Data processing method, device, equipment and computer-readable storage medium

Abstract

The present invention discloses a data processing method, system, device and computer-readable storage medium, wherein the method comprises: a user terminal sends a query request to a data storage blockchain; the data storage blockchain queries the target information corresponding to the query request based on a smart contract; the user terminal displays the target information and sends a transaction request to the corresponding merchant terminal based on the smart contract; the merchant terminal executes the transaction operation corresponding to the transaction request, and when the transaction operation is completed, performs a points issuance operation on the account information corresponding to the transaction request based on the incentive points. The present invention can implement transaction operations in an e-commerce platform system through blockchain technology, store product data (target information) in the data storage blockchain, ensure the security of various data in the e-commerce platform system, avoid the leakage of private data in the e-commerce platform system, and improve the data credibility and data security of the e-commerce platform system.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to an e-commerce platform system, a data processing method, a system, a device, and a computer-readable storage medium. Background Art

[0002] E-commerce transactions involve a vast amount of private user data, including transaction records, personal addresses, and contact information. The storage of user data on e-commerce platforms must balance security and access efficiency, ensuring data security while also meeting high-concurrency access requirements. Furthermore, platform data storage faces the risk of internal leaks. Surveys show that the largest sources of data leaks on e-commerce platforms are merchants and logistics providers. Among the causes of data leaks, the highest proportion is internal actors, i.e., employees leaking e-commerce platform data. Leaked e-commerce platform data includes user names, phone numbers, email addresses, and addresses. As the value of user data grows, data security faces even more severe challenges. This results in a high risk of data leaks within the e-commerce model, ineffective privacy protection, and low data credibility and security on e-commerce platforms.

[0003] The above content is only used to assist in understanding the technical solution of the present invention and does not constitute an admission that the above content is prior art. Summary of the Invention

[0004] The main purpose of the present invention is to provide an e-commerce platform system, data processing method, system, device and computer-readable storage medium, aiming to solve the technical problem of data leakage in e-commerce platforms.

[0005] To achieve the above objectives, the present invention provides an e-commerce platform system, which includes:

[0006] A data storage blockchain, the data storage blockchain comprising a platform data node for storing encrypted platform data, a merchant data node for storing encrypted merchant data, and a user data node for storing encrypted user data;

[0007] An e-commerce platform, wherein the e-commerce platform hashes the platform data, encrypts the hashed platform data using a platform private key, and uploads the encrypted platform data to the platform data node;

[0008] The merchant terminal hashes the product feature information, encrypts the hashed product feature information using the platform private key, and uploads the encrypted product feature information to the merchant data node;

[0009] The user terminal hashes the user information, encrypts the hashed user information using the platform private key, and uploads the encrypted user information to the user data node.

[0010] Furthermore, the e-commerce platform system further comprises: a commodity information chain;

[0011] The commodity information chain includes a production node for storing encrypted product production data, a transportation node for storing encrypted product transportation data, a warehousing node for storing encrypted product warehousing data, a sales node for storing encrypted product sales data, and a logistics node for storing encrypted product logistics data.

[0012] Furthermore, the e-commerce platform system also includes:

[0013] A production terminal, which performs hash processing on the product production data, encrypts the hashed product production data using a production private key, and uploads the encrypted product production data to the production node;

[0014] A transport terminal, wherein the transport terminal performs hash processing on the product transport data, encrypts the hashed product transport data using a transport private key, and uploads the encrypted product transport data to the transport node;

[0015] The warehousing terminal performs hash processing on the product warehousing data, encrypts the hashed product warehousing data using a warehousing private key, and uploads the encrypted product warehousing data to the warehousing node;

[0016] The sales terminal performs hash processing on the product sales data, encrypts the hashed product sales data using a sales private key, and uploads the encrypted product sales data to the sales node;

[0017] The logistics terminal performs hash processing on the product logistics data, encrypts the hashed product logistics data using a logistics private key, and uploads the encrypted product logistics data to the logistics node.

[0018] In addition, to achieve the above-mentioned purpose, the present invention also provides a data processing method, which is applied to the aforementioned e-commerce platform system, and the data processing method includes the following steps:

[0019] Upon receiving an information viewing request, the user terminal sends a query request to the data storage blockchain;

[0020] The data storage blockchain queries the target information corresponding to the query request in the merchant data node of the data storage blockchain based on the smart contract, and sends the target information to the user terminal;

[0021] The user terminal displays the received target information, and upon receiving a purchase request triggered by the target information, sends a transaction request to the merchant terminal corresponding to the target information based on the smart contract;

[0022] The merchant terminal executes the transaction operation corresponding to the transaction request, and when the transaction operation is completed, the merchant terminal determines the incentive points corresponding to the transaction request based on the smart contract, and performs a points issuance operation on the account information corresponding to the transaction request based on the incentive points.

[0023] Furthermore, the data processing method further includes:

[0024] Upon receiving a product traceability instruction, the user terminal sends a product traceability request to the product information blockchain, so that the product information blockchain queries the traceability information corresponding to the product traceability request based on the smart contract and feeds back the traceability information to the user terminal;

[0025] The user terminal displays the received traceability information.

[0026] Furthermore, the data processing method further includes:

[0027] The front-end traceability terminal hashes the product front-end data, encrypts the hashed product front-end data using a production private key, and uploads the encrypted product front-end data to the commodity information blockchain, so that the commodity information blockchain can store the encrypted product front-end data in the front-end traceability node of the commodity information blockchain, wherein the product front-end data includes transportation data, shipping data, and warehousing data;

[0028] The sales terminal hashes the product sales data, encrypts the hashed product sales data using a sales private key, and uploads the encrypted product sales data to the commodity information blockchain, so that the commodity information blockchain stores the encrypted product sales data in the sales node of the commodity information blockchain.

[0029] The logistics terminal hashes the product logistics data, encrypts the hashed product logistics data using a logistics private key, and uploads the encrypted product logistics data to the commodity information blockchain, so that the commodity information blockchain can store the encrypted product logistics data in the logistics node of the commodity information blockchain.

[0030] Furthermore, the data processing method further includes:

[0031] The merchant terminal hashes the product feature information, encrypts the hashed product feature information using the platform private key, and uploads the encrypted product feature information to the data storage blockchain, so that the data storage blockchain can store the encrypted product feature information in the merchant data node of the data storage blockchain.

[0032] Furthermore, the data processing method further includes:

[0033] The merchant data node of the data storage blockchain obtains the user information to be recommended;

[0034] The merchant data node inputs the user information to be recommended into the pre-trained federated recommendation model to obtain the recommendation results;

[0035] The merchant data node sends the recommendation result to the merchant terminal, so that the merchant terminal generates a product recommendation interface based on the recommendation result, and sends the product recommendation interface to the user terminal corresponding to the user information to be recommended.

