Data processing method, client, storage medium and computer program product
By generating and recommending data contracts in a trusted data space, the problem of lack of transaction matching in existing data circulation transactions is solved, the intelligence and accuracy of data transactions are improved, communication costs are reduced, and data circulation is promoted.
Patent Information
- Application Number
- CN202411147187.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-08-20
- Publication Date
- 2024-12-27
AI Technical Summary
The lack of transaction matching process in existing data circulation transactions has led to the lack of reference basis for data demanders and providers in value assessment and transaction pricing, high communication costs and low transaction intelligence.
By introducing data processing methods into the trusted data space, generating contract information of data resources, and using management equipment to perform value evaluation and contract recommendation, both supply and demand parties automatically generate contracts based on the evaluation results and historical transaction conditions, improving the intelligence and accuracy of transactions .
It improves the intelligence and accuracy of data transactions, reduces the communication costs between supply and demand parties during the transaction negotiation stage, provides scientific and credible value assessment and contract resource recommendation, and promotes the sharing of data circulation.
Smart Images
Figure CN119205230A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of data circulation, and in particular to a data processing method and a client, a storage medium, and a computer program product. Background Art
[0002] At present, in the scheme of realizing the circulation of data elements based on the trusted data space, the data supply and demand sides adopt the traditional transaction mode in which the data provider displays the data catalog of data products on the platform, and the data demander browses the details and places an order. The data provider accepts or rejects the transaction request initiated by the data demander after verifying the validity. However, data, as a special product, has huge differences in cost and consumption units, consumption methods, reuse and resale compared with traditional commodities, resulting in different considerations in pricing principles and methods. Version control has become a common mechanism for designing and pricing data elements. The prices of different versions can be associated with the value of different customer groups. The same data element asset has a great demand for "one case, one negotiation" when trading.
[0003] However, the current data circulation and transaction process only supports data listing and browsing, which leads to the problem of low intelligence of data transactions. Summary of the invention
[0004] The present application provides a data processing method, a client, a storage medium, and a computer program product, which can improve the intelligence of data transactions.
[0005] The technical solution of this application is implemented as follows:
[0006] In a first aspect, the present application provides a data processing method, applied to a first client, the method comprising:
[0007] Processing the uploaded data resource information to generate contract information corresponding to the data resource information;
[0008] The contract information is uploaded to the management device; so that the second client can obtain the contract information from the management device and select recommended contract information from the contract information according to the data demand information.
[0009] In a second aspect, the present application provides a data processing method, applied to a second client, the method comprising:
[0010] Obtain contract information from the management device;
[0011] Recommended contract information is selected from the contract information according to the data demand information.
[0012] In a third aspect, the present application proposes a first client, wherein the first client comprises:
[0013] A processing unit, used to process the uploaded data resource information and generate contract information corresponding to the data resource information;
[0014] The uploading unit is used to upload the contract information to the management device, so that the second client can obtain the contract information from the management device and select the recommended contract information from the contract information according to the data demand information.
[0015] In a fourth aspect, the present application proposes a second client, wherein the second client includes:
[0016] An acquisition unit, used for acquiring contract information from a management device;
[0017] The contract recommendation unit is used to select recommended contract information from the contract information according to the data demand information.
[0018] In a fifth aspect, the present application proposes a first client, which includes: a first processor, a first memory and a first communication bus; the first communication bus is used to realize the connection and communication between the first processor and the first memory; when the first processor executes the running program stored in the first memory, the above-mentioned data processing method applied to the first client is implemented.
[0019] In the sixth aspect, the present application proposes a second client, which includes: a second processor, a second memory and a second communication bus; the second communication bus is used to realize the connection and communication between the second processor and the second memory; when the second processor executes the running program stored in the second memory, it implements the above-mentioned data processing method applied to the second client.
[0020] In a seventh aspect, the present application proposes a storage medium having a computer program stored thereon, which, when executed by a first processor, implements the above-mentioned data processing method applied to the first client, or, when executed by a second processor, implements the above-mentioned data processing method applied to the second client.
[0021] In an eighth aspect, the present application proposes a computer program product, comprising a computer program, wherein the computer program implements the above-mentioned data processing method applied to the first client when executed by a first processor, or the computer program implements the above-mentioned data processing method applied to the second client when executed by a second processor.
