CN120258801A

CN120258801A - Blockchain data processing method, device, equipment and storage medium

Info

Publication number: CN120258801A
Application number: CN202410014677.4A
Authority: CN
Inventors: 梁军; 王宗友; 吴方; 蔡庆普; 时一防; 聂凯轩; 刘区城; 朱耿良; 廖志勇; 黄杨峻; 刘汉卿
Original assignee: Tencent Technology Shenzhen Co Ltd
Current assignee: Tencent Technology Shenzhen Co Ltd
Priority date: 2024-01-02
Filing date: 2024-01-02
Publication date: 2025-07-04

Abstract

The embodiment of the present application provides a blockchain data processing method, apparatus, device and storage medium, the method comprising: receiving a transaction request from a first device for multimedia data published by a second device in a media platform; obtaining behavioral operation data about the multimedia data and first object attribute information of an object corresponding to the second device from the blockchain according to the media attribute information carried by the transaction request; predicting the asset value of the multimedia data according to the behavioral operation data and the first object attribute information; 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, generating an updated digital certificate for the multimedia data, and storing the updated digital certificate on the blockchain. The present application can provide a reasonable asset value of multimedia data, avoid economic losses of buyers of multimedia data, and thus improve the transaction security of multimedia data.

Description

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

Technical Field

The present application relates to the field of computer technologies, and in particular, to a method, an apparatus, a device, and a storage medium for processing blockchain data.

Background

With the rapid development of multimedia data processing technology, multimedia data (such as images and videos) are becoming an integral part of people's work and study, and multimedia data not only can bring aesthetic feeling to users or provide useful information quantity, but also can bring economic value to users of multimedia data. For example, a user may trade multimedia data to obtain corresponding digital assets, but in the process of trading multimedia data, abnormal situations such as malicious lifting of asset value of the multimedia data by the user exist, so that economic loss is brought to purchasers of the multimedia data, and the trading security of the multimedia data is low.

Disclosure of Invention

The embodiment of the application provides a blockchain data processing method, a device, equipment and a storage medium, which can provide reasonable asset value of multimedia data, avoid economic loss of purchasers of the multimedia data and further improve transaction security of the multimedia data.

An aspect of an embodiment of the present application provides a blockchain data processing method, including:

receiving a transaction request of a first device for a second device to issue multimedia data in a media platform, wherein the transaction request carries media attribute information of the multimedia data;

acquiring behavior operation data about the multimedia data from a blockchain according to the media attribute information carried by the transaction request, and first object attribute information of an object corresponding to the second device;

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

Transferring a digital asset 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 of the multimedia data, and storing the updated digital certificate on a blockchain, wherein the updated digital certificate is used for indicating that the multimedia data belongs to an object corresponding to the first device.

An aspect of an embodiment of the present application provides a blockchain data processing device, including:

the receiving module is used for receiving a transaction request of the first equipment for the multimedia data issued by the second equipment in the media platform, wherein the transaction request carries the media attribute information of the multimedia data;

The acquisition module is used for acquiring behavior operation data about the multimedia data from a blockchain according to the media attribute information carried by the transaction request and first object attribute information of an object corresponding to the second device;

A prediction module for predicting an asset value of the multimedia data according to the behavior operation data and the first object attribute information;

And the transfer module is used for transferring the digital asset from the account address corresponding to the first equipment to the account address corresponding to the second equipment according to the transaction request and the asset value of the multimedia data, generating an updated digital certificate of the multimedia data, and storing the updated digital certificate on a blockchain, wherein the updated digital certificate is used for indicating that the multimedia data belongs to an object corresponding to the first equipment.

In one aspect, an embodiment of the present application provides a computer device, including a memory and a processor, where the memory stores a computer program, and the processor implements the steps of the method when executing the computer program.

In one aspect, embodiments of the present application provide a computer storage medium storing a computer program, where the computer program, when executed by a processor, performs the steps of the method. In the present application, by storing behavior operation data of multimedia data, and first object attribute information of an owner of the multimedia data (i.e., an object corresponding to a second device) on a blockchain in advance, the behavior operation data and the first object attribute information have authenticity and non-tamper ability. Therefore, when the first device needs to purchase the multimedia data released by the second device in the multimedia platform, the asset value of the multimedia data is predicted according to the behavior operation data and the first object attribute information on the blockchain, so that the accuracy of the asset value of the multimedia data is improved, the asset value of the multimedia data is prevented from being maliciously raised by a user, and the transaction safety of the multimedia data is improved. Further, according to the transaction request and the asset value of the multimedia data, transferring the digital asset from the account address corresponding to the first device to the account address corresponding to the second device, generating an updated digital certificate of the multimedia data, and storing the updated digital certificate on a blockchain, wherein the updated digital certificate is used for indicating that the multimedia data belongs to an object corresponding to the first device. By generating the updated digital certificate, the object corresponding to the first device is beneficial to transacting the multimedia data again, and the traceability of the multimedia data is beneficial to be realized.

Drawings

In order to more clearly describe the embodiments of the present application or the technical solutions in the background art, the following description will describe the drawings that are required to be used in the embodiments of the present application or the background art.

FIG. 1 is a block chain data processing system according to the present application;

FIG. 2 is a schematic diagram of an interaction scenario between devices of a blockchain data processing system provided by the present application;

FIG. 3 is a flow chart of a block chain data processing method provided by the present application;

FIG. 4 is a flow chart of another blockchain data processing method provided by the present application;

FIG. 5 is a schematic diagram of a block chain data processing apparatus according to the present application;

fig. 6 is a schematic structural diagram of a computer device according to the present application.

Detailed Description

The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. Based on the embodiments of the present application, one of ordinary skill in the art would obtain all other embodiments without undue burden, all falling within the scope of the present application.

Referring to fig. 1, fig. 1 is a schematic diagram of a block chain data processing system according to an embodiment of the present application. The blockchain data processing system may include a blockchain network and one or more terminals, the present application is not limited to the number of terminals, and the number of terminals may be set according to requirements, and in fig. 1, a case including 3 terminals is illustrated, including terminal 111, terminal 112 and terminal 113.

The terminals 111, 112, and 113 may each be provided with a multimedia platform, where the multimedia platform may be used for publishing, purchasing, selling multimedia data, and performing operations such as clicking, viewing, collecting, and commenting on the multimedia data by a user. For example, the terminal 111 may issue the multimedia data a in a multimedia platform, and when an object corresponding to the terminal 112 and an object corresponding to the terminal 111 have a social relationship, the terminal 112 may display the multimedia data a on 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 a node device in the blockchain network, where the node device is configured to execute the transaction request to complete a transaction for the multimedia data a. It should be noted that the multimedia data may refer to at least one of image data, video data, audio data, text data, and the like, and the multimedia platform may refer to an audio/video player, a content distribution application, a short video application, a live broadcast application, and the like.