[0036] Furthermore, before the step of the merchant data node obtaining the user information to be recommended, the step further includes:

[0037] The user data node of the data storage blockchain obtains user preference data based on the encrypted user information, and inputs the user preference data into the first to-be-trained model for model training to obtain a first intermediate parameter;

[0038] The merchant data node obtains product feature data based on the encrypted product feature information, and inputs the product feature data into a second to-be-trained model for model training to obtain a second intermediate parameter;

[0039] The platform data node of the data storage blockchain obtains the user purchasing power data based on the encrypted platform data, and inputs the user purchasing power data into the to-be-trained model for model training to obtain a third intermediate parameter;

[0040] The data storage blockchain determines a target gradient based on the first intermediate parameter, the second intermediate parameter, and the third intermediate parameter, and feeds back the target gradient to the merchant data node, so that the merchant data node determines a pre-trained federated recommendation model based on the target gradient.

[0041] Furthermore, the data storage blockchain determines a target gradient based on the first intermediate parameter, the second intermediate parameter, and the third intermediate parameter, and feeds back the target gradient to the merchant data node so that the merchant data node determines a pre-trained federated recommendation model based on the target gradient. The steps include:

[0042] The data storage blockchain determines a target intermediate parameter and a target gradient based on the first intermediate parameter, the second intermediate parameter, and the third intermediate parameter;

[0043] When the target intermediate parameter meets a preset condition, the data storage blockchain feeds back the target gradient to the merchant data node, so that the merchant data node determines a pre-trained federated recommendation model based on the target gradient.

[0044] Furthermore, after the step of determining the target intermediate parameter and the target gradient based on the first intermediate parameter, the second intermediate parameter, and the third intermediate parameter, the data storage blockchain further includes:

[0045] When the target intermediate parameter meets an unpreset condition, the data storage blockchain feeds back the target gradient to the merchant data node;

[0046] The merchant data node updates the second model to be trained based on the target gradient, and uses the updated second model to be trained as the second model to be trained, and returns to execute the step of inputting the user preference data into the second model to be trained for model training to obtain the second intermediate parameters.

[0047] Furthermore, after the step of determining a target gradient based on the first intermediate parameter, the second intermediate parameter, and the third intermediate parameter, and feeding back the target gradient to the merchant data node so that the merchant data node determines a pre-trained federated recommendation model based on the target gradient, the data storage blockchain further includes:

[0048] The data storage blockchain determines, based on the first intermediate parameter, the second intermediate parameter, and the third intermediate parameter, a first workload corresponding to the user data node, a second workload corresponding to the merchant data node, and a third workload corresponding to the platform data node;

[0049] The data storage blockchain distributes blockchain points to the user data node, the merchant data node, and the platform data node based on the first workload, the second workload, and the third workload.

[0050] In addition, to achieve the above-mentioned purpose, the present invention further provides a data processing device, which is applied to the aforementioned e-commerce platform system, and the data processing device includes:

[0051] A sending module is used to send a query request to the data storage blockchain upon receiving an information viewing request;

[0052] A query module, configured to query the target information corresponding to the query request in the merchant data node of the data storage blockchain based on the smart contract, and send the target information to the user terminal;

[0053] A display module is configured to display the received target information and, upon receiving a purchase request triggered by the target information, send a transaction request to a merchant terminal corresponding to the target information based on a smart contract;

[0054] An execution module is used to execute the transaction operation corresponding to the transaction request. When the transaction operation is completed, the merchant terminal determines the incentive points corresponding to the transaction request based on the smart contract, and performs a points issuance operation on the account information corresponding to the transaction request based on the incentive points.

[0055] In addition, to achieve the above-mentioned purpose, the present invention also provides a data processing device, which includes: a memory, a processor, and a data processing program stored in the memory and executable on the processor, and the data processing program implements the steps of the aforementioned data processing method when executed by the processor.

[0056] In addition, to achieve the above-mentioned purpose, the present invention also provides a computer-readable storage medium, on which a data processing program is stored. When the data processing program is executed by a processor, the steps of the aforementioned data processing method are implemented.

[0057] The present invention is as follows: when receiving an information viewing request, the user terminal sends a query request to the data storage blockchain; then the data storage blockchain queries the target information corresponding to the query request in the merchant data node of the data storage blockchain based on the smart contract, and sends the target information to the user terminal; then the user terminal displays the received target information, and when receiving a purchase request triggered by the target information, sends a transaction request to the merchant terminal corresponding to the target information based on the smart contract; then the merchant terminal executes the transaction operation corresponding to the transaction request, and when the transaction operation is completed, the merchant terminal determines the incentive points corresponding to the transaction request based on the smart contract, and executes a points issuance operation on the account information corresponding to the transaction request based on the incentive points. The transaction operation in the e-commerce platform system can be realized through blockchain technology, and the commodity data (target information) is stored through the data storage blockchain, thereby ensuring the security of various data in the e-commerce platform system, avoiding the leakage of privacy data in the e-commerce platform system, and improving the data credibility and data security of the e-commerce platform system. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 It is a structural diagram of a data processing device in a hardware operating environment involved in an embodiment of the present invention;

[0059] Figure 2 This is a flow chart of a first embodiment of a data processing method according to the present invention;

[0060] Figure 3 This is a schematic diagram of the structure of an e-commerce platform system in one embodiment of the present invention;

[0061] Figure 4 FIG. 1 is a schematic diagram of functional modules of a data processing device according to an embodiment of the present invention.

[0062] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0063] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0064] like Figure 1 As shown, Figure 1 It is a schematic diagram of the structure of a data processing device in a hardware operating environment involved in an embodiment of the present invention.

[0065] The data processing device of the embodiment of the present invention can be a PC, or it can be a mobile terminal device with display function such as a smart phone, a tablet computer, an e-book reader, an MP3 (Moving Picture Experts Group Audio Layer III) player, an MP4 (Moving Picture Experts Group Audio Layer IV) player, a portable computer, etc.

[0066] like Figure 1 As shown, the data processing device may include: a processor 1001, such as a CPU, a network interface 1004, a user interface 1003, a memory 1005, and a communication bus 1002. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a WI-FI interface). The memory 1005 may be a high-speed RAM memory or a stable memory (non-volatile memory), such as a disk memory. The memory 1005 may optionally be a storage system independent of the aforementioned processor 1001.