[0022] The present application provides a data processing method and client, storage medium, and computer program product. The method includes: a first client processes uploaded data resource information to generate contract information corresponding to the data resource information; uploads the contract information to a management device; so that a second client can obtain the contract information from the management device, and select recommended contract information from the contract information according to data demand information. With the above implementation scheme, the first client can adjust the contract content such as the scope of use, usage rights, transaction pricing, etc. of the data resource information by itself, generate contract information corresponding to the data resource information, and subsequently the second client can select recommended contract information according to the data demand information, and the selected recommended contractable information becomes more accurate and intelligent, thereby improving the intelligence of data transactions. BRIEF DESCRIPTION OF THE DRAWINGS
[0023] Figure 1 A data processing method provided in the embodiment of the present application Figure 1 ;
[0024] Figure 2 A data processing method provided in the embodiment of the present application Figure 2 ;
[0025] Figure 3 A flowchart of an exemplary value assessment and transaction matching method provided in an embodiment of the present application;
[0026] Figure 4 A schematic diagram of the system functional structure of an exemplary value assessment and transaction matching method provided in an embodiment of the present application;
[0027] Figure 5 A schematic diagram of the structure of a first client provided in an embodiment of the present application Figure 1 ;
[0028] Figure 6 A schematic diagram of the structure of a first client provided in an embodiment of the present application Figure 2 ;
[0029] Figure 7 A schematic diagram of the structure of a second client provided in an embodiment of the present application Figure 1 ;
[0030] Figure 8 A schematic diagram of the structure of a second client provided in an embodiment of the present application Figure 2 . DETAILED DESCRIPTION
[0031] In order to enable a more detailed understanding of the features and technical contents of the embodiments of the present application, the implementation of the embodiments of the present application is described in detail below in conjunction with the accompanying drawings. The attached drawings are for reference only and are not used to limit the embodiments of the present application.
[0032] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.
[0033] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict. It should also be noted that the terms "first\second\third" involved in the embodiments of the present application are only used to distinguish similar objects and do not represent a specific ordering of the objects. It is understandable that "first\second\third" may be interchanged in a specific order or sequence where permitted, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein.
[0034] Trusted data space is a new type of digital infrastructure that provides security and trust mechanisms for cross-organizational data circulation and use. It is distributed and built on the basis of existing data management systems and networks. It ensures the controlled and trusted circulation and application of data through systematic technical arrangements such as common standards and certifications, solves the security and trust issues between data element providers, users, service providers and other entities, and thus supports data-driven digital transformation. Trusted data space builds a distributed key data infrastructure for data aggregation, sharing, circulation and application on the existing information network, and ensures that the signed data circulation agreements can be fulfilled and maintained through systematic technical arrangements, solving the security and trust issues between data element providers, users, service providers, regulators and other entities.
[0035] The trusted data space uses systematic technical arrangements to ensure that the signed data circulation agreements can be fulfilled and maintained, in which data usage restrictions are enforced after access rights are granted through data usage control technology. The data supply and demand parties reach a cooperation and sign a data circulation transaction contract, in which a data circulation behavior contract is agreed upon. The data demand party's data usage behavior is restricted by converting the data circulation contract into a data usage control policy. Usage control is a way to bind policies to the data being exchanged and continuously control message processing, aggregation, or forwarding to other endpoints. This data-centric perspective allows users to continuously control data flows rather than access to services.
[0036] The current trusted data space realizes the data circulation and delivery between the supply and demand sides. The data is used in a controlled manner based on the contract reached, and there is no transaction matching process. The data demander needs to browse the data directory to issue a contract application for negotiation and reach a contract consensus. The transaction matching link is missing in the current implementation. The quotation of the data demander and the pricing of the data provider can only be based on subjective intentions and offline point-to-point communication. There is a lack of reference basis and the communication cost is too high. The data provider lacks a reference basis for judging the potential value of its own data resources. The data demander can only actively search and then issue a request to find the target data resource commodity. The lack of value assessment and transaction matching links between the supply and demand sides limits the circulation and sharing of data.
[0037] The present application embodiment provides a data processing method, such as Figure 1 As shown, applied to a first client, the method may include:
[0038] S101. Process the uploaded data resource information and generate contract information corresponding to the data resource information.
[0039] In the embodiment of the present application, the first client is a trusted data space (TDS) client of the data provider, and the data provider creates a data directory, uploads data products, and provides data resource information. The data resource information includes at least one of the following: industry, data subject, product type, update frequency, data dimension, source proof, etc. The specific ones can be selected according to the actual situation, and the embodiment of the present application does not make specific limitations.
[0040] In the embodiment of the present application, the first client may be a software or hardware trusted data space client (or connector) set by the data provider for identity authentication, data application management, circulation transaction contract execution, data usage control, etc.
[0041] In the embodiment of the present application, the data provider may be a data providing side device, which may be specifically determined based on actual conditions, and the embodiment of the present application does not make any specific limitation.
[0042] In the embodiment of the present application, the data provider inputs the data resource information to the first client and provides corresponding fields according to the requirements of the first client.
[0043] In an embodiment of the present application, the first client performs a value assessment on the uploaded data resource information to obtain assessment result information; determines the first historical contract template corresponding to the assessment result information, and obtains the contract information generated according to the first historical contract template.