It should be noted that, the social relationship may refer to a colleague relationship, a friend relationship, a parent relationship, a concern relationship, and the like, and the concern relationship may refer to that two objects pay attention to the subject corresponding to the same multimedia data together, or that two objects belong to the same communication group, and the like.

The blockchain network is an end-to-end decentralization network formed by a plurality of node devices (also called blockchain nodes), the number of the node devices in the blockchain network can be deployed according to actual requirements, the number of the node devices is not limited in the application, and as shown in fig. 1, the blockchain network comprises 4 node devices as an example, and the 4 node devices are respectively node device 101, node device 102, node device 103 and node device 104.

It is understood that the functions involved in each node device in a blockchain network include:

1) The routing, the node devices have basic functions for supporting communication between the node devices.

For example, as shown in fig. 1, data or block transmission may be performed between node devices through a network connection. The network connection between the node devices may perform data transmission based on the node identifiers, each node device has a node identifier corresponding to the node device, and each node device may store the node identifiers of other node devices having a connection relationship with itself, so as to broadcast the acquired data or the generated block to the other node devices according to the node identifiers of the other node devices, for example, the node device 101 may maintain a node identifier list, where the node identifier list stores node names and node identifiers of the other node devices, as shown in table 1:

TABLE 1

Node name	Node identification
		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
		...	...

The node identifier may be a protocol (Internet Protocol, IP) address of the interconnection between networks, and any other information that can be used to identify the node device in the blockchain network, and the IP address is only illustrated in table 1.

Assuming that the node identifier of the node device 101 is 117.Xxx.xxx.174, the node device 101 may send a data synchronization request to the node device 102 through the 117.Xxx.xxx.174, and the node device 102 may know that the data synchronization request is sent by the node device 101 through the node identifier 117.Xxx.xxx.174, and similarly, the node device 102 may send the transaction data a to the node device 101 through the node identifier 117. Xxx.145, and the node device 101 may know that the transaction data a is sent by the node device 101 through the node identifier 117.Xxx.xxx.145, and so on, and data transmission between other node devices will not be repeated.

2) The application is used for being deployed in a block chain to realize specific service according to actual service requirements, recording data related to the realization function to form recorded data, carrying a digital signature in the recorded data to represent the source of task data, sending the recorded data to other node equipment in the block chain network, and adding the recorded data into a temporary block when the source and the integrity of the recorded data are verified by the other node equipment.

For example, the services implemented by the application include:

2.1 The node device may include a resource client that may be configured to implement a resource management service function and to implement a communication connection with the de-centralized application client based on the resource management service function. The resource client is a tool for managing and storing digital resources of users, and can transfer digital resources to other accounts based on the resource client, for example, and can receive digital resources transferred to other accounts based on the resource client. The resource client may be a hardware device or a software program.

It will be appreciated that as various types of decentralized applications are widely deployed on the blockchain, the activities of users on the blockchain increase, and a typical user may log in using a blockchain key management tool when using the decentralized application, where the address in the blockchain key management tool corresponds to a user on the blockchain, the decentralized application may obtain the user address from the key management tool through some interfaces, and in order to solve the problem that Dapp background cannot trust the user address used when logging in the decentralized application.

2.2 The shared ledger is used for providing the functions of storing, inquiring, modifying and the like of account data (namely transaction data), sending record data of the operation of the account data to other nodes in the blockchain network, after the other nodes verify that the account data is valid, storing the record data into a temporary block as a response for acknowledging that the account data is valid, and also sending acknowledgement to node equipment initiating the operation.

For example, each node device may receive data to be logged while operating normally and maintain a shared ledger (i.e., blockchain) based on the received data to be logged. In order to ensure the information intercommunication in the shared ledger network, network connection can exist between each node device in the shared ledger network, and data transmission can be carried out between the node devices through the network connection. 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 verify the data to be recorded according to the consensus algorithm, and store the data to be recorded as the data in the shared ledger after the verification is successful (i.e. after the verification is completed), so that the data stored on all node devices in the shared ledger network are consistent.

2.3 A computerized agreement, which can execute the terms of a certain contract, through the implementation of codes deployed on a shared ledger for execution when certain conditions are met, for completing automated transactions, such as querying the physical distribution status of the goods purchased by the buyer, transferring the digital resources of the buyer to the merchant's address after the buyer signs the goods, and of course, intelligent contracts are not limited to executing contracts for transactions, but also executing contracts for processing the received information.

It should be noted that, the node device 101, the node device 102, the node device 103, and the node device 104 may be independent physical servers, or may be a server cluster or a distributed system formed by at least two physical servers, or may be a cloud server that provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and basic cloud computing services such as big data and artificial intelligent platforms. The terminal can comprise an intelligent terminal with a data processing function, such as a smart phone, a tablet computer, a notebook computer, a desktop computer, an intelligent voice interaction device, an intelligent household appliance (e.g. an intelligent television), a wearable device, a vehicle-mounted terminal and the like.

In the present application, any node device in a blockchain network may be used to transact multimedia data, specifically, taking the node device 101 as an example, the node device 101 may acquire behavior operation data of each multimedia data in a multimedia platform and object attribute information of an owner of each multimedia data, and a consensus node device in the blockchain network may perform consensus on the behavior operation data and the object attribute information, and store the acquired behavior operation data and object attribute information onto a blockchain when the consensus passes. The consensus here may be that the authenticity, the integrity, etc. of the behavior operation data and the object attribute information are verified, and when the authenticity and the integrity of the behavior operation data and the object attribute information are obtained, it is determined that the behavior operation data and the object attribute information are passed through the consensus.

Further, when the first device needs to purchase the multimedia data B that the second device publishes in the multimedia platform, the node device 101 may receive a transaction request of the first device for the multimedia data B that the second device publishes in the multimedia platform, read behavior operation data of the multimedia data B from the blockchain according to the transaction request, and first object attribute information of an object corresponding to the second device, predict an asset value of the multimedia data B according to the behavior operation data and the first object attribute information on the blockchain, thereby being beneficial to improving accuracy of the asset value of the multimedia data, avoiding a user from maliciously raising the asset value of the multimedia data, and improving transaction security of the multimedia data. Further, according to the transaction request and the asset value of the multimedia data B, transferring the digital asset from the account address corresponding to the first device to the account address corresponding to the second device, generating an updated digital certificate of the multimedia data B, and storing the updated digital certificate on a blockchain, where 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, the object corresponding to the first device is beneficial to transacting the multimedia data B again, and the traceability of the multimedia data B is beneficial to be realized.

Here, the first device may be a device for purchasing multimedia data, the first device may be any one of the terminal 111, the terminal 112, and the terminal 113, the second device may be a device for selling multimedia data, the second device may be any one of the terminal 111, the terminal 112, and the terminal 113, and the first device and the second device are different.