[0067] Optionally, the data processing device may also include a camera, an RF (Radio Frequency) circuit, a sensor, an audio circuit, a WiFi module, and the like. Among them, the sensors include light sensors, motion sensors, and other sensors. Specifically, the light sensor may include an ambient light sensor and a proximity sensor, wherein the ambient light sensor may adjust the brightness of the display screen according to the brightness of the ambient light, and the proximity sensor may turn off the display screen and / or backlight when the mobile terminal is moved to the ear. As a type of motion sensor, the gravity acceleration sensor can detect the magnitude of acceleration in all directions (generally three axes), and can detect the magnitude and direction of gravity when stationary. It can be used for applications that identify the posture of the mobile terminal (such as horizontal and vertical screen switching, related games, magnetometer posture calibration), vibration recognition related functions (such as pedometer, tapping), etc.; of course, the mobile terminal can also be equipped with other sensors such as gyroscopes, barometers, hygrometers, thermometers, infrared sensors, etc., which will not be repeated here.

[0068] Those skilled in the art will understand that Figure 1 The terminal structure shown in the figure does not constitute a limitation on the data processing device, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0069] like Figure 1 As shown, the memory 1005 as a computer-readable storage medium may include an operating system, a network communication module, a user interface module, and a data processing program.

[0070] exist Figure 1 In the data processing device shown, the network interface 1004 is mainly used to connect to the background server and communicate data with the background server; the user interface 1003 is mainly used to connect to the client (user end) and communicate data with the client; and the processor 1001 can be used to call the data processing program stored in the memory 1005.

[0071] In this embodiment, the data processing device includes: a memory 1005, a processor 1001, and a data processing program stored on the memory 1005 and executable on the processor 1001, wherein the processor 1001 calls the data processing program stored in the memory 1005 and executes the steps of the data processing method in each embodiment of the present application.

[0072] The present invention also provides a data processing method, referring to Figure 2 , Figure 2 Schematic diagram of the flow of the first embodiment of the data processing method of the present invention.

[0073] In this embodiment, the data processing method is applied to the e-commerce platform system, referring to Figure 3The e-commerce platform system includes a data storage blockchain 100, an e-commerce platform 200, a merchant terminal 300 and a user terminal 400.

[0074] Among them, the data storage blockchain includes platform data nodes for storing encrypted platform data, merchant data nodes for storing encrypted merchant data, and user data nodes for storing encrypted user data; the data storage blockchain is a consortium chain in the blockchain.

[0075] The data processing method includes the following steps:

[0076] Step S101: Upon receiving an information viewing request, the user terminal sends a query request to the data storage blockchain;

[0077] Step S102: The data storage blockchain queries the merchant data node of the data storage blockchain based on the smart contract for target information corresponding to the query request, and sends the target information to the user terminal;

[0078] Step S103: The user terminal displays the received target information and, upon receiving a purchase request triggered by the target information, sends a transaction request to the merchant terminal corresponding to the target information based on the smart contract;

[0079] In step S104, the merchant terminal executes the transaction operation corresponding to the transaction request. When the transaction operation is completed, the merchant terminal determines the incentive points corresponding to the transaction request based on the smart contract, and performs a points issuance operation on the account information corresponding to the transaction request based on the incentive points.

[0080] In this embodiment, the user terminal can be a mobile phone, iPad, PC, wearable device, smart TV and other terminals. The user can browse the corresponding page through the user terminal and trigger an information viewing request through the page to obtain the corresponding target information (product information). When receiving the information viewing request, the user terminal sends a query request to the data storage blockchain.

[0081] The data storage blockchain queries the target information corresponding to the query request in the merchant data node of the data storage blockchain based on the smart contract, and sends the target information to the user terminal. The data storage blockchain can first parse the query request to obtain the corresponding product identification information, and query the corresponding target information in the merchant data node according to the product identification information. The merchant data node of the data storage blockchain is used to store encrypted product feature information. After the data storage blockchain queries the encrypted product feature information corresponding to the query request in the merchant data node, it decrypts the encrypted product feature information, performs hash processing to obtain the target information, and sends the target information to the user terminal.

[0082] After receiving the target information fed back by the data storage blockchain, the user terminal displays the received target information for the user to view. At the same time, the user can trigger a purchase request through the display interface of the target information. When receiving a purchase request triggered based on the target information, the user terminal sends a transaction request to the merchant terminal corresponding to the target information based on the smart contract.

[0083] When a merchant terminal receives a transaction request, it executes the transaction operation corresponding to the transaction request. For example, the merchant terminal debits the user account corresponding to the transaction request, or sends a debit request including the target information corresponding to the debit amount to the corresponding server (or data storage blockchain). The server debits the user account corresponding to the debit request and feeds back the debit result to the merchant terminal. When the transaction operation is completed, the merchant terminal determines the incentive points corresponding to the transaction request based on the smart contract, and executes a points issuance operation based on the incentive points for the account information corresponding to the transaction request. Specifically, the merchant terminal determines the incentive points based on the transaction request, issues the incentive points to the account information corresponding to the transaction request, and deducts the corresponding incentive points from the corresponding account of the merchant terminal.

[0084] Furthermore, the data processing method further includes:

[0085] The merchant terminal hashes the product feature information, encrypts the hashed product feature information using the platform private key, and uploads the encrypted product feature information to the data storage blockchain, so that the data storage blockchain can store the encrypted product feature information in the merchant data node of the data storage blockchain.

[0086] In this embodiment, the merchant terminal hashes the product feature information, encrypts the hashed product feature information using the platform private key, and uploads the encrypted product feature information to the data storage blockchain. The data storage blockchain then stores the encrypted product feature information in the merchant data node of the data storage blockchain. Specifically, the merchant terminal desensitizes the product feature information, hashes the desensitized product feature information, encrypts the hashed product feature information using the platform private key, and then uploads the encrypted product feature information to the merchant data node, thereby protecting the privacy data in the product feature information through desensitization technology.

[0087] It should be noted that the e-commerce platform hashes the platform data, encrypts the hashed platform data using the platform's private key, and uploads the encrypted platform data to the data storage blockchain. The data storage blockchain then stores the encrypted platform data in the platform data node of the data storage blockchain. Specifically, the e-commerce platform can first desensitize the platform data, hash the desensitized platform data, encrypt the hashed platform data using the platform's private key, and then upload the encrypted platform data to the data storage blockchain, thereby protecting the privacy of the platform data through desensitization technology.

[0088] The user terminal hashes the user information, encrypts the hashed user information using the platform's private key, and uploads the encrypted user information to the data storage blockchain. The data storage blockchain then stores the encrypted user information on the user data node. Specifically, the user terminal first desensitizes the user information, hashes the desensitized user information, encrypts the hashed user information using the platform's private key, and then uploads the encrypted user information to the data storage blockchain, thereby protecting the privacy of the user information through desensitization technology.