[0044] In the embodiment of the present application, the first client includes a value assessment module, which performs value assessment on the input data resource information to obtain assessment result information. The value assessment module can also assist in value assessment in combination with pre-stored data provider credit information, historical transaction status, etc. to obtain assessment result information.
[0045] It should be noted that the value assessment module is completed using a privacy-based computing approach to ensure the data protection needs of both supply and demand parties before the transaction is completed.
[0046] In an embodiment of the present application, value assessment data is generated based on data resource information; the value assessment data and historical data value information are clustered to obtain a first historical assessment result of the first category where the data resource information is located; the historical data value information is composed of historical data resources and corresponding historical assessment information; and the first historical assessment result is determined as the assessment result information.
[0047] In the embodiment of the present application, the clustering method can be implemented by using a learning vector quantization algorithm (LVQ), which can be selected according to actual conditions and is not specifically limited in the embodiment of the present application.
[0048] In the embodiment of the present application, the historical data value information is all historical data value information containing data resource value features that has been registered in the data resource directory in the trusted data space data resource platform.
[0049] In an embodiment of the present application, the value assessment data and the historical data value information are clustered after being homomorphically encrypted. The specific process includes: encrypting the value assessment data with an encrypted public key to obtain encrypted data; and sending the encrypted data to a management device; sending an encrypted public key to a management device; allowing the management device to encrypt the historical data value information with the encrypted public key to obtain encrypted historical data value information; clustering the encrypted historical data value information and the encrypted data through the management device to obtain an encrypted first historical assessment result; receiving the encrypted first historical assessment result, and decrypting the encrypted first historical assessment result with an encrypted private key to obtain a first historical assessment result.
[0050] Based on the above embodiments, a value assessment method is exemplarily proposed.
[0051] 1. Use data classification results, data industry, data theme, product type, update frequency, data dimension and other data features to quantize the vector into a single value assessment data b m , b m =(x m1 ,x m2 ,……x mn ). mnIt is the sample characteristic value of the classification result, data industry, data theme, product type, update frequency, data dimension, etc. m The sample value category (value assessment data) is y m The data resource directory in the trusted data space data resource platform has registered multiple historical data resource information b m-1 and corresponding real assessment information.
[0052] 2. The first client generates a homomorphic encryption public and private key pair, sends the homomorphic encryption public key to the trusted data space management platform, and the value assessment module encrypts b m , c m =En Pki (b m ), send ciphertext c m To the trusted data space management platform. The trusted data space management platform uses the same public key encryption (b1,y 1) , (b2,y2)……(b m-1 ,y m-1 ), encrypted as (c1,Cy1), (c2,Cy2)...(c m-1 ,Cy m-1 ). All ciphertext sample sets participating in clustering are (c1,Cy1), (c2,Cy2)…(c m-1 ,Cy m-1 ),(c m ,Cy m ).
[0053] 3. The trusted data space management platform manages the ciphertext sample sets c1, c2, ... c m Perform clustering and get c m The data value of the class is used as the first historical evaluation result after encryption. The clustering method can be implemented using the learning vector quantization algorithm (LVQ):
[0054] Input sample set D = {(c1, Cy1), (c2, Cy2)...(c m ,Cy m )}; Design a trusted data space management platform. The data value assessment results have q categories, the number of prototype vectors is q, and the preset category labels of the prototype vectors are {t1, t2, ... t q}; learning rate η∈(0,1).
[0055] Initialize the prototype vector {p1,p2,...p q},
[0056] Repeat the following steps:
[0057] S1. Randomly select sample c from sample set D j ;
[0058] S2. Calculate sample c j With p i (1≤i≤q) distance: d ji =||c j -p i || n ;
[0059] S3, find the j The nearest prototype vector p i* ,i * =argmin i∈{1,2,……,q} d ji ;
[0060] S4, if Cy j =t i* but
[0061] p ’ =p i* +η*(c j -p i* )
[0062] Otherwise ’ =p i* -η*(c j -p i* )
[0063] The prototype vector p i* Update to p ’
[0064] Until the stop condition is met, the prototype vector {p1, p2, ... p q}.
[0065] Recalculate c m Data value results Cy m .
[0066] 4. The trusted data space management platform sends the encrypted first historical evaluation result Cy m The data is sent back to the first client, which decrypts the data using the local private key to obtain a first value assessment result.
[0067] In an embodiment of the present application, the process of generating value assessment data based on data resource information specifically includes: using the first information to perform hierarchical classification to obtain hierarchical classification results; combining the second information and the hierarchical classification results into value assessment data; the first information and the second information form data resource information.
[0068] In an embodiment of the present application, the first information includes information such as data importance (core data, important data, ordinary data), data confidentiality level (low density, medium density, high density, etc.), usage method (privacy computing, plain text transmission, API call, etc.), etc.