Referring to fig. 2, fig. 2 is a schematic diagram of an interaction scenario between devices of a blockchain data processing system according to an embodiment of the present application, where a node device 203 in fig. 2 may refer to any node device in the blockchain network in fig. 1, and a terminal 201 and a terminal 202 in fig. 2 may refer to different terminals in fig. 1. The node device 203 stores a blockchain 204, the terminals 201 and 202 are respectively provided with a multimedia platform, the object corresponding to the terminal 201 is a small piece, the object corresponding to the terminal 202 is a small piece, the small Zhang Yuxiao pieces have social relations, and the small Zhang Yuxiao pieces can mutually operate (view, purchase, click, collect, comment and the like) multimedia data published by each other.

In a specific implementation, the terminal 201 may present the published multimedia data C in a media page 205 in the multimedia platform in response to a publication request for the multimedia data C, the multimedia page 205 further comprising sales options for the multimedia data C. The selling option is used for selling the multimedia data C to other users, wherein the multimedia data C is a work finished by the king, namely, the multimedia data C is a creative work of the king. After the multimedia data C is published on the multimedia platform, the background service device of the multimedia platform may send the multimedia data C to an associated terminal corresponding to an object having a social relationship with the king, and the associated terminal may display the multimedia data C on the multimedia platform, and respond to a behavior operation for the multimedia data C, to generate behavior operation data, where the behavior operation includes praise, collection, comment, and the like, and the behavior operation data includes a behavior operation, a number of times corresponding to the behavior operation, and object attribute information possessed by the object performing the behavior operation. Then, the behavior operation data is synchronized to the terminal 201, the terminal 201 displays the behavior operation data in the media page 205, the terminal 201 may further send the behavior operation data of the multimedia data C and the object attribute information of the king to the node device 203, the node device 203 may send the behavior operation data and the object attribute information of the king to a consensus node device in the blockchain network, the consensus node device performs consensus on the behavior operation data and the object attribute information of the king, and when the behavior operation data and the object attribute information of the king are commonly passed, the node device 203 may store the behavior operation data and the object attribute information of the king on the blockchain 204.

As in fig. 2, the associated terminal includes a terminal 202, and after receiving the multimedia data C, the terminal 202 may present the multimedia data C, and behavior operation data of the multimedia data C in a multimedia page 206, where the multimedia page 206 further includes a purchase option, and the terminal 202 generates a transaction request for the multimedia data C in response to a trigger operation for the purchase option, where the transaction request carries media attribute information of the multimedia data C, and the media attribute information includes at least one of a media identifier, a media type, a data size, a release time, and the like of the multimedia data C. The terminal 202 may send a transaction request for the multimedia data C to the terminal 201, and the terminal 201 may verify whether the terminal 202 has the purchase right for the multimedia data C, e.g. when the verification results in the terminal 202 having the purchase right for the multimedia data C, the transaction request for the multimedia data C may be sent to the node device 203. In particular, here terminal 202 may also send a transaction request for multimedia data C directly to node device 203 in the blockchain network.

As in fig. 2, after receiving the transaction request about the multimedia data C, the node device 203 reads the behavior operation data about the multimedia data C and the object attribute information of the king from the blockchain 204 according to the media attribute information carried by the transaction request, and predicts the asset value of the multimedia data C according to the behavior operation data and the object attribute information. Transferring the digital asset from the account address of the sheetlet to the account address of the sheetlet according to the asset value and the transaction request, and generating an updated digital voucher 207 for the multimedia data, the updated digital voucher being stored on the blockchain, the updated digital voucher being used to indicate that the multimedia data belongs to the sheetlet.

Optionally, when the behavior operation data and the object attribute information of the king are commonly known, the node device 203 may generate an original digital certificate of the multimedia data C, and store the original digital certificate into the blockchain 204, where the original digital certificate may be used to indicate that the multimedia data C belongs to the king. After the node device 203 generates the updated digital voucher, the original digital voucher for the multimedia data C is invalidated.

In summary, by storing behavior operation data of multimedia data in advance, and object attribute information of an owner of the multimedia data on a blockchain, it is possible to ensure the authenticity and the non-tamper ability of the behavior operation data and the first object attribute information. In the process of trading the multimedia data, the asset value of the multimedia data is predicted according to the behavior operation data and the object attribute information on the blockchain, so that the accuracy of the asset value of the multimedia data is improved, the user is prevented from maliciously raising the asset value of the multimedia data, and the trading safety of the multimedia data is improved. Meanwhile, in the process of trading multimedia data, the updating digital certificate of the multimedia data is generated, so that the multimedia data can be traded again, and the traceability of the multimedia data can be realized.

Fig. 3 is a flowchart of a block chain data processing method according to an embodiment of the present application. The present application may be performed by any node device in the blockchain network of fig. 1. Wherein, the method can comprise the following steps:

S301, receiving a transaction request of the first device for the multimedia data issued by the second device in the media platform, wherein the transaction request carries media attribute information of the multimedia data.

The transaction request further includes an account address of the object corresponding to the first device, an IP address of the first device, an account address of the object corresponding to the second device, an IP address of the second device, and the like. The media attribute information of the multimedia data may include a media identifier, a media type, a size, etc. of the multimedia data.

It should be noted that, the multimedia data may be a creative work of an object corresponding to the second device, that is, the second device is first displayed in the multimedia platform, where the multimedia data is captured by the second device, or the multimedia data may be generated by the second device. The multimedia data may be a non-creative work of the object corresponding to the second device, such as purchased by the object corresponding to the second device.

It can be appreciated that when the first device detects a triggering operation of an object corresponding to the first device on a transaction option related to multimedia data on a media platform, a transaction request for the multimedia data issued by the second device in the media platform can be generated, and the transaction request is sent to a node device in the blockchain network, and the node device can receive the transaction request for the multimedia data issued by the first device in the media platform by the second device.

Optionally, a second similarity between the multimedia data and historical multimedia data in a second database is obtained, the historical multimedia data is multimedia data with corresponding digital certificates recorded on the blockchain, when the second similarity is smaller than a similarity threshold, the multimedia data is determined to belong to an object corresponding to the second device, an original digital certificate of the multimedia data is generated according to first object attribute information of the object corresponding to the second device and the media attribute information, the original digital certificate is stored in the blockchain, and the original digital certificate is used for indicating that the multimedia data belongs to the object corresponding to the second device.

It should be noted that the second database is configured to store multimedia data with corresponding digital certificates recorded on the blockchain, where the second similarity may be obtained by a similarity algorithm, where the similarity algorithm specifically includes cosine similarity, jaccard similarity coefficient, euclidean distance, and the like, and the similarity threshold may be set by the node device or stored in the blockchain. The first object attribute information may include user information of an object corresponding to the second device, the user information including a user name, a user level, and the like.