[0089] In this embodiment, blockchain technology is used to achieve secure storage of various data in the e-commerce platform system, data desensitization technology is used to ensure the privacy of data information in the e-commerce platform system, and an encryption method that combines hash processing and private key encryption is used to perform targeted encrypted on-chain storage of private information in the e-commerce platform system.

[0090] It should be noted that the consortium chain architecture can also be used to manage access to data stored on the blockchain. This allows only specific nodes to access the corresponding blocks and the private key for decrypting the content, thus preventing the leakage of private data. For example, read access to the platform data node can be limited to the e-commerce platform, while read access to the user data node can be limited to specific nodes in the user terminal.

[0091] This embodiment proposes a data processing method, whereby upon receiving an information viewing request, the user terminal sends a query request to the data storage blockchain; then the data storage blockchain queries the target information corresponding to the query request in the merchant data node of the data storage blockchain based on the smart contract, and sends the target information to the user terminal; the user terminal then displays the received target information, and upon receiving a purchase request triggered based on the target information, sends a transaction request to the merchant terminal corresponding to the target information based on the smart contract; then the merchant terminal executes the transaction operation corresponding to the transaction request, and when the transaction operation is completed, the merchant terminal determines the incentive points corresponding to the transaction request based on the smart contract, and executes a points issuance operation on the account information corresponding to the transaction request based on the incentive points. This method can implement transaction operations in the e-commerce platform system through blockchain technology, store product data (target information) through the data storage blockchain, ensure the security of various data in the e-commerce platform system, avoid the leakage of privacy data in the e-commerce platform system, and improve the data credibility and data security of the e-commerce platform system.

[0092] Based on the first embodiment, a second embodiment of the data processing method of the present invention is proposed. In this embodiment, the data processing method further includes:

[0093] Step S201: Upon receiving a product traceability instruction, the user terminal sends a product traceability request to the product information blockchain, so that the product information blockchain queries the traceability information corresponding to the product traceability request based on the smart contract and feeds back the traceability information to the user terminal.

[0094] Step S202: The user terminal displays the received traceability information.

[0095] In this embodiment, the user can trigger the product traceability instruction through the interface displayed on the user terminal, for example, triggering the product traceability instruction of the product corresponding to the target information through the display interface of the target information, or triggering the product traceability instruction through the information display interface of other products stored in the data storage blockchain.

[0096] Upon receiving a product traceability instruction, the user terminal sends a product traceability request to the product information blockchain. The product information blockchain queries the traceability information corresponding to the product traceability request based on the smart contract, and feeds back the traceability information to the user terminal. Specifically, the product information blockchain obtains the product identifier corresponding to the product traceability request, and queries the corresponding traceability information in each node of the product information blockchain through the product identifier. The traceability information includes transportation data, shipping data, and warehousing data. If the product corresponding to the product traceability request has been sold, the traceability information also includes sales data and transportation data.

[0097] When receiving the tracing information, the user terminal displays the received tracing information.

[0098] Furthermore, in one embodiment, the data processing method further includes:

[0099] In step S203, the front-end traceability terminal hashes the product front-end data, encrypts the hashed product front-end data using the production private key, and uploads the encrypted product front-end data to the commodity information blockchain, so that the commodity information blockchain can store the encrypted product front-end data in the front-end traceability node of the commodity information blockchain, wherein the product front-end data includes transportation data, shipping data, and warehousing data;

[0100] In step S204, the transport terminal hashes the product sales data, encrypts the hashed product sales data using a sales private key, and uploads the encrypted product sales data to the commodity information blockchain, so that the commodity information blockchain stores the encrypted product sales data in a sales node of the commodity information blockchain.

[0101] In step S205, the logistics terminal hashes the product logistics data, encrypts the hashed product logistics data using a logistics private key, and uploads the encrypted product logistics data to the commodity information blockchain, so that the commodity information blockchain can store the encrypted product logistics data in the logistics node of the commodity information blockchain.

[0102] In this embodiment, refer to Figure 3 The product information chain includes a front-end traceability node for storing encrypted product front-end data, a sales node for storing encrypted product sales data, and a logistics node for storing encrypted product logistics data. The e-commerce platform system also includes a front-end traceability terminal, a sales terminal, and a logistics terminal.

[0103] Among them, reference Figure 3 The product front-end data includes transportation data, transport data and warehousing data. The front-end traceability nodes include production nodes for storing encrypted product production data, transportation nodes for storing encrypted product transportation data, and warehousing nodes for storing encrypted product warehousing data; the front-end traceability terminals include production terminals, transportation terminals and warehousing terminals.

[0104] The production terminal hashes the product production data, encrypts the hashed product production data using the production private key, and uploads the encrypted product production data to the production node;

[0105] The transport terminal hashes the product transport data, encrypts the hashed product transport data using a transport private key, and uploads the encrypted product transport data to the transport node;

[0106] The warehousing terminal performs hash processing on the product warehousing data, encrypts the hashed product warehousing data using a warehousing private key, and uploads the encrypted product warehousing data to the warehousing node.

[0107] In e-commerce platforms, the deep integration of blockchain and product supply chains enables reliable recording and tracking of product distribution information throughout the entire process, effectively managing and controlling the supply chain, and effectively improving the authenticity and credibility of product information and the reliability of product inquiries. Blockchain technology enables full traceability of product information within the e-commerce platform system and by buyers. Furthermore, blockchain's value transfer capabilities empower supply chain finance, helping to integrate the flow of goods, logistics, capital, and information, achieving win-win outcomes for all platform participants and promoting the development of a networked platform economy. The establishment of a blockchain information platform can help reduce information asymmetry within the supply chain, improve communication efficiency between platform merchants and supply chain companies, achieve integrated production and sales, and alleviate supply chain warehousing pressures. Furthermore, by integrating mature technologies such as "one item, one code," RFID tags, and embedded sensors, full-cycle control and traceability of all types of products on the platform can be achieved. This makes product information recording, traceability, and content review more convenient and efficient. For example, RFID tags and embedded sensors can be incorporated into every product.

[0108] It should be noted that during product marketing activities, merchants can use smart contracts within the e-commerce system to set up product marketing promotions and marketing plans, reducing campaign setup costs, channel promotion costs, and user participation. Furthermore, automated contract-based transaction triggering helps reduce product transaction disputes, improve transaction efficiency for platform merchants, and reduce the burden of community operations for merchants. Secure storage of platform data is achieved through on-chain block storage.

