transaction security of the multimedia data. Further, according to the transaction request and the asset value of the multimedia data, transfer the digital assets from the account address corresponding to the first device to the account address corresponding to the second device, generate an updated digital certificate for the multimedia data, and store the updated digital certificate on the blockchain. The updated digital certificate is used to indicate that the multimedia data belongs to the object corresponding to the first device. By generating the updated digital certificate, it is beneficial for the object corresponding to the first device to trade the multimedia data again and is beneficial to realizing the traceability of the multimedia data.

[0108] Please refer to Figure 5 , which is a schematic structural diagram of a blockchain data processing device provided by an embodiment of the present application. AsFigure 5 As shown, the blockchain data processing device may include:

[0109] A receiving module 511, configured to receive a transaction request from a first device for multimedia data published by a second device on a media platform; the transaction request carries media attribute information of the multimedia data;

[0110] An obtaining module 512, configured to obtain, from the blockchain, behavior operation data of the multimedia data and first object attribute information of an object corresponding to the second device according to the media attribute information carried in the transaction request;

[0111] A prediction module 513, configured to predict the asset value of the multimedia data according to the behavior operation data and the first object attribute information;

[0112] A transfer module 514, configured to transfer digital assets from an account address corresponding to the first device to an account address corresponding to the second device according to the transaction request and the asset value of the multimedia data, generate an updated digital certificate of the multimedia data, and store the updated digital certificate on the blockchain; the updated digital certificate is used to indicate that the multimedia data belongs to an object corresponding to the first device.

[0113] Optionally, the prediction module 513 predicts the asset value of the multimedia data according to the behavior operation data and the first object attribute information, including:

[0114] Invoking a value recognition model to perform label recognition on the multimedia data to obtain a predicted label of the multimedia data;

[0115] Obtaining a first correlation degree between the predicted label of the multimedia data and a first labeled label; the first labeled label is a label concerned by an object corresponding to the first device;

[0116] Predicting an additional value of the multimedia data according to the behavior operation data and the first object attribute information;

[0117] Predicting the asset value of the multimedia data according to the first correlation degree and the additional value.

[0118] Optionally, the prediction module 513 predicts the asset value of the multimedia data according to the first correlation degree and the additional value, including:

[0119] Invoking the value recognition model to determine the content value of the multimedia data according to the first correlation degree;

[0120] Obtaining weights corresponding to the content value and the additional value respectively;

[0121] Based on the weights corresponding to the above content value and the above additional value respectively, perform a weighted summation process on the above content value and the above additional value to obtain the asset value of the above multimedia data.

[0122] Optionally, the above prediction module 513 performs a weighted summation process on the above content value and the above additional value based on the weights corresponding to the above content value and the above additional value respectively to obtain the asset value of the above multimedia data, including:

[0123] Perform a weighted summation process on the above content value and the above additional value based on the weights corresponding to the above content value and the above additional value respectively to obtain the initial asset value of the above multimedia data;

[0124] Obtain the first similarity between the above multimedia data and the reference media data in the first database; the above reference media data is the multimedia data that has been published on the above media platform;

[0125] Predict the original value of the above multimedia data based on the above first similarity;

[0126] Perform a summation process on the above original value and the above initial asset value to obtain the asset value of the above multimedia data.

[0127] Optionally, the above prediction module 513 is further used to include:

[0128] Obtain the historical behavior operation data and the labeled asset value of the sample multimedia data, as well as the third object attribute information of the publisher of the above sample multimedia data;

[0129] Call the initial value recognition model to perform label recognition on the above sample multimedia data to obtain the predicted label of the above sample multimedia data;

[0130] Obtain the second correlation degree between the predicted label of the above sample multimedia data and the second labeled label; the above second labeled label is obtained from the description information of the above sample multimedia data;

[0131] Predict the additional value of the above sample multimedia data based on the above historical behavior operation data and the above third object attribute information;

[0132] Predict the asset value of the above sample multimedia data based on the above second correlation degree and the above additional value;

[0133] Adjust the above initial value recognition model based on the asset value of the above sample multimedia data and the above labeled asset value to obtain a value recognition model.