[0069] In the embodiment of the present application, the hierarchical classification method can be completed based on the rules specified by the data provider using classifier algorithms such as Bayesian model and vector machine model. The specific method can be selected according to the actual situation, and the embodiment of the present application does not make specific limitations.
[0070] In an embodiment of the present application, the second information includes information such as the industry to which the data belongs, the data subject, the product type, the update frequency, and the data dimension.
[0071] It should be noted that after obtaining the evaluation result information, the evaluation result information and data resource information are also uploaded to the management device so that the second client can obtain the evaluation result information and data resource information from the management device, and select the target data resource information from the data resource information for recommendation based on the data demand information and the evaluation result information.
[0072] In the embodiment of the present application, the management device is a trusted data space management platform.
[0073] In the embodiment of the present application, the trusted data space management platform is used to manage institutions accessing the trusted data space, data circulation transaction management, data resource registration, etc.
[0074] In the embodiment of the present application, the trusted data space management platform includes the original data resource directory, and newly includes a contract template directory and a contract resource directory. Among them, the contract template directory provides general contract templates for display, and dynamically adjusts the display order based on the number of final transactions using the template; the contract resource directory verifies the contract resources provided by each data provider and then displays them on the shelves.
[0075] In the embodiment of the present application, the management device classifies the received data resource information into a data resource directory according to the evaluation result information, and displays it on the shelves for data demanders to browse and view.
[0076] In an embodiment of the present application, the first client further includes a contract template recommendation module, which generates one or more historical contract templates for reference by the data provider based on the evaluation result information and the historical contract signing situation recorded by the system.
[0077] In an embodiment of the present application, a set of historical evaluation information of a set of historical contract templates is obtained; by performing similarity matching on the evaluation result information and the set of historical evaluation information, a historical contract template with the highest similarity is selected from the set of historical evaluation information as the first historical contract template corresponding to the evaluation result information.
[0078] Specifically, the trusted data space management platform stores multiple historical data circulation contracts (a set of historical contract templates), and performs similarity matching based on the K-nearest neighbor algorithm model for the evaluation result information after data value evaluation and the historical evaluation information in the historical contract, and selects the first historical contract template used by the historical transaction contract with the highest similarity, anonymizes it, and recommends it to the data provider. The specific implementation method can use the Minkowski distance to calculate the distance between the evaluation result information output after the data value evaluation and the data value vector (historical evaluation information) in each historical contract. The specific method can be selected according to the actual situation, and the embodiments of the present application do not make specific limitations.
[0079] S102, uploading the contract information to the management device; so that the second client can obtain the contract information from the management device and select recommended contract information from the contract information according to the data demand information.
[0080] In an embodiment of the present application, the data provider designs an intended contract based on the first historical contract template recommended by the first client to obtain contract information; after obtaining the contract information, the contract information is sent to the management device, and the management device registers the received contract information into the contract resource directory for the data demander to browse and view.
[0081] It is understandable that the first client can perform a value assessment on the uploaded data resource information, and can determine the first historical contract template that matches the value assessment of the data resource information, so as to generate contract information corresponding to the data resource information based on the first historical contract template, thereby providing a more scientific and reliable value assessment, improving the accuracy of the value positioning of data resources, and the subsequent selection of recommended contract information becomes more accurate and intelligent, thereby improving the accuracy and intelligence of data demanders in finding data resources.
[0082] The present application embodiment provides a data processing method, such as Figure 2 As shown, applied to the second client, the method may include:
[0083] S201. Obtain contract information from a management device.
[0084] S202: Select recommended contract information from the contract information according to the data demand information.
[0085] In the embodiment of the present application, the second client is a TDS client of the data demander. The data demander proposes data demand information, which includes at least one of the following: the industry to which the data belongs, the amount of data, the type of data, the duration of use, the method of use, the data confidentiality requirements, the demand budget, etc. The specific ones can be selected according to the actual situation, and the embodiment of the present application does not make specific limitations.
[0086] In the embodiment of the present application, the data demander may be a data demand side device, which may be specifically determined based on actual conditions, and the embodiment of the present application does not make any specific limitation.
[0087] In an embodiment of the present application, the second client may be a software or hardware trusted data space client (or connector) set up by the data demander, which is used for identity authentication, data application management, circulation transaction contract execution, data usage control, etc.
[0088] In an embodiment of the present application, the data demander inputs the data demand information into the second client and provides corresponding fields according to the requirements of the second client.
[0089] In an embodiment of the present application, the second client includes a demand assessment module, which assesses the rationality and legality of data demand information.
[0090] Specifically, the demand assessment module conducts demand assessment on the data demand information filled in by the data demander, and checks whether the demand type, demand budget, data volume, data resource usage scenario, data importance (core data, important data, ordinary data), data confidentiality (low-density, medium-density, high-density, etc.), and usage (privacy computing, plain text transmission, API call, etc.) exceed the compliance use application. If the demand assessment is passed, the demand assessment module converts the data demand data resource field into a feature field for storage.