[0109] Reference Figure 3 , Figure 3 This is a framework diagram of the e-commerce platform system of this application, where the platform is the e-commerce platform, the user is the user terminal, the merchant is the merchant terminal, the data storage blockchain is the data storage blockchain, the platform data, user data and merchant data are respectively the platform data node, user data node and merchant data node, the commodity information blockchain is the commodity information chain, and the production, transportation, warehousing, sales and logistics are respectively the production node, transportation node, warehousing node, sales node and logistics node.

[0110] The data processing method proposed in this embodiment is that when a product tracing instruction is received, the user terminal sends a product tracing request to the product information blockchain, so that the product information blockchain queries the traceability information corresponding to the product tracing request based on the smart contract, and feeds back the traceability information to the user terminal; then the user terminal displays the received traceability information, which can realize the traceability of products in the e-commerce platform system through blockchain technology, and store the traceability data of the products through the product information blockchain, thereby ensuring the security of various data in the e-commerce platform system, avoiding the leakage of privacy data in the e-commerce platform system, and further improving the data credibility and data security of the e-commerce platform system.

[0111] Based on the above embodiments, a third embodiment of the data processing method of the present invention is proposed. In this embodiment, the data processing method further includes:

[0112] Step S301: The merchant data node of the data storage blockchain obtains the user information to be recommended;

[0113] In this embodiment, the merchant terminal of the data storage blockchain can push a product recommendation interface including product information to the user account that is currently logged in. For example, the user logs in to the e-commerce platform of the e-commerce platform system through the user terminal with the user account, and the e-commerce platform sends the login information of the user account to the merchant terminal. The login information includes the user information to be recommended. The merchant terminal uploads the recommendation request to the merchant data node, and the recommendation request includes the user information to be recommended.

[0114] Then, the merchant data node obtains the user information to be recommended. For example, the merchant data node parses the recommendation request uploaded by the merchant terminal and obtains the user information to be recommended in the recommendation request.

[0115] Step S302: The merchant data node inputs the user information to be recommended into the pre-trained federated recommendation model to obtain a recommendation result;

[0116] In this embodiment, the merchant data node stores a pre-trained federated recommendation model. When obtaining the user information to be recommended, the merchant data node inputs the user information to be recommended into the pre-trained federated recommendation model for model training to obtain the recommendation result, that is, the output of the pre-trained federated recommendation model is the recommendation result.

[0117] In step S303 , the merchant data node sends the recommendation result to the merchant terminal, so that the merchant terminal generates a product recommendation interface based on the recommendation result, and sends the product recommendation interface to the user terminal corresponding to the user information to be recommended.

[0118] In this embodiment, after obtaining the recommendation result, the merchant data node sends the recommendation result to the merchant terminal, that is, sends the recommendation result to the merchant terminal. When receiving the recommendation result sent by the merchant data node, the merchant terminal generates a product recommendation interface based on the recommendation result, for example, adding the product information corresponding to the recommendation result to the preset product recommendation interface to obtain the product recommendation interface, and sending the product recommendation interface to the user terminal corresponding to the user information to be recommended, so as to realize product recommendation to the user.

[0119] The data processing method proposed in this embodiment obtains the user information to be recommended through the merchant data node of the data storage blockchain; then the merchant data node inputs the user information to be recommended into a pre-trained federated recommendation model to obtain a recommendation result; then the merchant data node sends the recommendation result to the merchant terminal, so that the merchant terminal generates a product recommendation interface based on the recommendation result, and sends the product recommendation interface to the user terminal corresponding to the user information to be recommended, and recommends products to the user through the pre-trained federated recommendation model, so as to realize product recommendation based on various data in the e-commerce system, improve the accuracy of product recommendation, and thereby improve the transaction efficiency of the e-commerce system.

[0120] Based on the third embodiment, a fourth embodiment of the data processing method of the present invention is proposed. In this embodiment, before step S301, the data processing method further includes:

[0121] Step S401: The user data node of the data storage blockchain obtains user preference data based on the encrypted user information, and inputs the user preference data into a first to-be-trained model for model training to obtain a first intermediate parameter.

[0122] Step S402: The merchant data node obtains product feature data based on the encrypted product feature information, and inputs the product feature data into a second to-be-trained model for model training to obtain second intermediate parameters.

[0123] Step S403: The platform data node of the data storage blockchain obtains user purchasing power data based on the encrypted platform data, and inputs the user purchasing power data into the to-be-trained model for model training to obtain a third intermediate parameter.

[0124] In step S404, the data storage blockchain determines a target gradient based on the first intermediate parameter, the second intermediate parameter, and the third intermediate parameter, and feeds back the target gradient to the merchant data node, so that the merchant data node determines a pre-trained federated recommendation model based on the target gradient.

[0125] In this embodiment, in order to improve the accuracy of product recommendations, the federated recommendation model is first trained using various relevant data in the e-commerce system to obtain a pre-trained federated recommendation model.

[0126] Specifically, the user data node obtains user preference data based on the encrypted user information, that is, the user data node decrypts the encrypted user information to obtain the decrypted user information, and determines the user preference data from the decrypted user information. For example, the user preference data is determined based on the historical purchase data in the user information, and the user preference data is input into the first model to be trained for model training to obtain a first intermediate parameter, which can be the loss function value of the first model to be trained.

[0127] Simultaneously, the merchant data node decrypts the encrypted product feature information to obtain decrypted product feature data, and inputs this product feature data into the second to-be-trained model for model training to obtain a second intermediate parameter. The platform data node decrypts the encrypted platform data to obtain decrypted platform data, determines user purchasing power data based on the decrypted platform data, and inputs this user purchasing power data into the to-be-trained model for model training to obtain a third intermediate parameter. The e-commerce platform can connect with a banking system to obtain bank data, determine platform data based on the bank data, and then upload the platform data to the platform data node to determine user purchasing power data based on the platform data.

[0128] Then, the user data node uploads the first intermediate parameter to the data storage blockchain, the merchant data node uploads the second intermediate parameter to the data storage blockchain, and the platform data node uploads the third intermediate parameter to the data storage blockchain. The data storage blockchain determines a target gradient based on the first intermediate parameter, the second intermediate parameter, and the third intermediate parameter. For example, the data storage blockchain determines a target parameter, such as a target loss function value, based on the first intermediate parameter, the second intermediate parameter, and the third intermediate parameter, and determines a target gradient based on the target parameter. The data storage blockchain then sends the target gradient to the merchant data node, the user data node, and the platform data node. The merchant data node determines a pre-trained federated recommendation model based on the target gradient. Simultaneously, the user data node and the platform data node determine the pre-trained federated recommendation model based on the target gradient.