[0134] Optionally, the prediction module 513 adjusts the initial value recognition model according to the asset value of the sample multimedia data and the marked asset value to obtain a value recognition model, including:

[0135] Determine the asset prediction error of the initial value recognition model according to the asset value of the sample multimedia data and the marked asset value;

[0136] Determine the convergence state of the initial value recognition model according to the asset prediction error;

[0137] When the convergence state of the initial value recognition model is the non-converged state, the prediction module 513 adjusts the model parameters of the initial value recognition model according to the asset prediction error;

[0138] Determine the adjusted initial value recognition model as the value recognition model.

[0139] Optionally, the transfer module 514 transfers digital assets from the account address corresponding to the first device to the account address corresponding to the second device according to the transaction request and the asset value of the multimedia data, including:

[0140] Obtain the distribution strategy of the value-added assets regarding the multimedia data from the blockchain according to the transaction request;

[0141] Determine the asset quantity of the digital assets that the object corresponding to the first device needs to pay to purchase the multimedia data according to the distribution strategy and the asset value of the multimedia data;

[0142] Transfer the digital assets of the asset quantity from the account address corresponding to the first device to the account address corresponding to the second device.

[0143] Optionally, the transfer module 514 generates an updated digital certificate for the multimedia data, including:

[0144] Determine the occupancy share of the object corresponding to the first device for the multimedia data according to the distribution strategy;

[0145] Generate an initial digital certificate according to the media attribute information and the second object attribute information of the object corresponding to the first device;

[0146] Add the occupancy share of the object corresponding to the first device to the initial digital certificate to obtain the updated digital certificate for the multimedia data.

[0147] Optionally, the method further includes:

[0148] Obtain a second similarity between the above multimedia data and the historical multimedia data in the second database; the above historical multimedia data is the multimedia data for which the corresponding digital certificate is recorded on the above blockchain;

[0149] When the above second similarity is less than the similarity threshold, determine that the above multimedia data belongs to the object corresponding to the above second device;

[0150] Generate an original digital certificate for the above multimedia data according to the first object attribute information of the object corresponding to the above second device and the above media attribute information, and store the above original digital certificate in the above blockchain; the above original digital certificate is used to indicate that the above multimedia data belongs to the object corresponding to the above second device.

[0151] Optionally, the above method further includes:

[0152] Obtain the update behavior operation data of the above multimedia data;

[0153] Determine the value-added assets of the above multimedia data according to the above update behavior operation data;

[0154] Obtain the latest digital certificate of the above multimedia data from the above blockchain; the above latest digital certificate is the digital certificate with the smallest time interval between the recording time on the above blockchain and the current time;

[0155] Determine the owner of the above multimedia data and the share of ownership of the owner for the above multimedia data according to the above latest digital certificate;

[0156] Distribute the above value-added assets to the owner according to the share of ownership of the owner for the above multimedia data.

[0157] In this application, by pre-storing the behavioral operation data of the multimedia data and the first object attribute information of the owner of the multimedia data (i.e., the object corresponding to the second device) on the blockchain, the behavioral operation data and the first object attribute information have authenticity and immutability. Therefore, when the first device needs to purchase the multimedia data published by the second device on the media platform, predicting the asset value of the multimedia data based on the behavioral operation data and the first object attribute information on the blockchain is beneficial to improving the accuracy of the asset value of the multimedia data, avoiding malicious overvaluation of the asset value of the multimedia data by users, and enhancing the transaction security of the multimedia data. Further, according to the transaction request and the asset value of the multimedia data, digital assets are transferred from the account address corresponding to the first device to the account address corresponding to the second device, an updated digital voucher for the multimedia data is generated, and the updated digital voucher is stored on the blockchain. The updated digital voucher is used to indicate that the multimedia data belongs to the object corresponding to the first device. By generating the updated digital voucher, it is beneficial for the object corresponding to the first device to conduct transactions on the multimedia data again and is conducive to realizing the traceability of the multimedia data.