[0091] In an embodiment of the present application, the second client further includes a contract resource recommendation module, which can recommend contract information or data resource information based on the demand evaluation result.
[0092] It should be noted that the contract resource recommendation module is completed using a privacy-based computing approach to ensure the data protection needs of both supply and demand parties before the transaction is completed.
[0093] In an embodiment of the present application, the data demand information proposed by the data demander is processed by demand evaluation and quantization, and becomes the input of the contract resource recommendation module. The contract resource recommendation module matches and recommends all contract resources in the contract resource directory stored in the trusted data space management platform, and recommends the top N items of the scoring results to the data demander for reference. The matching scoring recommendation method can be specifically implemented using a hybrid recommendation system that uses collaborative filtering and content-based recommendations. The item-based collaborative filtering method uses the historical feedback data of contract resources stored in the system to judge the similarity between contract resources, and the demand evaluation results of the demander are used as the feedback results based on feature recommendations. The specific method can be selected according to the actual situation, and the embodiment of the present application does not make specific limitations.
[0094] In the embodiment of the present application, the data demand information is first matched, and when the data demand information is evaluated to be passed, recommended contract information is selected from the contract information based on the data demand information.
[0095] In the embodiment of the present application, the data demander browses the recommended contract information, and initiates contract negotiation after selecting the intended contract information. The data demander and the provider reach an agreement on the contract and sign the contract.
[0096] It is understandable that the first client can perform a value assessment on the uploaded data resource information, and can determine the first historical contract template that matches the value assessment of the data resource information, so as to generate contract information corresponding to the data resource information based on the first historical contract template, thereby providing a more scientific and reliable value assessment, improving the accuracy of the value positioning of data resources, and the subsequent selection of recommended contract information becomes more accurate and intelligent, thereby improving the accuracy and intelligence of data demanders in finding data resources.
[0097] Based on the above embodiments, the present application provides a method for value assessment and transaction matching for privacy protection of both supply and demand parties in a trusted data space, which fills the gap of this function in the current process of realizing data element circulation transactions based on trusted data space, and provides great help in promoting the completion of transactions.
[0098] Based on the above embodiments, the present application performs value assessment and auxiliary pricing reference for the data resources of the data provider, and provides guidance for the data provider to publish data resources.
[0099] Based on the above embodiments, this application provides a data contract resource directory for browsing and data contract directory recommendations for data demanders, in addition to the traditional method of initiating applications by browsing the data resource directory, which greatly reduces the communication costs between the supply and demand parties during the transaction negotiation stage.
[0100] The embodiment of the present application designs a method for value assessment and transaction matching in a trusted data space, which adds a value assessment and transaction matching module to the existing trusted data space, while ensuring the data privacy of the data provider. Based on the model training and optimization effect of data value and data transaction supply and demand recommendation, it provides relatively scientific and reliable value assessment and contract resource recommendation to data transaction buyers and sellers in the trusted data space, and promotes cooperation between the supply and demand parties while ensuring the data privacy of the data provider, solving the current dilemma of difficult pricing and difficult matching between the supply and demand parties in the data transaction process based on the trusted data space.
[0101] Based on the above embodiments, a value assessment and transaction matching method proposed in the embodiments of the present application is as follows: Figure 3 As shown, the method may include:
[0102] 1. The data provider creates a data directory, uploads data products, and provides data resource information.
[0103] Data resource information includes the industry to which the data belongs, data subject, product type, update frequency, data dimension, proof of source, etc.
[0104] 2. The data provider inputs the data resources into the data provider TDS client and provides the corresponding fields according to the client's requirements.
[0105] 3. The value assessment module of the data provider's TDS client conducts value assessment based on the input data resource information, data provider's credit status, historical transaction status, etc.
[0106] 4. The data provider TDS client communicates with the trusted data space management platform and transmits data resource information and value assessment results to the management platform.
[0107] 5. The trusted data space management platform classifies the received data resources into a data resource directory and displays them on the shelves for data demanders to browse and view.
[0108] 6. The data provider's TDS contract template recommendation module generates (one or more) contract templates based on the results of the value assessment module and the historical contract signing records recorded in the system for reference by the data provider.
[0109] 7. The data provider designs a letter of intent based on the contract template recommended by the data provider’s TDS client.
[0110] 8. After the contract resource design is completed, it will be put on the trusted data space management platform.
[0111] 9. The trusted data space management platform registers the received contract resources into the contract resource directory and displays them on the shelves for data demanders to browse and view.
[0112] 10. The data demander proposes data requirements, which include the industry to which the data belongs, data volume, data type, usage duration, usage method, data confidentiality requirements, demand budget, etc.