[0129] The data processing method proposed in this embodiment obtains user preference data based on encrypted user information through the user data node of the data storage blockchain, and inputs the user preference data into a first to-be-trained model for model training to obtain a first intermediate parameter. The merchant data node then obtains product feature data based on the encrypted product feature information, and inputs the product feature data into a second to-be-trained model for model training to obtain a second intermediate parameter. The platform data node of the data storage blockchain then obtains user purchasing power data based on the encrypted platform data, and inputs the user purchasing power data into the to-be-trained model for model training to obtain a third intermediate parameter. The data storage blockchain then determines a target gradient based on the first intermediate parameter, the second intermediate parameter, and the third intermediate parameter, and feeds the target gradient back to the merchant data node, so that the merchant data node determines a pre-trained federated recommendation model based on the target gradient. This enables a pre-trained federated recommendation model to be obtained through federated learning based on user information, product feature information, and platform data. In federated learning, a pre-trained federated recommendation model can be jointly constructed for the three parties without exporting data from the e-commerce system. This fully protects various private data in the e-commerce system and accurately obtains a pre-trained federated recommendation model to provide users with personalized product services.

[0130] Based on the fourth embodiment, a fifth embodiment of the data processing method of the present invention is proposed. In this embodiment, step S404 includes:

[0131] Step S501: The data storage blockchain determines a target intermediate parameter and a target gradient based on the first intermediate parameter, the second intermediate parameter, and the third intermediate parameter;

[0132] In step S502, when the target intermediate parameter meets a preset condition, the data storage blockchain feeds back the target gradient to the merchant data node, so that the merchant data node determines a pre-trained federated recommendation model based on the target gradient.

[0133] In this embodiment, when the data storage blockchain obtains the first intermediate parameter, the second intermediate parameter, and the third intermediate parameter, it determines the target intermediate parameter based on the first intermediate parameter, the second intermediate parameter, and the third intermediate parameter. Specifically, the weight corresponding to the first intermediate parameter, the weight corresponding to the second intermediate parameter, and the weight corresponding to the third intermediate parameter can be first determined, and then the target intermediate parameter is determined by vector addition. For example, the target intermediate parameter = the first intermediate parameter * the weight corresponding to the first intermediate parameter + the second intermediate parameter * the weight corresponding to the second intermediate parameter + the third intermediate parameter * the weight corresponding to the third intermediate parameter. The target gradient is then determined based on the target intermediate parameter. For example, if the target intermediate parameter is the total loss function value, the target intermediate parameter is processed using a gradient descent algorithm to obtain the target gradient.

[0134] Then, it is determined whether the target intermediate parameter meets the preset conditions, for example, whether the target intermediate parameter is less than the preset parameter. If the target intermediate parameter is less than the preset parameter, it is determined that the target intermediate parameter meets the preset conditions, and then the data storage blockchain sends the target gradient to the merchant data node, the user data node and the platform data node. The merchant data node determines the pre-trained federated recommendation model based on the target gradient. At the same time, the user data node and the platform data node determine the pre-trained federated recommendation model based on the target gradient.

[0135] Furthermore, in one embodiment, after step S501, the following steps are further included:

[0136] Step S503: When the target intermediate parameter satisfies an unpreset condition, the data storage blockchain feeds back the target gradient to the merchant data node;

[0137] In step S504, the merchant data node updates the second model to be trained based on the target gradient, and uses the updated second model to be trained as the second model to be trained, and returns to execute the step of inputting the user preference data into the second model to be trained for model training to obtain the second intermediate parameters.

[0138] In this embodiment, if the target intermediate parameter satisfies an unpreset condition, that is, the target intermediate parameter is greater than or equal to the preset parameter, the data storage blockchain feeds back the target gradient to the merchant data node; the merchant data node updates the second model to be trained based on the target gradient, and uses the updated second model to be trained as the second model to be trained, and returns to step S202. At the same time, the data storage blockchain sends the target gradient to the user data node and the platform data node. The user data node updates the first model to be trained based on the target gradient, and uses the updated first model to be trained as the first model to be trained, and returns to step S201. The platform data node updates the third model to be trained based on the target gradient, and uses the updated third model to be trained as the third model to be trained, and returns to step S203 to ensure convergence of the pre-trained federated recommendation model.

[0139] The data processing method proposed in this embodiment determines the target intermediate parameter and the target gradient based on the first intermediate parameter, the second intermediate parameter, and the third intermediate parameter through the data storage blockchain; when the target intermediate parameter meets the preset condition, the data storage blockchain feeds back the target gradient to the merchant data node, so that the merchant data node determines the pre-trained federated recommendation model based on the target gradient. By ensuring that the target intermediate parameter meets the preset condition, the pre-stored effect of the pre-trained federated recommendation model is ensured.

[0140] Based on the fifth embodiment, a sixth embodiment of the data processing method of the present invention is proposed. In this embodiment, after step S303, the method further includes:

[0141] Step S601: The data storage blockchain determines a first workload corresponding to the user data node, a second workload corresponding to the merchant data node, and a third workload corresponding to the platform data node based on the first intermediate parameter, the second intermediate parameter, and the third intermediate parameter.

[0142] Step S602: The data storage blockchain distributes blockchain points to the user data node, the merchant data node, and the platform data node based on the first workload, the second workload, and the third workload.

[0143] In this embodiment, the data storage blockchain determines the first workload corresponding to the user data node, the second workload corresponding to the merchant data node, and the third workload corresponding to the platform data node based on the first intermediate parameter, the second intermediate parameter, and the third intermediate parameter, so as to determine the workload of each node according to the first intermediate parameter, the second intermediate parameter, and the third intermediate parameter, and distributes blockchain points to the user data node, the merchant data node, and the platform data node based on the first workload, the second workload, and the third workload, so as to realize the token incentive of the blockchain, and then improve the activity of the e-commerce system through token incentives. Platform users can obtain corresponding behavioral incentive benefits based on their own user behavior, further improve their own benefits through more extensive user behavior participation, reflect their own behavior value, and promote the active traffic of the e-commerce system.

[0144] The data processing method proposed in this embodiment determines, through the data storage blockchain, a first workload corresponding to the user data node, a second workload corresponding to the merchant data node, and a third workload corresponding to the platform data node based on the first intermediate parameter, the second intermediate parameter, and the third intermediate parameter; then, the data storage blockchain distributes blockchain points to the user data node, the merchant data node, and the platform data node based on the first workload, the second workload, and the third workload, so as to improve the activity of the e-commerce system through token incentives.