[0158] Please refer to Figure 6 , which is a schematic structural diagram of a computer device provided by an embodiment of this application. As Figure 6 shown, the above computer device 600 may refer to a server or a terminal, including: a processor 601, a network interface 604, and a memory 605. In addition, the above computer device 600 may further include: a user interface 603 and at least one communication bus 602. Among them, the communication bus 602 is used to implement connection communication between these components. Among them, in some embodiments, the user interface 603 may include a display screen (Display) and a keyboard (Keyboard). Optionally, the user interface 603 may further include a standard wired interface and a wireless interface. The network interface 604 may optionally include a standard wired interface and a wireless interface (such as a WI-FI interface). The memory 605 may be a high-speed RAM memory or a non-volatile memory, such as at least one disk memory. Optionally, the memory 605 may further be at least one storage device far from the aforementioned processor 601. As Figure 6 shown, the memory 605, as a computer-readable storage medium, may include an operating system, a network communication module, a user interface module, and a computer program.

[0159] In Figure 6 the computer device 600 shown, the network interface 604 can provide network communication functions; while the user interface 603 is mainly used to provide an input interface; and the processor 601 can be used to call the computer program stored in the memory 605 to execute:

[0160] Receive a transaction request from a first device for multimedia data published by a second device on a media platform; the transaction request carries media attribute information of the multimedia data.

[0161] Obtain, from a blockchain, behavior operation data regarding the multimedia data and first object attribute information of an object corresponding to the second device according to the media attribute information carried in the transaction request.

[0162] Predict the asset value of the multimedia data according to the behavior operation data and the first object attribute information.

[0163] Transfer digital assets from an account address corresponding to the first device to an account address corresponding to the second device according to the transaction request and the asset value of the multimedia data, generate an updated digital certificate for the multimedia data, and store the updated digital certificate on the blockchain; the updated digital certificate is used to indicate that the multimedia data belongs to an object corresponding to the first device.

[0164] Optionally, the processor 601 may be used to call a computer program stored in the memory 605 to execute predicting the asset value of the multimedia data according to the behavior operation data and the first object attribute information, including:

[0165] Call a value recognition model to perform label recognition on the multimedia data to obtain a predicted label of the multimedia data.

[0166] Obtain a first correlation degree between the predicted label of the multimedia data and a first labeled label; the first labeled label is a label concerned by an object corresponding to the first device.

[0167] Predict an additional value of the multimedia data according to the behavior operation data and the first object attribute information.

[0168] Predict the asset value of the multimedia data according to the first correlation degree and the additional value.

[0169] Optionally, the processor 601 may be used to call a computer program stored in the memory 605 to execute predicting the asset value of the multimedia data according to the first correlation degree and the additional value, including:

[0170] Call the value recognition model to determine the content value of the multimedia data according to the first correlation degree.

[0171] Obtain weights corresponding to the content value and the additional value respectively.

[0172] Based on the weights corresponding to the above content value and the above additional value respectively, perform a weighted summation process on the above content value and the above additional value to obtain the asset value of the above multimedia data.

[0173] Optionally, the processor 601 may be used to call a computer program stored in the memory 605 to execute the above process of performing a weighted summation process on the above content value and the above additional value based on the weights corresponding to the above content value and the above additional value respectively to obtain the asset value of the above multimedia data, including:

[0174] Perform a weighted summation process on the above content value and the above additional value based on the weights corresponding to the above content value and the above additional value respectively to obtain the initial asset value of the above multimedia data;

[0175] Obtain a first similarity between the above multimedia data and reference media data in a first database; the above reference media data is multimedia data that has been published on the above media platform;

[0176] Predict the original value of the above multimedia data based on the above first similarity;

[0177] Perform a summation process on the above original value and the above initial asset value to obtain the asset value of the above multimedia data.