[0113] 11. The data demander inputs the data demand into the data demander's TDS client and provides the corresponding fields according to the requirements of the data demander's TDS client.
[0114] 12. The demand assessment module of the TDS client of the data demander evaluates the legality and rationality of the proposed data resource requirements.
[0115] 13. After the evaluation is passed, the data demander selects the intended contract resource based on the recommended contract resources or resource directory and initiates contract negotiation.
[0116] 14. The data demander and provider reach an agreement and sign the contract.
[0117] Based on the above embodiments, the system functional structure of a value assessment and transaction matching method proposed in the embodiments of the present application is as follows: Figure 4 As shown, it includes a trusted data space management platform, a trusted data space client of a data provider, and a trusted data space client of a data demander. Among them, the trusted data space management platform includes a data resource directory, a contract template directory, and a contract resource directory; the trusted data space client of a data provider includes a value assessment module and a contract template recommendation module; the trusted data space client of a data demander includes a demand assessment module and a contract resource recommendation module.
[0118] This embodiment of the application provides a first client 1. Figure 5 As shown, the first client 1 includes:
[0119] The processing unit 10 is used to process the uploaded data resource information and generate contract information corresponding to the data resource information;
[0120] The uploading unit 11 is used to upload the contract information to the management device, so that the second client can obtain the contract information from the management device and select recommended contract information from the contract information according to the data demand information.
[0121] Optionally, the first client further includes: a value assessment unit and a determination unit;
[0122] The value evaluation unit is used to perform value evaluation on the uploaded data resource information to obtain evaluation result information;
[0123] The determining unit is used to determine the first historical contract template corresponding to the evaluation result information, and obtain contract information generated according to the first historical contract template.
[0124] Optionally, the first client further includes: a generation unit and a clustering unit;
[0125] The generating unit is used to generate value assessment data according to the data resource information;
[0126] The clustering unit is used to cluster the value assessment data and the historical data value information to obtain a first historical assessment result of the first category where the data resource information is located; the historical data value information is composed of historical data resources and corresponding historical assessment information;
[0127] The determining unit is further configured to determine the first historical evaluation result as the evaluation result information.
[0128] Optionally, the first client further includes: an encryption unit, a sending unit, a receiving unit and a decryption unit;
[0129] The encryption unit is used to encrypt the value assessment data using an encryption public key to obtain encrypted data;
[0130] The sending unit is used to send the encrypted data to the management device; send the encryption public key to the management device; so that the management device uses the encryption public key to encrypt the historical data value information to obtain the encrypted historical data value information;
[0131] The clustering unit is further used to cluster the encrypted historical data value information and the encrypted data through the management device to obtain an encrypted first historical evaluation result;
[0132] The receiving unit is used to receive the encrypted first historical evaluation result;
[0133] The decryption unit is used to decrypt the encrypted first historical evaluation result using the encryption private key to obtain the first historical evaluation result.
[0134] Optionally, the first client further includes: a grading and classification unit;
[0135] The hierarchical classification unit is used to perform hierarchical classification using the first information to obtain a hierarchical classification result; the second information and the hierarchical classification result are combined into the value assessment data; and the data resource information is composed of the first information and the second information.
[0136] Optionally, the first client further includes: an acquisition unit and a matching unit;
[0137] The acquisition unit is used to acquire a set of historical evaluation information of a set of historical contract templates;
[0138] The matching unit is used to select a historical contract template with the highest similarity from the group of historical evaluation information as the first historical contract template corresponding to the evaluation result information by performing similarity matching on the evaluation result information and the group of historical evaluation information.
[0139] Optionally, the uploading unit 11 is also used to upload the evaluation result information and the data resource information to the management device, so that the second client can obtain the evaluation result information and the data resource information from the management device, and select target data resource information from the data resource information for recommendation based on the data demand information and the evaluation result information.
[0140] The embodiment of the present application provides a first client that processes uploaded data resource information and generates contract information corresponding to the data resource information; uploads the contract information to a management device; so that a second client can obtain the contract information from the management device and select recommended contract information from the contract information according to data demand information. It can be seen that the first client can adjust the contract content such as the scope of use, usage rights, transaction pricing, etc. of the data resource information by itself, and generate contract information corresponding to the data resource information. Subsequently, the second client can select recommended contract information according to the data demand information, and the selected recommended contractable information becomes more accurate and intelligent, thereby improving the intelligence of data transactions.
[0141] Figure 6 A schematic diagram of the composition structure of a first client 1 provided in an embodiment of the present application Figure 2 In practical applications, based on the same disclosure concept of the above embodiments, Figure 6 As shown, the first client 1 of this embodiment includes: a first processor 12 , a first memory 13 and a first communication bus 14 .