[0145] The embodiment of the present invention further provides a data processing device, referring to Figure 4 , the data processing device includes:

[0146] The sending module 100 is used to send a query request to the data storage blockchain upon receiving an information viewing request;

[0147] A query module 200 is configured to query the target information corresponding to the query request in the merchant data node of the data storage blockchain based on the smart contract, and send the target information to the user terminal;

[0148] The display module 300 is used to display the received target information and, upon receiving a purchase request triggered by the target information, send a transaction request to the merchant terminal corresponding to the target information based on the smart contract;

[0149] The execution module 400 is used to execute the transaction operation corresponding to the transaction request. When the transaction operation is completed, the merchant terminal determines the incentive points corresponding to the transaction request based on the smart contract, and performs a points issuance operation on the account information corresponding to the transaction request based on the incentive points.

[0150] Furthermore, the data processing device further includes:

[0151] Upon receiving a product traceability instruction, the user terminal sends a product traceability request to the product information blockchain, so that the product information blockchain queries the traceability information corresponding to the product traceability request based on the smart contract and feeds back the traceability information to the user terminal;

[0152] The user terminal displays the received traceability information.

[0153] Furthermore, the data processing device further includes:

[0154] The front-end traceability terminal hashes the product front-end data, encrypts the hashed product front-end data using a production private key, and uploads the encrypted product front-end data to the commodity information blockchain, so that the commodity information blockchain can store the encrypted product front-end data in the front-end traceability node of the commodity information blockchain, wherein the product front-end data includes transportation data, shipping data, and warehousing data;

[0155] The sales terminal hashes the product sales data, encrypts the hashed product sales data using a sales private key, and uploads the encrypted product sales data to the commodity information blockchain, so that the commodity information blockchain stores the encrypted product sales data in the sales node of the commodity information blockchain.

[0156] The logistics terminal hashes the product logistics data, encrypts the hashed product logistics data using a logistics private key, and uploads the encrypted product logistics data to the commodity information blockchain, so that the commodity information blockchain can store the encrypted product logistics data in the logistics node of the commodity information blockchain.

[0157] Furthermore, the data processing device further includes:

[0158] The merchant terminal hashes the product feature information, encrypts the hashed product feature information using the platform private key, and uploads the encrypted product feature information to the data storage blockchain, so that the data storage blockchain can store the encrypted product feature information in the merchant data node of the data storage blockchain.

[0159] Furthermore, the data processing device further includes:

[0160] The merchant data node of the data storage blockchain obtains the user information to be recommended;

[0161] The merchant data node inputs the user information to be recommended into the pre-trained federated recommendation model to obtain the recommendation results;

[0162] The merchant data node sends the recommendation result to the merchant terminal, so that the merchant terminal generates a product recommendation interface based on the recommendation result, and sends the product recommendation interface to the user terminal corresponding to the user information to be recommended.

[0163] Furthermore, the data processing device further includes:

[0164] The user data node of the data storage blockchain obtains user preference data based on the encrypted user information, and inputs the user preference data into the first to-be-trained model for model training to obtain a first intermediate parameter;

[0165] The merchant data node obtains product feature data based on the encrypted product feature information, and inputs the product feature data into a second to-be-trained model for model training to obtain a second intermediate parameter;

[0166] The platform data node of the data storage blockchain obtains the user purchasing power data based on the encrypted platform data, and inputs the user purchasing power data into the to-be-trained model for model training to obtain a third intermediate parameter;

[0167] The data storage blockchain determines a target gradient based on the first intermediate parameter, the second intermediate parameter, and the third intermediate parameter, and feeds back the target gradient to the merchant data node, so that the merchant data node determines a pre-trained federated recommendation model based on the target gradient.

[0168] Furthermore, the data processing device further includes:

[0169] The data storage blockchain determines a target intermediate parameter and a target gradient based on the first intermediate parameter, the second intermediate parameter, and the third intermediate parameter;

[0170] When the target intermediate parameter meets a preset condition, the data storage blockchain feeds back the target gradient to the merchant data node, so that the merchant data node determines a pre-trained federated recommendation model based on the target gradient.

[0171] Furthermore, the data processing device further includes:

[0172] When the target intermediate parameter meets an unpreset condition, the data storage blockchain feeds back the target gradient to the merchant data node;

[0173] The merchant data node updates the second model to be trained based on the target gradient, and uses the updated second model to be trained as the second model to be trained, and returns to execute the step of inputting the user preference data into the second model to be trained for model training to obtain the second intermediate parameters.

[0174] Furthermore, the data processing device further includes:

[0175] The data storage blockchain determines, based on the first intermediate parameter, the second intermediate parameter, and the third intermediate parameter, a first workload corresponding to the user data node, a second workload corresponding to the merchant data node, and a third workload corresponding to the platform data node;

[0176] The data storage blockchain distributes blockchain points to the user data node, the merchant data node, and the platform data node based on the first workload, the second workload, and the third workload.

[0177] In addition, an embodiment of the present invention further provides a computer-readable storage medium, on which a data processing program is stored. When the data processing program is executed by a processor, the steps of the data processing method described above are implemented.

[0178] The method implemented when the data processing program running on the processor is executed can refer to the various embodiments of the data processing method of the present invention, and will not be described in detail here.

[0179] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or system comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or system. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or system comprising the element.

[0180] The serial numbers of the above embodiments of the present invention are for description only and do not represent the advantages or disadvantages of the embodiments.

[0181] Through the description of the above embodiments, those skilled in the art can clearly understand that the above embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better embodiment. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a computer-readable storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes a number of instructions for enabling a terminal device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present invention.

[0182] The above are only preferred embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention description and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A data processing method, characterized in that: The data processing method comprises the following steps: Upon receiving an information viewing request, the user terminal sends a query request to the data storage blockchain; The data storage blockchain queries the target information corresponding to the query request in the merchant data node of the data storage blockchain based on the smart contract, and sends the target information to the user terminal; The user terminal displays the received target information, and upon receiving a purchase request triggered by the target information, sends a transaction request to the merchant terminal corresponding to the target information based on the smart contract; The merchant terminal executes the transaction operation corresponding to the transaction request, and when the transaction operation is completed, the merchant terminal determines the incentive points corresponding to the transaction request based on the smart contract, and performs a points issuance operation on the account information corresponding to the transaction request based on the incentive points; The data processing method further includes: The data storage blockchain determines a target gradient based on the obtained first intermediate parameter, second intermediate parameter, and third intermediate parameter, and feeds back the target gradient to the merchant data node, so that the merchant data node determines a pre-trained federated recommendation model based on the target gradient. The second intermediate parameter is obtained by: the merchant data node obtains product feature data based on the encrypted product feature information, and inputs the product feature data into a second to-be-trained model for model training to obtain the second intermediate parameter. The data storage blockchain determines a target gradient based on the first intermediate parameter, the second intermediate parameter, and the third intermediate parameter, and feeds back the target gradient to the merchant data node so that the merchant data node determines a pre-trained federated recommendation model based on the target gradient. The steps include: The data storage blockchain determines a target intermediate parameter and a target gradient based on the first intermediate parameter, the second intermediate parameter, and the third intermediate parameter; When the target intermediate parameter meets a preset condition, the data storage blockchain feeds back the target gradient to the merchant data node, so that the merchant data node determines a pre-trained federated recommendation model based on the target gradient; When the target intermediate parameter does not meet the preset conditions, the data storage blockchain feeds back the target gradient to the merchant data node; The merchant data node updates the second model to be trained based on the target gradient, uses the updated second model to be trained as the second model to be trained, and returns to the step of inputting the product feature data into the second model to be trained for model training to obtain second intermediate parameters; Upon receiving a product traceability instruction, the user terminal sends a product traceability request to the product information blockchain, so that the product information blockchain queries the traceability information corresponding to the product traceability request based on the smart contract and feeds back the traceability information to the user terminal; The user terminal displays the received traceability information.