It can be understood that after the second device publishes the multimedia data to the multimedia platform, the node device may obtain the historical multimedia data in the second database, and calculate the similarity between the multimedia data and the historical multimedia data by using a similarity algorithm, and record the similarity as the second similarity. And when the second similarity is smaller than the similarity threshold, the multimedia data is indicated to not generate the digital certificate, and the multimedia data is the original work of the object corresponding to the second equipment. The node device can 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 into the blockchain, wherein the original digital certificate is used for indicating that the multimedia data belongs to the object corresponding to the second device, and can prevent the multimedia data from being used by illegal users through the original digital certificate, so that copyright protection of the multimedia data and security of the multimedia data are realized.

It should be noted that the original digital certificate may include verifiability, transparent execution, validity, non-falsification, accessibility, and tradable property for the ownership certificate of the multimedia data, where the original digital certificate includes a unique identifier of the multimedia data, and object attribute information corresponding to the second device and media attribute information of the multimedia data.

Optionally, acquiring historical behavior operation data and labeling asset value of the sample multimedia data and third object attribute information of a publisher of the sample multimedia data, calling an initial value identification model, carrying out tag identification on the sample multimedia data to obtain a prediction tag of the sample multimedia data, acquiring a second association degree between the prediction tag of the sample multimedia data and a second labeling tag, acquiring description information of the sample multimedia data by the second labeling tag, predicting additional value of the sample multimedia data according to the historical behavior operation data and the third object attribute information, predicting asset value of the sample multimedia data according to the second association degree and the additional value, and adjusting the initial value identification model according to the asset value of the sample multimedia data and the labeling asset value to obtain a value identification model.

It can be understood that the initial value recognition model is a value recognition model with lower accuracy, i.e. there is a large error in asset value of multimedia data predicted by the initial value recognition model. In order to improve the accuracy of the prediction of the initial value model and reduce the prediction error, the node equipment can obtain a value recognition model with higher accuracy by training the initial value recognition model. Specifically, the node device may obtain historical behavior operation data and labeling asset value of the sample multimedia data from the blockchain, and third object attribute information of the publisher of the sample multimedia data. And inputting the sample multimedia data into an initial value recognition model, and performing tag recognition on the sample multimedia data through the initial value recognition model to obtain a prediction tag of the sample multimedia data. The prediction tag of the sample multimedia data is used for reflecting the media type of the sample multimedia data, a similarity algorithm is adopted to obtain a second association degree between the prediction tag of the sample multimedia data and a second labeling tag, and the second labeling tag is obtained from the description information of the sample multimedia data, namely the second labeling tag can refer to a keyword reflecting the media type of the sample multimedia data in the description information.

Further, the added value of the sample multimedia data is predicted based on the historical behavior operation data and the third object attribute information, and the asset value of the sample multimedia data is predicted based on the second degree of association and the added value. If the asset value of the sample multimedia data is similar to the labeling asset value, the value prediction accuracy of the initial value recognition model is higher, and if the asset value of the sample multimedia data is different from the labeling asset value, the value prediction accuracy of the initial value recognition model is lower. Therefore, the computer equipment can adjust 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. And training the initial value recognition model to obtain a value recognition model, so that the value recognition accuracy of the value recognition model is improved.

The historical time period may refer to a week, a month, a day, etc., and the third object attribute information may include a user name, a user level, etc. of the publisher of the sample multimedia data.

Optionally, determining an asset prediction error of the initial value recognition model according to the asset value of the sample multimedia data and the labeled asset value, determining a convergence state of the initial value recognition model according to the asset prediction error, adjusting model parameters of the initial value recognition model according to the asset prediction error when the convergence state of the initial value recognition model is in an unconverged state, and determining the adjusted initial value recognition model as a value recognition model.

It can be understood that the node device inputs the asset value of the marked asset value and the asset value of the sample multimedia data into the loss function of the initial value recognition model to obtain the asset prediction error of the initial value recognition model, wherein the asset prediction error is used for reflecting the value recognition accuracy of the initial value recognition model, namely, the larger the asset prediction error is, the lower the value recognition accuracy of the initial value recognition model is, and the lower the asset prediction error is, the higher the value recognition accuracy of the initial value recognition model is. Further, the node device can determine the convergence state of the initial value recognition model according to the asset prediction error, wherein the convergence state of the initial value recognition model comprises a converged state and an unconverged state, the converged state reflects that the asset prediction error of the initial value recognition model is the lowest, and the unconverged state reflects that the asset prediction error of the initial value recognition model is not the lowest. When the convergence state of the initial value recognition model is the converged state, the node device may use the initial value recognition model as the value recognition model. When the convergence state of the initial value recognition model is an unconverged state, the node device may adjust the model parameters of the initial value recognition model according to the asset prediction error until the convergence state of the adjusted initial value recognition model is a converged state, or the number of times of adjustment of the model parameters of the initial value recognition model is greater than a threshold, and the node device may determine the adjusted initial value recognition model as the value recognition model, thereby improving the value recognition accuracy of the value recognition model.

S302, 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 device are obtained from the blockchain.

It should be noted that, the first object attribute information may include user information of an object corresponding to the second device, where the user information includes a user name, a user class, and the like. The behavior operation data include data such as number of comments, number of praise, number of forwarding, etc. for the multimedia data.

It can be understood that after the node device receives a transaction request of the first device for the second device to issue the multimedia data in the media platform, the node device may obtain, according to the media attribute information of the multimedia data, behavior operation data about the multimedia data from the blockchain, and first object attribute information of an object corresponding to the second device. The behavior operation data can reflect the preference degree of a user on the media platform for the media data, and the first object attribute information can reflect the popularity degree of an object corresponding to the second device on the media platform, so that the multimedia data can be comprehensively known through the behavior operation data and the first object attribute information.

S303, predicting the asset value of the multimedia data according to the behavior operation data and the first object attribute information.

It can be understood that the node device may analyze the preference of the user of the media platform for the multimedia data according to the behavior operation data, analyze the popularity of the object corresponding to the second device on the media platform according to the attribute information of the first object, and predict the asset value of the multimedia data according to the above analysis, where the asset value may refer to the number of assets corresponding to the digital assets required for purchasing 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 resulting multimedia data.

S304, transferring the digital asset from the account address corresponding to the first equipment to the account address corresponding to the second equipment according to the transaction request and the asset value of the multimedia data, generating an updated digital certificate of the multimedia data, and storing the updated digital certificate on the blockchain.

It should be noted that the account address may be used to receive and store digital assets, generated by a private key through a specific algorithm. The update digital certificate may include a unique identifier of the multimedia data, and object attribute information and media attribute information of an object corresponding to the first 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 of the object corresponding to the first device, and store the updated digital certificate on a blockchain, wherein the updated digital certificate is used for indicating 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 asset in the account address corresponding to the first device is directly transferred to the account address corresponding to the second device, and the update digital certificate is generated, so that the object corresponding to the first device is facilitated to transact the multimedia data again, and the traceability of the multimedia data is facilitated.