[0178] Optionally, the processor 601 may be used to call a computer program stored in the memory 605 to execute the above method further including:

[0179] Obtain historical behavior operation data and labeled asset value of sample multimedia data, and third object attribute information of the publisher of the above sample multimedia data;

[0180] Call an initial value recognition model to perform label recognition on the above sample multimedia data to obtain a predicted label of the above sample multimedia data;

[0181] Obtain a second correlation degree between the predicted label of the above sample multimedia data and a second labeled label; the above second labeled label is obtained from the description information of the above sample multimedia data;

[0182] Predict the additional value of the above sample multimedia data based on the above historical behavior operation data and the above third object attribute information;

[0183] Predict the asset value of the above sample multimedia data based on the above second correlation degree and the above additional value;

[0184] Adjust the above initial value recognition model based on the asset value of the above sample multimedia data and the above labeled asset value to obtain a value recognition model.

[0185] Optionally, the processor 601 may be used to call a computer program stored in the memory 605 to perform the above adjustment of the initial value recognition model based on the asset value of the above sample multimedia data and the above marked asset value to obtain a value recognition model, including:

[0186] Determine the asset prediction error of the initial value recognition model according to the asset value of the above sample multimedia data and the above marked asset value;

[0187] Determine the convergence state of the initial value recognition model according to the above asset prediction error;

[0188] When the convergence state of the initial value recognition model is the non-converged state, adjust the model parameters of the initial value recognition model according to the above asset prediction error;

[0189] Determine the adjusted initial value recognition model as the value recognition model.

[0190] Optionally, the processor 601 may be used to call a computer program stored in the memory 605 to perform the above transfer of digital assets from the account address corresponding to the first device to the account address corresponding to the second device according to the above transaction request and the asset value of the above multimedia data, including:

[0191] Obtain the distribution strategy of the value-added assets of the above multimedia data from the above blockchain according to the above transaction request;

[0192] Determine the asset quantity of digital assets required for the object corresponding to the first device to purchase the above multimedia data according to the above distribution strategy and the asset value of the above multimedia data;

[0193] Transfer the digital assets of the above asset quantity from the account address corresponding to the first device to the account address corresponding to the second device.

[0194] Optionally, the processor 601 may be used to call a computer program stored in the memory 605 to perform the above generation of the updated digital certificate of the above multimedia data, including:

[0195] Determine the share of the object corresponding to the first device for the above multimedia data according to the above distribution strategy;

[0196] Generate an initial digital certificate according to the above media attribute information and the second object attribute information of the object corresponding to the first device;

[0197] Add the share of the object corresponding to the first device to the above initial digital certificate to obtain the updated digital certificate of the above multimedia data.

[0198] Optionally, the processor 601 may be used to call a computer program stored in the memory 605 to execute the following steps further included in the above method:

[0199] Obtain a second similarity between the above multimedia data and historical multimedia data in the second database; the above historical multimedia data is multimedia data for which a corresponding digital certificate is recorded on the above blockchain;

[0200] When the above second similarity is less than the similarity threshold, determine that the above multimedia data belongs to the object corresponding to the above second device;

[0201] Generate an original digital certificate for the above multimedia data according to the first object attribute information of the object corresponding to the above second device and the above media attribute information, and store the original digital certificate in the above blockchain; the original digital certificate is used to indicate that the above multimedia data belongs to the object corresponding to the above second device.

[0202] Optionally, the processor 601 may be used to call a computer program stored in the memory 605 to execute the following steps further included in the above method:

[0203] Obtain update behavior operation data of the above multimedia data;

[0204] Determine the value-added assets of the above multimedia data according to the above update behavior operation data;

[0205] Obtain the latest digital certificate of the above multimedia data from the above blockchain; the latest digital certificate is a digital certificate with the smallest time interval between the recording time on the above blockchain and the current time;

[0206] Determine the owner of the above multimedia data and the share of ownership of the owner with respect to the above multimedia data according to the above latest digital certificate;

[0207] Allocate the above value-added assets to the owner according to the share of ownership of the owner with respect to the above multimedia data.