2. The data processing method according to claim 1, wherein: The data processing method further includes: The front-end traceability terminal hashes the product front-end data, encrypts the hashed product front-end data using the production private key, and uploads the encrypted product front-end data to the commodity information blockchain, so that the commodity information blockchain can store the encrypted product front-end data in the front-end traceability node of the commodity information blockchain. The product front-end data includes transportation data and warehousing data. The sales terminal hashes the product sales data, encrypts the hashed product sales data using a sales private key, and uploads the encrypted product sales data to the commodity information blockchain, so that the commodity information blockchain stores the encrypted product sales data in the sales node of the commodity information blockchain. The logistics terminal hashes the product logistics data, encrypts the hashed product logistics data using a logistics private key, and uploads the encrypted product logistics data to the commodity information blockchain, so that the commodity information blockchain can store the encrypted product logistics data in the logistics node of the commodity information blockchain.

3. The data processing method according to claim 1, wherein: The data processing method further includes: The merchant terminal hashes the product feature information, encrypts the hashed product feature information using the platform private key, and uploads the encrypted product feature information to the data storage blockchain, so that the data storage blockchain can store the encrypted product feature information in the merchant data node of the data storage blockchain.

4. The data processing method according to any one of claims 1 to 3, characterized in that: The data processing method further includes: The merchant data node of the data storage blockchain obtains the user information to be recommended; The merchant data node inputs the user information to be recommended into the pre-trained federated recommendation model to obtain the recommendation results; The merchant data node sends the recommendation result to the merchant terminal, so that the merchant terminal generates a product recommendation interface based on the recommendation result, and sends the product recommendation interface to the user terminal corresponding to the user information to be recommended.

5. The data processing method according to claim 4, wherein: Before the step of the merchant data node acquiring the user information to be recommended, the method further includes: The user data node of the data storage blockchain obtains user preference data based on the encrypted user information, and inputs the user preference data into the first to-be-trained model for model training to obtain a first intermediate parameter; The merchant data node obtains product feature data based on the encrypted product feature information, and inputs the product feature data into a second to-be-trained model for model training to obtain a second intermediate parameter; The platform data node of the data storage blockchain obtains the user purchasing power data based on the encrypted platform data, and inputs the user purchasing power data into the to-be-trained model for model training to obtain the third intermediate parameter.

6. The data processing method according to claim 5, wherein: After the step of the data storage blockchain determining a target gradient based on the first intermediate parameter, the second intermediate parameter, and the third intermediate parameter, and feeding back the target gradient to the merchant data node so that the merchant data node determines a pre-trained federated recommendation model based on the target gradient, the step further includes: The data storage blockchain determines, based on the first intermediate parameter, the second intermediate parameter, and the third intermediate parameter, a first workload corresponding to the user data node, a second workload corresponding to the merchant data node, and a third workload corresponding to the platform data node; The data storage blockchain distributes blockchain points to the user data node, the merchant data node, and the platform data node based on the first workload, the second workload, and the third workload.

7. A data processing device, characterized in that: The data processing device includes: A sending module is used to send a query request to the data storage blockchain upon receiving an information viewing request; A query module, configured to query the target information corresponding to the query request in the merchant data node of the data storage blockchain based on the smart contract, and send the target information to the user terminal; A display module is configured to display the received target information and, upon receiving a purchase request triggered by the target information, send a transaction request to a merchant terminal corresponding to the target information based on a smart contract; an execution module, configured to execute the transaction operation corresponding to the transaction request; upon completion of the transaction operation, the merchant terminal determines the incentive points corresponding to the transaction request based on the smart contract, and executes a points issuance operation on the account information corresponding to the transaction request based on the incentive points; The data processing device further includes: The data storage blockchain determines a target gradient based on the obtained first intermediate parameter, second intermediate parameter, and third intermediate parameter, and feeds back the target gradient to the merchant data node, so that the merchant data node determines a pre-trained federated recommendation model based on the target gradient. The second intermediate parameter is obtained by: the merchant data node obtains product feature data based on the encrypted product feature information, and inputs the product feature data into a second to-be-trained model for model training to obtain the second intermediate parameter. The data storage blockchain determines a target gradient based on the first intermediate parameter, the second intermediate parameter, and the third intermediate parameter, and feeds back the target gradient to the merchant data node, so that the merchant data node determines a pre-trained federated recommendation model based on the target gradient. The pre-trained federated recommendation model includes: The data storage blockchain determines a target intermediate parameter and a target gradient based on the first intermediate parameter, the second intermediate parameter, and the third intermediate parameter; When the target intermediate parameter meets a preset condition, the data storage blockchain feeds back the target gradient to the merchant data node, so that the merchant data node determines a pre-trained federated recommendation model based on the target gradient; When the target intermediate parameter does not meet the preset conditions, the data storage blockchain feeds back the target gradient to the merchant data node; The merchant data node updates the second model to be trained based on the target gradient, uses the updated second model to be trained as the second model to be trained, and returns to execute inputting the product feature data into the second model to be trained for model training to obtain second intermediate parameters; Upon receiving a product traceability instruction, the user terminal sends a product traceability request to the product information blockchain, so that the product information blockchain queries the traceability information corresponding to the product traceability request based on the smart contract and feeds back the traceability information to the user terminal; The user terminal displays the received traceability information.

8. A data processing device, characterized in that: The data processing device includes: a memory, a processor, and a data processing program stored in the memory and executable on the processor. When the data processing program is executed by the processor, the steps of the data processing method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a data processing program, which, when executed by a processor, implements the steps of the data processing method according to any one of claims 1 to 6.

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