Optionally, according to the transaction request, acquiring an allocation policy of value-added assets about the multimedia data from the blockchain, determining the number of assets of digital assets required to be paid by the object corresponding to the first device for purchasing the multimedia data according to the allocation policy and the asset value of the multimedia data, and transferring the digital assets of the number of assets from the account address corresponding to the first device to the account address corresponding to the second device.

It should be noted that the above value-added asset may be an increased portion of the asset value of the multimedia data within a period of time, the above allocation policy may be an allocation proportion, and the value-added asset may be determined according to new behavior operation data of the multimedia data, where the new behavior operation data may be generated after generating the updated digital certificate of the multimedia data.

It can be understood that when the object corresponding to the first device purchases the multimedia data, there may be multiple purchasing modes, where the purchasing modes include purchasing the use right of the multimedia data, purchasing the adapting right of the multimedia data, etc., and in different purchasing modes, the value added assets of the multimedia data available to the object corresponding to the first device are different, and the asset amount of the digital asset that the object corresponding to the first device needs to pay when purchasing is also different. Therefore, when transferring the digital asset to the account address of the object corresponding to the second device, the node device may obtain, from the blockchain, an allocation policy of the value-added asset corresponding to the purchase mode with respect to the multimedia data according to the purchase mode of the object corresponding to the first device, and determine, according to the allocation proportion recorded in the allocation policy, the allocation proportion of the object corresponding to the first device with respect to the value-added asset of the multimedia data. And the node equipment determines the number of the assets of the digital assets required to be paid by the object corresponding to the first equipment for purchasing the multimedia data according to the asset value of the multimedia data and the distribution proportion, and transfers the digital assets of the number of the assets from the account address corresponding to the first equipment to the account address corresponding to the second equipment. By determining the distribution strategy of the value added assets of the multimedia data through the purchasing mode, the asset quantity of the digital assets required to be paid by the object corresponding to the first equipment for purchasing the multimedia data is determined, and the transaction fairness of the multimedia data can be improved.

For example, the object corresponding to the first device purchases the recomposition right of the multimedia data, the allocation proportion of the value added asset corresponding to the recomposition right with respect to the multimedia data is 1:1, so that the allocation proportion of the object corresponding to the first device and the object corresponding to the second device with respect to the value added asset of the multimedia data is 1:1, the asset value of the multimedia data is 100, the node device determines that the number of the digital asset required to be paid by the object corresponding to the first device for purchasing the multimedia data is 50% (namely 50) of the asset value, and the node device transfers the digital asset with the number of 50 from the account address corresponding to the first device to the account address corresponding to the second device.

Optionally, determining an occupied share of the object corresponding to the first device with respect to the multimedia data according to the allocation policy, generating 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 adding the occupied share of the object corresponding to the first device to the initial digital certificate to obtain an updated digital certificate of the multimedia data.

The second object attribute information may include user information of an object corresponding to the first device, where the user information includes a user name, a user class, and the like. The initial digital certificate may include the attribute information of the second object, the attribute information of the multimedia data, and the unique identifier. The unique identification is used to indicate the uniqueness of the initial digital credential.

It can be understood that the allocation policy may also indicate an occupancy share of the owner with respect to the multimedia data, so that the node device may determine, according to the allocation policy, an occupancy share of the object corresponding to the first device with respect to the multimedia data, the node device may 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, where the initial digital certificate includes a unique identifier of the multimedia data, and add the occupancy share of the object corresponding to the first device with respect to the multimedia data to the initial digital certificate, thereby obtaining an updated digital certificate of the multimedia data.

For example, if the allocation policy of the object corresponding to the first device and the object corresponding to the second device with respect to the multimedia data is 1:1, the occupancy share of the object corresponding to the first device with respect to the multimedia data is 50%. The 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 occupied share (namely 50%) to the initial digital certificate to obtain the updated digital certificate of the multimedia data.

Optionally, the method comprises the steps of obtaining update behavior operation data of the multimedia data, determining value added assets of the multimedia data according to the update behavior operation data, obtaining the latest digital certificates of the multimedia data from the blockchain, wherein the latest digital certificates are digital certificates with the minimum time interval between the recording time and the current time on the blockchain, determining owners of the multimedia data according to the latest digital certificates, determining the share of the owners of the multimedia data relative to the multimedia data, and distributing the value added assets to the owners according to the share of the owners relative to the multimedia data.

It should be noted that the update behavior operation data may be behavior operation data of multimedia data in an update period, where the update period may be a period from a time node generating the update digital certificate to a current time node. The latest digital certificate is used for indicating the current owner of the multimedia data, the owner can be one object or a plurality of objects, the owner can obtain the value added asset of the multimedia data, and the latest digital certificate comprises the share of the owner for the multimedia data. It is appreciated that the asset value of the multimedia data may change over time after the updated digital voucher is generated, and thus, value added assets of the multimedia data may be generated. To determine that an accurate value added asset is obtained, the value added asset is reasonably distributed to the owners. The node equipment acquires behavior operation data of the multimedia data in an updating time period from the blockchain, namely, data such as comment times, praise times, forwarding times and the like generated after the digital certificate is updated, and determines the value added asset of the multimedia data. Further, the node device obtains the latest digital certificate of the multimedia data from the blockchain, and determines the user name of the owner of the current multimedia data and the account address of the owner from the latest digital certificate. The node device may also obtain the share of the owner for the multimedia data from the latest digital voucher. The node equipment determines the asset amount of the value-added asset about the multimedia data which is available to the owner according to the share of the owner for the multimedia data and the asset amount of the value-added asset, and transfers the digital asset of the asset amount corresponding to the owner to the account address of the corresponding owner. Therefore, the value-added asset can be prevented from being distributed to the account addresses of irrelevant objects, and the distribution fairness of the value-added asset of the multimedia data is improved.

In the present application, by storing behavior operation data of multimedia data, and first object attribute information of an owner of the multimedia data (i.e., an object corresponding to a second device) on a blockchain in advance, the behavior operation data and the first object attribute information have authenticity and non-tamper ability. Therefore, when the first device needs to purchase the multimedia data released in the media platform by the second device, the asset value of the multimedia data is predicted according to the behavior operation data and the first object attribute information on the blockchain, so that the accuracy of the asset value of the multimedia data is improved, the asset value of the multimedia data is prevented from being maliciously raised by a user, and the transaction safety of the multimedia data is improved. Further, according to the transaction request and the asset value of the multimedia data, transferring the digital asset from the account address corresponding to the first device to the account address corresponding to the second device, generating an updated digital certificate of the multimedia data, and storing the updated digital certificate on a blockchain, wherein the updated digital certificate is used for indicating that the multimedia data belongs to an object corresponding to the first device. By generating the updated digital certificate, the object corresponding to the first device is beneficial to transacting the multimedia data again, and the traceability of the multimedia data is beneficial to be realized.