[0208] In this application, by pre-storing the behavioral operation data of the multimedia data and the first object attribute information of the owner of the multimedia data (i.e., the object corresponding to the second device) on the blockchain, the behavioral operation data and the first object attribute information have authenticity and immutability. Therefore, when the first device needs to purchase the multimedia data published by the second device on the media platform, predicting the asset value of the multimedia data based on the behavioral operation data and the first object attribute information on the blockchain is beneficial to improving the accuracy of the asset value of the multimedia data, avoiding malicious over-elevation of the asset value of the multimedia data by users, and improving the transaction security of the multimedia data. Further, according to the transaction request and the asset value of the multimedia data, digital assets are transferred from the account address corresponding to the first device to the account address corresponding to the second device, an updated digital voucher for the multimedia data is generated, and the updated digital voucher is stored on the blockchain. The updated digital voucher is used to indicate that the multimedia data belongs to the object corresponding to the first device. By generating the updated digital voucher, it is beneficial for the object corresponding to the first device to conduct transactions on the multimedia data again and is beneficial to realizing the traceability of the multimedia data.

[0209] In addition, it should be noted here that: The embodiments of the present application also provide a computer-readable storage medium, and the computer-readable storage medium stores a computer program executed by the aforementioned data processing device. The computer program includes program instructions. When the processor executes the program instructions, it can execute the description of the above data processing method in the corresponding previous embodiments. Therefore, it will not be elaborated here. In addition, the description of the beneficial effects of using the same method will not be elaborated either. For the technical details not disclosed in the embodiments of the computer-readable storage medium involved in the present application, please refer to the description of the method embodiments of the present application.

[0210] As an example, the above program instructions can be deployed to be executed on a computer device, or deployed to be executed on at least two computer devices at one location, or, executed on at least two computer devices distributed at least two locations and interconnected through a communication network. The at least two computer devices distributed at least two locations and interconnected through a communication network can form a blockchain network.

[0211] The above computer-readable storage medium may be the data processing device provided in any of the foregoing embodiments or the middle storage unit of the above computer device, such as the hard disk or middle memory of the computer device. The computer-readable storage medium may also be an external storage device of the computer device, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the computer device. Further, the computer-readable storage medium may also include both the middle storage unit and the external storage device of the computer device. The computer-readable storage medium is used to store the computer program and other programs and data required by the computer device. The computer-readable storage medium may also be used to temporarily store the data that has been output or is to be output.

[0212] In the embodiments of the present application, the terms "first", "second", etc. in the description, claims and drawings of the embodiments are used to distinguish the content in different media, rather than to describe a specific order. In addition, the term "comprising" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, device, product or equipment that includes a series of steps or units is not limited to the listed steps or modules, but may optionally further include steps or modules not listed, or may optionally further include other step units inherent to these processes, methods, devices, products or equipment.

[0213] In the embodiments of the present application, the term "module" or "unit" refers to a computer program with a predetermined function or a part of a computer program, which works together with other related parts to achieve a predetermined goal, and can be fully or partially implemented by using software, hardware (such as a processing circuit or a memory), or a combination thereof. Similarly, a processor (or multiple processors or memories) can be used to implement one or more modules or units. In addition, each module or unit can be a part of the overall module or unit that includes the function of the module or unit.

[0214] In the practical application of the relevant data collection and processing in this application, the informed consent or separate consent of the personal information subject should be obtained strictly in accordance with the requirements of relevant laws and regulations, and subsequent data use and processing behaviors should be carried out within the scope authorized by laws and regulations and the personal information subject.

[0215] The embodiments of the present application also provide a computer program product, including a computer program. When the computer program is executed by a processor, it implements the descriptions of the above data processing method and decoding method in the corresponding foregoing embodiments. Therefore, details will not be repeated here. In addition, the description of the beneficial effects of adopting the same method will not be repeated either. For the technical details not disclosed in the embodiments of the computer program product involved in the present application, please refer to the description of the method embodiments of the present application.