[0142] The first processor 12 may be at least one of an application specific integrated circuit (ASIC), a digital signal processor (DSP), a digital signal processing image processing device (DSPD), a programmable logic image processing device (PLD), a field programmable gate array (FPGA), a CPU, a controller, a microcontroller, and a microprocessor. It is understandable that for different devices, the electronic device used to implement the above-mentioned processor function may also be other, and this embodiment does not specifically limit it.
[0143] In the embodiment of the present application, the first communication bus 14 is used to realize the connection and communication between the first processor 12 and the first memory 13; when the first processor 12 executes the running program stored in the first memory 13, the following data processing method is implemented:
[0144] The uploaded data resource information is processed to generate contract information corresponding to the data resource information; the contract information is uploaded to the management device; the second client obtains the contract information from the management device, and selects recommended contract information from the contract information according to the data demand information.
[0145] Furthermore, the first processor 12 is also used to perform a value assessment on the uploaded data resource information to obtain assessment result information; determine a first historical contract template corresponding to the assessment result information, and obtain contract information generated according to the first historical contract template.
[0146] Furthermore, the above-mentioned first processor 12 is also used to generate value assessment data based on the data resource information; cluster the value assessment data and historical data value information to obtain a first historical assessment result of the first category where the data resource information is located; the historical data value information is composed of historical data resources and corresponding historical assessment information; and determine the first historical assessment result as the assessment result information.
[0147] Furthermore, the above-mentioned first processor 12 is also used to encrypt the value assessment data using an encryption public key to obtain encrypted data; and send the encrypted data to the management device; send the encryption public key to the management device; so that the management device can use the encryption public key to encrypt the historical data value information to obtain encrypted historical data value information; cluster the encrypted historical data value information and the encrypted data through the management device to obtain an encrypted first historical assessment result; receive the encrypted first historical assessment result, and decrypt the encrypted first historical assessment result using an encryption private key to obtain the first historical assessment result.
[0148] Furthermore, the first processor 12 is also used to perform hierarchical classification using the first information to obtain a hierarchical classification result; the second information and the hierarchical classification result are combined into the value assessment data; and the data resource information is composed of the first information and the second information.
[0149] Furthermore, the above-mentioned first processor 12 is also used to obtain a set of historical evaluation information of a set of historical contract templates; by performing similarity matching on the evaluation result information and the set of historical evaluation information, a historical contract template with the highest similarity is selected from the set of historical evaluation information as the first historical contract template corresponding to the evaluation result information.
[0150] Furthermore, the above-mentioned first processor 12 is also used to upload the evaluation result information and the data resource information to the management device, so that the second client can obtain the evaluation result information and the data resource information from the management device, and select target data resource information from the data resource information for recommendation based on the data demand information and the evaluation result information.
[0151] This embodiment of the application provides a second client 2. Figure 7 As shown, the second client 2 includes:
[0152] An acquisition unit 20, configured to acquire contract information from a management device;
[0153] The contract recommendation unit 21 is used to select recommended contract information from the contract information according to the data demand information.
[0154] Optionally, the second client further includes: a demand assessment unit and a selection unit;
[0155] The demand assessment unit is used to perform demand assessment on the data demand information;
[0156] The selection unit is used to select recommended contract information from the contract information according to the data demand information when the data demand information demand assessment is passed.
[0157] The second client provided in the embodiment of the present application obtains contract information from the management device; and selects recommended contract information from the contract information according to the data demand information. It can be seen that the first client can adjust the contract content such as the scope of use, use rights, transaction pricing, etc. of the data resource information by itself, and generate the contract information corresponding to the data resource information. Subsequently, the second client can select the recommended contract information according to the data demand information, and the selected recommended contractable information becomes more accurate and intelligent, thereby improving the intelligence of data transactions.
[0158] Figure 8 A schematic diagram of the structure of a second client 2 provided in an embodiment of the present application Figure 2 In practical applications, based on the same disclosure concept of the above embodiments, Figure 8 As shown, the second client 2 of this embodiment includes: a second processor 22 , a second memory 23 and a second communication bus 24 .
[0159] The second processor 22 may be at least one of ASIC, DSP, DSPD, PLD, FPGA, CPU, controller, microcontroller, and microprocessor. It is understandable that for different devices, the electronic device used to implement the processor function may also be other, which is not specifically limited in this embodiment.
[0160] In the embodiment of the present application, the second communication bus 24 is used to realize the connection and communication between the second processor 22 and the second memory 23; when the second processor 22 executes the running program stored in the second memory 23, the following data processing method is implemented:
[0161] Acquire contract information from a management device; and select recommended contract information from the contract information based on data demand information.
[0162] Furthermore, the second processor 22 is further configured to perform a demand assessment on the data demand information; and when the demand assessment on the data demand information is passed, select recommended contract information from the contract information according to the data demand information.
[0163] An embodiment of the present application provides a storage medium having a computer program stored thereon. The computer-readable storage medium stores one or more programs. The one or more programs can be executed by one or more processors. The computer program implements the data processing method as described above.