Fig. 4 is a flowchart of a block chain data processing method according to an embodiment of the present application. The present application may be performed by any node device in the blockchain network of fig. 1. Wherein, the method can comprise the following steps:

S401, a transaction request of the first device for the multimedia data issued by the second device in the media platform is received, wherein the transaction request carries media attribute information of the multimedia data.

S402, 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 device are obtained from the blockchain.

S403, calling a value recognition model, and performing tag recognition on the multimedia data to obtain a prediction tag of the multimedia data.

It should be noted that the value recognition model described above may be used to predict asset value of multimedia data. The predictive label is used for reflecting the media type of the sample multimedia data.

It can be understood that in order to more accurately predict the asset value of the multimedia data, the node device obtains the behavior operation data about the multimedia data and the first object attribute information from the blockchain, inputs the multimedia data into the value recognition model, and performs tag recognition on the multimedia data through the value recognition model, so as to obtain the prediction tag of the multimedia data.

S404, acquiring a first association degree between the prediction label and the first labeling label of the multimedia data.

It should be noted that, the first label is a label of interest of the object corresponding to the first device, that is, in the media platform, a media type of the multimedia data of interest of the object corresponding to the first device. The first relevance may be obtained by a relevance algorithm, and the relevance algorithm may include a cosine similarity algorithm, a pearson correlation coefficient algorithm, a euclidean distance algorithm, and the like.

It can be understood that after obtaining the prediction tag of the multimedia data, the node device obtains a first label tag from the media type of the content multimedia data concerned by the object corresponding to the first device, and obtains a first association degree between the prediction tag and the first label tag by adopting a similarity algorithm.

S405, predicting the added value of the multimedia data according to the behavior operation data and the first object attribute information.

It is understood that the node device operates on the data according to the behavior. The method comprises the steps of analyzing the favorites of a user of a media platform for multimedia data, analyzing the popularity of an object corresponding to second equipment on the media platform according to the attribute information of a first object, and predicting the added value of the multimedia data according to the analysis. Through the behavior operation data and the first object attribute information, the popularity of the multimedia data can be known, and the higher the popularity is, the higher the asset value of the multimedia data can be, so that the asset value with high accuracy can be obtained.

S406, predicting the asset value of the multimedia data according to the first association degree and the added value.

It should be noted that, the first relevance may be used to indicate a relevance between the multimedia data and the multimedia data focused on by the object corresponding to the first device, and the asset value of the multimedia data with high relevance may provide a reference for predicting the asset value of the multimedia data.

It is understood that the node device inputs the first association degree and the added value into a value recognition model, and the asset value of the multimedia data can be obtained through the value recognition model.

Optionally, the value recognition model is called, the content value of the multimedia data is determined according to the first association degree, weights corresponding to the content value and the added value are obtained, and the asset value of the multimedia data is obtained by carrying out weighted summation processing on the content value and the added value according to the weights corresponding to the content value and the added value.

It should be noted that, the above weight may refer to a ratio of the content value and the added value in the asset value, and the weight may be set by the value recognition model.

It can be understood that the asset values of the multimedia data of the same media type are not necessarily consistent, so that the asset values of the multimedia data with high correlation are not necessarily consistent, in order to predict and obtain the asset value with higher accuracy, the node device can determine the content value of the multimedia data through the first correlation, acquire weights corresponding to the content value and the added value respectively, namely acquire the proportion of the content value and the added value in the asset value respectively, multiply the content value with the corresponding proportion, multiply the added value with 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 added value is 120, the ratio of the content value to the added value in the asset value is 40% and 60%, respectively, so that the content value is multiplied by the corresponding ratio (i.e., 100 to 40%), the added value is multiplied by the corresponding ratio (i.e., 120 to 60%), and the multiplied results are added to obtain the asset value of 112 of the multimedia data. The asset value of the multimedia data is determined through the weights corresponding to the content value and the added value respectively, so that the condition that the asset value of the multimedia data is too high or too low due to the fact that any one of the content value and the added value is too high or too low is avoided, and the accuracy of the asset value of the multimedia data is improved.

Optionally, weighting and summing the content value and the added value according to weights corresponding to the content value and the added value respectively to obtain an initial asset value of the multimedia data, obtaining a first similarity between the multimedia data and reference media data in a first database, wherein the reference media data is multimedia data published in the media platform, predicting an original value of the multimedia data according to the first similarity, and summing the original value and the initial asset value to obtain an asset value of the multimedia data.

It should be noted that, the first database is configured to store multimedia data published in the media platform, and the first similarity may be obtained by a similarity algorithm, where the similarity algorithm specifically includes cosine similarity, jaccard similarity coefficient, euclidean distance, and the like. The originality of the multimedia data is higher, and the originality of the multimedia data is higher.

It can be understood that the node device determines the proportion 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 weighted summation processing on the content value and the additional value, so as to obtain the initial asset value of the multimedia data. The node device may obtain the reference multimedia data in the first database, and obtain a first similarity between the multimedia data and the reference multimedia data in the first database by adopting a similarity algorithm. The node device predicts an original value of the multimedia data based on the first similarity. The lower the first similarity, the higher the original value of the multimedia data, and conversely, the higher the first similarity, 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, the problem that the asset value of the multimedia data is inaccurate due to inaccurate content value caused by the fact that the multimedia data is high in originality and few in associated multimedia data and the object corresponding to the first device does not pay attention to the multimedia data associated with the multimedia data is avoided.

S407, transferring the digital asset from the account address corresponding to the first equipment to the account address corresponding to the second equipment according to the transaction request and the asset value of the multimedia data, generating an updated digital certificate of the multimedia data, and storing the updated digital certificate on the blockchain.

Fig. 5 is a schematic structural diagram of a blockchain data processing device according to an embodiment of the present application. As shown in fig. 5, the blockchain data processing device may include:

a receiving module 511, configured to receive a transaction request issued by a first device for a second device for multimedia data in a media platform, where the transaction request carries media attribute information of the multimedia data;

an obtaining module 512, configured to obtain, from a blockchain, behavior operation data related to the multimedia data and first object attribute information of an object corresponding to the second device according to media attribute information carried by the transaction request;

a prediction module 513 for predicting an asset value of the multimedia data according to the behavior operation data and the first object attribute information;

And a transferring module 514, configured to transfer a digital asset 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 a blockchain, where the updated digital certificate is used to indicate that the multimedia data belongs to an object corresponding to the first device.

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

Calling a value recognition model, and performing tag recognition on the multimedia data to obtain a prediction tag of the multimedia data;

Acquiring a first association degree between a prediction tag and a first labeling tag of the multimedia data, wherein the first labeling tag is a tag focused on an object corresponding to the first equipment;

predicting added value of the multimedia data according to the behavior operation data and the first object attribute information;

and predicting the asset value of the multimedia data according to the first association degree and the added value.