[0216] Those of ordinary skill in the art can realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be implemented by electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the composition and steps of the examples have been generally described according to functions in the above description. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0217] The methods and related devices provided by the embodiments of this application are described with reference to the method flowcharts and / or structural schematic diagrams provided by the embodiments of this application. Specifically, each process and / or block of the method flowchart and / or structural schematic diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable network-connected devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable network-connected devices generate a device for realizing the functions specified in Figure 1 one process or multiple processes and / or structural schematic Figure 1 one block or multiple blocks. These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable network-connected devices to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device, and the instruction device realizes the functions specified in Figure 1 one process or multiple processes and / or structural schematic Figure 1 one block or multiple blocks. These computer program instructions can also be loaded onto a computer or other programmable network-connected devices, so that a series of operation steps are executed on the computer or other programmable devices to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable devices provide steps for realizing the functions specified in Figure 1 one process or multiple processes and / or structural schematic one block or multiple blocks.

[0218] The above-disclosed are only the preferred embodiments of this application. Of course, the scope of the rights of this application cannot be limited thereby. Therefore, equivalent changes made according to the claims of this application still fall within the scope covered by this application.

Claims

1. A blockchain data processing method, characterized in that, Including: Receiving a transaction request for multimedia data published by a first device for a second device on a media platform; The transaction request carries media attribute information of the multimedia data; According to the media attribute information carried in the transaction request, obtaining behavior operation data about the multimedia data and first object attribute information of an object corresponding to the second device from a blockchain; Predicting the asset value of the multimedia data according to the behavior operation data and the first object attribute information; Transferring digital assets from an account address corresponding to the first device to an account address corresponding to the second device according to the transaction request and the asset value of the multimedia data, generating an updated digital certificate for the multimedia data, and storing the updated digital certificate on the blockchain; the updated digital certificate is used to indicate that the multimedia data belongs to an object corresponding to the first device.

2. The method according to claim 1, wherein The predicting the asset value of the multimedia data according to the behavior operation data and the first object attribute information includes: Invoking a value recognition model to perform label recognition on the multimedia data to obtain a predicted label of the multimedia data; Obtaining a first correlation degree between the predicted label of the multimedia data and a first labeled label; the first labeled label is a label concerned by an object corresponding to the first device; Predicting an additional value of the multimedia data according to the behavior operation data and the first object attribute information; Predicting the asset value of the multimedia data according to the first correlation degree and the additional value.

3. The method according to claim 2, wherein The predicting the asset value of the multimedia data according to the first correlation degree and the additional value includes Invoking the value recognition model to determine the content value of the multimedia data according to the first correlation degree; Obtaining weights corresponding to the content value and the additional value respectively; Performing a weighted summation process on the content value and the additional value according to the weights corresponding to the content value and the additional value respectively to obtain the asset value of the multimedia data.

4. The method according to claim 3, wherein The performing a weighted summation process on the content value and the additional value according to the weights corresponding to the content value and the additional value respectively to obtain the asset value of the multimedia data includes: Performing a weighted summation process on the content value and the additional value according to the weights corresponding to the content value and the additional value respectively to obtain an initial asset value of the multimedia data; Obtaining a first similarity degree between the multimedia data and reference media data in a first database; the reference media data is multimedia data that has been published on the media platform; Predicting an original value of the multimedia data according to the first similarity degree; Performing a summation process on the original value and the initial asset value to obtain the asset value of the multimedia data.