[0164] Based on the above embodiments, an embodiment of the present application provides a computer program product, including a computer program, which can be executed by one or more processors, and the computer program implements the data processing method as described above.
[0165] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.
[0166] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present disclosure, or the part that contributes to the relevant technology, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a disk, or an optical disk), and includes a number of instructions for enabling an image display device (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods described in each embodiment of the present disclosure.
[0167] The above description is only a preferred embodiment of the present application and is not intended to limit the protection scope of the present application.
Claims
1. A data processing method, characterized in that: Applied to a first client, the method includes: Processing the uploaded data resource information to generate contract information corresponding to the data resource information; The contract information is uploaded to the management device; so that the second client can obtain the contract information from the management device and select recommended contract information from the contract information according to the data demand information.
2. The method according to claim 1, characterized in that: The processing of the uploaded data resource information to generate contract information corresponding to the data resource information includes: Perform value assessment on the uploaded data resource information and obtain assessment result information; Determine a first historical contract template corresponding to the evaluation result information, and obtain contract information generated according to the first historical contract template.
3. The method according to claim 1, characterized in that The uploaded data resource information is evaluated for value to obtain evaluation result information, including: Generating value assessment data according to the data resource information; Clustering the value assessment data and historical data value information to obtain a first historical assessment result of a first category where the data resource information belongs; the historical data value information is composed of historical data resources and corresponding historical assessment information; The first historical evaluation result is determined as the evaluation result information.
4. The method according to claim 3, characterized in that The clustering of the value assessment data and the historical data value information to obtain the first historical assessment result of the first category where the data resource information is located includes: Encrypting the value assessment data using an encryption public key to obtain encrypted data; and sending the encrypted data to the management device; Sending the encryption public key to the management device; so that the management device uses the encryption public key to encrypt the historical data value information to obtain the encrypted historical data value information; Clustering the encrypted historical data value information and the encrypted data by the management device to obtain an encrypted first historical evaluation result; The encrypted first historical evaluation result is received, and the encrypted first historical evaluation result is decrypted using an encryption private key to obtain the first historical evaluation result.
5. The method according to claim 3, characterized in that: Generating value assessment data according to the data resource information includes: Using the first information to perform hierarchical classification to obtain a hierarchical classification result; The second information and the hierarchical classification result are combined into the value assessment data; the data resource information is composed of the first information and the second information.
6. The method according to claim 2, characterized in that The determining the first historical contract template corresponding to the evaluation result information includes: Obtain a set of historical evaluation information for a set of historical contract templates; By performing similarity matching between the evaluation result information and the set of historical evaluation information, a historical contract template with the highest similarity is selected from the set of historical evaluation information as the first historical contract template.
7. The method according to claim 2, characterized in that: The method further comprises: The evaluation result information and the data resource information are uploaded to the management device so that the second client can obtain the evaluation result information and the data resource information from the management device, and select target data resource information from the data resource information for recommendation based on the data demand information and the evaluation result information.
8. A data processing method, characterized in that: Applied to the second client, the method includes: Obtain contract information from the management device; Recommended contract information is selected from the contract information according to the data demand information.
9. The method according to claim 8, characterized in that Before selecting recommended contract information from the contract information according to the data demand information, the method further includes: Conducting demand assessment on the data demand information; When the data demand information is evaluated to be passed, recommended contract information is selected from the contract information according to the data demand information.
10. A first client, characterized in that: The first client comprises: A processing unit, used to process the uploaded data resource information and generate contract information corresponding to the data resource information; The uploading unit is used to upload the contract information to the management device, so that the second client can obtain the contract information from the management device and select the recommended contract information from the contract information according to the data demand information.
11. A second client, characterized in that: The second client comprises: An acquisition unit, used for acquiring contract information from a management device; The contract recommendation unit is used to select recommended contract information from the contract information according to the data demand information.
12. A first client, characterized in that: The first client includes: a first processor, a first memory and a first communication bus; the first communication bus is used to realize the connection and communication between the first processor and the first memory; when the first processor executes the running program stored in the first memory, it implements the method described in any one of claims 1-7.
13. A second client, characterized in that: The second client includes: a second processor, a second memory and a second communication bus; the second communication bus is used to realize the connection and communication between the second processor and the second memory; when the second processor executes the running program stored in the second memory, it implements the method described in any one of claims 8-9.
14. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a first processor, the method according to any one of claims 1 to 7 is implemented; or when the computer program is executed by a second processor, the method according to any one of claims 8 to 9 is implemented.
15. A computer program product comprising a computer program, characterized in that When the computer program is executed by a first processor, the computer program implements the method according to any one of claims 1 to 7; or, when the computer program is executed by a second processor, the computer program implements the method according to any one of claims 8 to 9.