Optionally, the predicting module 513 predicts the asset value of the multimedia data according to the first association degree and the added value, including:

calling the value recognition model, and determining the content value of the multimedia data according to the first association degree;

acquiring weights corresponding to the content value and the added value respectively;

and weighting and summing the content value and the added value according to weights respectively corresponding to the content value and the added value to obtain the asset value of the multimedia data.

Optionally, the predicting module 513 performs weighted summation processing on the content value and the added value according to weights corresponding to the content value and the added value, to obtain an asset value of the multimedia data, where the weighted summation processing includes:

weighting and summing the content value and the added value according to weights respectively corresponding to the content value and the added value to obtain an initial asset value of the multimedia data;

Acquiring a first similarity between the multimedia data and reference media data in a first database, wherein the reference media data is multimedia data published in the media platform;

Predicting the original value of the multimedia data according to the first similarity;

and summing the original value and the initial asset value to obtain the asset value of the multimedia data.

Optionally, the prediction module 513 is further configured to include:

Acquiring historical behavior operation data and labeling asset value of sample multimedia data, and third object attribute information of a publisher of the sample multimedia data;

calling an initial value identification model, and carrying out tag identification on the sample multimedia data to obtain a prediction tag of the sample multimedia data;

acquiring a second association degree between a prediction tag and a second labeling tag of the sample multimedia data, wherein the second labeling tag is acquired from description information of the sample multimedia data;

Predicting the added value of the sample multimedia data according to the historical behavior operation data and the third object attribute information;

predicting asset value of the sample multimedia data according to the second association degree and the added value;

and adjusting 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.

Optionally, the predicting module 513 adjusts the initial value recognition model according to the asset value of the sample multimedia data and the tagged asset value to obtain a value recognition model, including:

determining an asset prediction error of the initial value recognition model according to the asset value of the sample multimedia data and the marked asset value;

Determining a 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 an unconverged state, the prediction module 513 adjusts model parameters of the initial value recognition model according to the asset prediction error;

And determining the adjusted initial value recognition model as a value recognition model.

Optionally, the transferring module 514 transfers the digital asset 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:

Acquiring a value added asset allocation strategy related to the multimedia data from the blockchain according to the transaction request;

Determining the number of assets of the digital asset to be paid by the object corresponding to the first device for purchasing the multimedia data according to the distribution strategy and the asset value of the multimedia data;

transferring the digital assets of the asset quantity from the account address corresponding to the first equipment to the account address corresponding to the second equipment.

Optionally, the transferring module 514 generates updated digital certificates of the multimedia data, including:

determining the occupancy share of the object corresponding to the first equipment for the multimedia data according to the allocation strategy;

generating an initial digital certificate according to the media attribute information and second object attribute information of an object corresponding to the first device;

and adding the occupied share of the object corresponding to the first equipment to the initial digital certificate to obtain the updated digital certificate of the multimedia data.

Optionally, the method further comprises:

Acquiring a second similarity between the multimedia data and historical multimedia data in a second database, wherein the historical multimedia data is multimedia data on which the corresponding digital certificate is recorded on the blockchain;

When the second similarity is smaller than a similarity threshold, determining that the multimedia data belongs to an object corresponding to the second device;

Generating 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 storing the original digital certificate into the blockchain, wherein the original digital certificate is used for indicating that the multimedia data belongs to the object corresponding to the second device.

Optionally, the method further comprises:

acquiring the update behavior operation data of the multimedia data;

determining value added assets of the multimedia data according to the updating behavior operation data;

the latest digital certificate of the multimedia data is obtained from the block chain, wherein the latest digital certificate is a digital certificate with the minimum time interval between the recording time and the current time on the block chain;

Determining an owner of the multimedia data and an occupancy share of the owner for the multimedia data according to the latest digital certificate;

and distributing the value-added asset to the owner according to the share of the owner for the multimedia data.

Fig. 6 is a schematic structural diagram of a computer device according to an embodiment of the present application. As shown in fig. 6, the computer device 600 may refer to a server or terminal, including a processor 601, a network interface 604, and a memory 605, and the computer device 600 may further include a user interface 603, and at least one communication bus 602. Wherein the communication bus 602 is used to enable connected communications between these components. In some embodiments, the user interface 603 may include a Display screen (Display), a Keyboard (Keyboard), and the optional user interface 603 may further include a standard wired interface, a wireless interface, among others. The network interface 604 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). The Memory 605 may be a high-speed RAM Memory or a nonvolatile Memory (non-volatile Memory), such as at least one magnetic disk Memory. The memory 605 may also optionally be at least one storage device remote from the processor 601. As shown in fig. 6, an operating system, a network communication module, a user interface module, and a computer program may be included in the memory 605, which is a computer-readable storage medium.

In the computer device 600 shown in fig. 6, the network interface 604 may provide network communication functions, while the user interface 603 is mainly used for providing an interface for input, and the processor 601 may be used for calling a computer program stored in the memory 605 to execute:

Optionally, the processor 601 may be configured to invoke a computer program stored in the memory 605 to execute the above-mentioned operation data according to the above-mentioned behavior and the above-mentioned first object attribute information, and predict the asset value of the above-mentioned multimedia data, including:

Optionally, the processor 601 may be configured to invoke a computer program stored in the memory 605 to perform the predicting the asset value of the multimedia data according to the first association and the added value, including:

Optionally, the processor 601 may be configured to invoke a computer program stored in the memory 605 to execute the weighting corresponding to the content value and the added value, and perform a weighted summation process on the content value and the added value to obtain an asset value of the multimedia data, where the method includes:

Optionally, the processor 601 may be configured to invoke a computer program stored in the memory 605 to perform the above method further comprising:

Optionally, the processor 601 may be configured to invoke a computer program stored in the memory 605 to execute the adjusting the initial value recognition model according to the asset value of the sample multimedia data and the tagged asset value to obtain a value recognition model, including:

When the convergence state of the initial value recognition model is a non-convergence state, adjusting model parameters of the initial value recognition model according to the asset prediction error;

Optionally, the processor 601 may be configured to invoke a computer program stored in the memory 605 to execute the transferring the digital asset 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:

Optionally, the processor 601 may be configured to invoke a computer program stored in the memory 605 to execute the above-mentioned update digital certificate that generates the above-mentioned multimedia data, including:

acquiring the update behavior operation data of the multimedia data;

In addition, it should be noted that the embodiment of the present application further provides a computer readable storage medium, where the computer readable storage medium stores a computer program executed by the aforementioned data processing apparatus, and the computer program includes program instructions, when the processor executes the program instructions, the processor can execute the description of the data processing method in the corresponding embodiment, and therefore, a description will not be given here. In addition, the description of the beneficial effects of the same method is omitted. For technical details not disclosed in the embodiments of the computer-readable storage medium according to the present application, please refer to the description of the method embodiments of the present application.

As an example, the above-described program instructions may be executed on one computer device or at least two computer devices disposed at one site, or at least two computer devices distributed at least two sites and interconnected by a communication network, which may constitute a blockchain network.