5. The method according to claim 2, wherein The method further includes: Obtaining historical behavior operation data and labeled asset values of sample multimedia data, and third object attribute information of a publisher of the sample multimedia data; Call the initial value recognition model to perform label recognition on the sample multimedia data to obtain the predicted labels of the sample multimedia data; Obtain the second correlation degree between the predicted labels of the sample multimedia data and the second annotation labels; the second annotation labels are obtained from the description information of the sample multimedia data; Predict the added value of the sample multimedia data according to the historical behavior operation data and the third object attribute information; Predict the asset value of the sample multimedia data according to the second correlation degree and the added value; Adjust the initial value recognition model according to the asset value of the sample multimedia data and the annotated asset value to obtain a value recognition model.

6. The method according to claim 5, wherein The adjusting the initial value recognition model according to the asset value of the sample multimedia data and the annotated asset value to obtain a value recognition model includes: Determine the asset prediction error of the initial value recognition model according to the asset value of the sample multimedia data and the annotated asset value; Determine the convergence state of the initial value recognition model according to the asset prediction error; When the convergence state of the initial value recognition model is the non-converged state, adjust the model parameters of the initial value recognition model according to the asset prediction error; Determine the adjusted initial value recognition model as the value recognition model.

7. The method according to claim 1, wherein The transferring digital assets from the account address corresponding to the first device to the account address corresponding to the second device according to the transaction request and the asset value of the multimedia data includes: According to the transaction request, obtain the distribution strategy of the value-added assets regarding the multimedia data from the blockchain; Determine the asset quantity of the digital assets that the object corresponding to the first device needs to pay to purchase the multimedia data according to the distribution strategy and the asset value of the multimedia data; Transfer the digital assets of the asset quantity from the account address corresponding to the first device to the account address corresponding to the second device.

8. The method according to claim 7, characterized in that, The generating the updated digital certificate of the multimedia data includes: Determine the occupancy share of the object corresponding to the first device for the multimedia data according to the distribution strategy; Generate an initial digital certificate according to the media attribute information and the second object attribute information of the object corresponding to the first device; Add the occupancy share of the object corresponding to the first device to the initial digital certificate to obtain the updated digital certificate of the multimedia data.

9. The method according to claim 1, wherein The method further includes: Obtain the second similarity between the multimedia data and the historical multimedia data in the second database; the historical multimedia data is the multimedia data for which the corresponding digital certificate is recorded on the blockchain; When the second similarity is less than the similarity threshold, determine that the multimedia data belongs to the object corresponding to the second device; Generate an original digital certificate of the multimedia data according to the first object attribute information of the object corresponding to the second device and the media attribute information, and store the original digital certificate in the blockchain; the original digital certificate is used to indicate that the multimedia data belongs to the object corresponding to the second device.

10. The method according to claim 1, wherein The method further includes: Obtain the update behavior operation data of the multimedia data; Determine the value-added assets of the multimedia data according to the update behavior operation data; Obtain the latest digital certificate of the multimedia data from the blockchain; the latest digital certificate is the digital certificate with the smallest time interval between the recorded time and the current time on the blockchain; Determine the owner of the multimedia data and the share of ownership of the multimedia data by the owner according to the latest digital certificate; Allocate the value-added assets to the owner according to the share of ownership of the multimedia data by the owner.

11. A blockchain data processing device, characterized in that, Includes: A receiving module, configured to receive a transaction request from a first device for multimedia data published by a second device on a media platform; The transaction request carries the media attribute information of the multimedia data; An obtaining module, configured to obtain, from the blockchain, the behavior operation data of the multimedia data and the first object attribute information of the object corresponding to the second device according to the media attribute information carried in the transaction request; A prediction module, configured to predict the asset value of the multimedia data according to the behavior operation data and the first object attribute information; A transfer module, configured to transfer digital assets from the account address corresponding to the first device to the account address corresponding to the second device according to the transaction request and the asset value of the multimedia data, generate an updated digital certificate of the multimedia data, and store the updated digital certificate in the blockchain; the updated digital certificate is used to indicate that the multimedia data belongs to the object corresponding to the first device.

12. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 10.

13. A computer storage medium, characterized in that, The computer storage medium stores a computer program, and when the computer program is executed by a processor, it executes the steps of the method according to any one of claims 1 to 10.

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