The computer readable storage medium may be the data processing apparatus provided in any of the foregoing embodiments or a middle storage unit of the foregoing computer device, for example, a hard disk or a 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 memory card (SMART MEDIA CARD, SMC), a Secure Digital (SD) card, a flash memory card (FLASH CARD), etc. that are provided on the computer device. Further, the computer-readable storage medium may also include both a central storage unit and an 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 data that has been output or is to be output.

The terms first, second and the like in the description and in the claims and drawings of embodiments of the application, are used for distinguishing between different media and not necessarily for describing a particular sequential or chronological order. Furthermore, the term "include" and any variations thereof is intended to cover a non-exclusive inclusion. For example, a process, method, apparatus, article, or device that comprises a list of steps or elements is not limited to the list of steps or modules but may, in the alternative, include other steps or modules not listed or inherent to such process, method, apparatus, article, or device.

In the present embodiment, the term "module" or "unit" refers to a computer program or a part of a computer program having a predetermined function and working together with other relevant parts to achieve a predetermined object, and may be implemented in whole or in part by using software, hardware (such as a processing circuit or a memory), or a combination thereof. Also, a processor (or multiple processors or memories) may be used to implement one or more modules or units. Furthermore, each module or unit may be part of an overall module or unit that incorporates the functionality of the module or unit.

The relevant data collection and processing in the application can obtain the informed consent or independent consent of the personal information body according to the requirements of relevant laws and regulations when the example is applied, and develop the subsequent data use and processing behaviors within the authorized range of laws and regulations and the personal information body.

The embodiment of the present application further provides a computer program product, which includes a computer program, where the computer program when executed by a processor implements the descriptions of the data processing method and the decoding method in the foregoing corresponding embodiments, and therefore, a detailed description will not be given here. In addition, the description of the beneficial effects of the same method is omitted. For technical details not disclosed in the embodiments of the computer program product according to the present application, reference is made to the description of the method embodiments according to the present application.

Those of ordinary skill in the art will appreciate that the elements and algorithm steps described in connection with the embodiments disclosed herein may be embodied in electronic hardware, in computer software, or in a combination of the two, and that the elements and steps of the examples have been generally described in terms of function in the foregoing description to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

The method and related apparatus provided in the embodiments of the present application are described with reference to the flowchart and/or schematic structural diagrams of the method provided in the embodiments of the present application, and each flow and/or block of the flowchart and/or schematic structural diagrams of the method may be implemented by computer program instructions, and combinations of flows and/or blocks in the flowchart and/or block diagrams. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable network connection device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable network connection device, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks. These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable network connection device to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or structural diagram block or blocks. These computer program instructions may also be loaded onto a computer or other programmable network connection device to cause a series of operational steps to be performed on the computer or other programmable device to produce a computer implemented process such that the instructions which execute on the computer or other programmable device provide steps for implementing the functions specified in the flowchart flow or flows and/or structures.

The foregoing disclosure is illustrative of the present application and is not to be construed as limiting the scope of the application, which is defined by the appended claims.

Claims

1. A method of blockchain data processing, comprising:

And transferring digital assets from account addresses corresponding to the first equipment to account addresses corresponding to the second equipment according to the transaction request and the asset value of the multimedia data, generating an updated digital certificate of the multimedia data, and storing the updated digital certificate on a blockchain, wherein the updated digital certificate is used for indicating that the multimedia data belongs to an object corresponding to the first equipment.

2. The method of claim 1, wherein predicting asset value of the multimedia data based on the behavioral manipulation data and the first object attribute information comprises:

Invoking a value recognition model, and performing tag recognition on the multimedia data to obtain a prediction tag of the multimedia data;

predicting the added value of the multimedia data according to the behavior operation data and the first object attribute information;

3. The method of claim 2, wherein predicting the asset value of the multimedia data based on the first degree of association and the added value comprises

Invoking the value recognition model, and determining the content value of the multimedia data according to the first association degree;

and carrying out weighted summation processing on the content value and the added value according to weights respectively corresponding to the content value and the added value to obtain the asset value of the multimedia data.

4. The method of claim 3, wherein the weighting and summing the content value and the added value according to weights corresponding to the content value and the added value, respectively, to obtain the asset value of the multimedia data, includes:

Weighting and summing the content value and the added value according to the weights respectively corresponding to the content value and the added value to obtain the initial asset value of the multimedia data;

Acquiring first similarity between the multimedia data and reference media data in a first database, wherein the reference media data is multimedia data published in the media platform;

5. The method according to claim 2, wherein the method further comprises:

Calling an initial value identification model, and carrying out label identification on the sample multimedia data to obtain a prediction label of the sample multimedia data;

Acquiring a second association degree between a prediction tag and a second labeling tag of the sample multimedia data, wherein the second association degree is acquired from description information of the sample multimedia data;

and adjusting the initial value recognition model according to the asset value of the sample multimedia data and the labeling asset value to obtain a value recognition model.

6. The method of claim 5, wherein adjusting the initial value recognition model based on the asset value of the sample multimedia data and the tagged asset value to obtain a value recognition model comprises:

Determining asset prediction errors of the initial value recognition model according to the asset value of the sample multimedia data and the marked asset value;

When the convergence state of the initial value recognition model is an unconverged state, adjusting model parameters of the initial value recognition model according to the asset prediction error;

7. The method of claim 1, wherein transferring the digital asset from the account address corresponding to the first device to the account address corresponding to the second device based on the transaction request and the asset value of the multimedia data comprises:

acquiring an allocation strategy of value added assets about the multimedia data from the blockchain according to the transaction request;

determining the number of assets of the digital assets required to be paid by the object corresponding to the first equipment for purchasing the multimedia data according to the distribution strategy and the asset value of the multimedia data;

8. The method of claim 7, wherein the generating the updated digital voucher for the multimedia data comprises:

9. The method according to claim 1, wherein the method further comprises:

Acquiring a second similarity between the multimedia data and historical multimedia data in a second database, wherein the historical multimedia data is multimedia data on which a corresponding digital certificate is recorded on the blockchain;

10. The method according to claim 1, wherein the method further comprises:

Acquiring the update behavior operation data of the multimedia data;

according to the updating behavior operation data, determining the value added asset of the multimedia data;

the latest digital certificate of the multimedia data is obtained from the blockchain, wherein the latest digital certificate is a digital certificate with the minimum time interval between the recording time and the current time on the blockchain;

And distributing the value added asset to the owner according to the share of the owner for the multimedia data.

11. A blockchain data processing device, comprising:

the system comprises a receiving module, a processing module and a processing module, wherein the receiving module is used for receiving a transaction request of multimedia data issued by a first device in a media platform aiming at a second device, wherein the transaction request carries media attribute information of the multimedia data;

The prediction module is used for predicting the asset value of the multimedia data according to the behavior operation data and the first object attribute information;

12. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any one of claims 1 to 10 when the computer program is executed.

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