Data processing method and device

Abstract

The present application discloses a data processing method and apparatus, the method comprising: upon receiving a query request for a basic data set from a data access party, obtaining alternative data provided by each of one or more data providers for a target data item in the basic data set during a target data provision period, thereby obtaining one or more pieces of alternative data; obtaining historical rights and interests of each data provider, wherein the historical rights and interests are obtained based on the comprehensive rights and interests of each data provider during all historical data provision periods; determining the confidence of each piece of the one or more pieces of alternative data, and using the alternative data with the highest confidence as the target data, wherein the confidence is determined based on the historical rights and interests of each target data provider among the one or more target data providers that provided the alternative data; determining a basic data set based on the target data, and sending the basic data set to the data access party, thereby improving the accuracy of the basic data set queried by the user.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a data processing method and device. Background Art

[0002] With the rapid development of internet technology, a data platform can often collaborate with multiple data providers to integrate a more comprehensive and accurate basic data set for users, thereby enhancing the data platform's competitiveness among similar products. The so-called basic data set refers to data that can be made public and does not involve sensitive information. In the case of multiple data providers, data conflicts may occur when the data platform integrates data. The so-called data conflict can be understood as: different data providers provide different data values for the same data item. For example, for the address of shopping mall A, provider A provides data for block A, while provider B provides data for block B. Therefore, how to efficiently integrate the data provided by various data providers has become a current research hotspot. Summary of the Invention

[0003] The embodiments of the present application provide a data processing method and device, which can improve the efficiency of data fusion on a data platform.

[0004] In one aspect, an embodiment of the present application provides a data processing method, comprising:

[0005] If a query request for a basic data set is received from a data access party, obtaining candidate data provided by each of one or more data providers for a target data item in the basic data set within a target data provision period, thereby obtaining one or more candidate data;

[0006] Acquire the historical rights and interests of each data provider, where the historical rights and interests are obtained based on the comprehensive rights and interests of each data provider in all historical data provision periods before the target data provision period;

[0007] determining a confidence level of each candidate data piece among the one or more candidate data pieces, and selecting the candidate data piece with the highest confidence level as the target data piece, wherein the confidence level of each candidate data piece is determined based on the historical equity of each target data provider among the one or more target data providers providing the candidate data piece;

[0008] A basic data set is determined according to the target data, and the basic data set is sent to the data access party.

[0009] In one aspect, an embodiment of the present application provides a data processing device, comprising:

[0010] an acquiring unit configured to, upon receiving a query request for a basic data set from a data access party, acquire candidate data provided by each of one or more data providers for a target data item in the basic data set within a target data provision period, thereby obtaining one or more pieces of candidate data;

[0011] The acquisition unit is further configured to acquire the historical rights and interests of each data provider, where the historical rights and interests are obtained based on the comprehensive rights and interests of each data provider in all historical data provision periods before the target data provision period;

[0012] a determining unit, configured to determine a confidence level of each candidate data piece among the one or more candidate data pieces, and select the candidate data piece with the highest confidence level as the target data piece, wherein the confidence level of each candidate data piece is determined based on the historical equity of each target data provider among the one or more target data providers providing the candidate data piece;

[0013] A sending unit is configured to determine a basic data set according to the target data, and send the basic data set to the data access party.

[0014] On the one hand, embodiments of the present application provide a data platform, including:

[0015] a processor adapted to execute one or more computer programs;

[0016] A computer storage medium storing one or more computer programs, wherein the one or more computer programs are suitable for being loaded and executed by the processor:

[0017] If a query request for a basic data set is received from a data access party, the alternative data provided by each of one or more data providers for the target data item in the basic data set within the target data provision period is obtained to obtain one or more alternative data; the historical rights and interests of each data provider are obtained, and the historical rights and interests are obtained based on the comprehensive rights and interests of each data provider in all historical data provision periods before the target data provision period; the confidence of each of the one or more alternative data is determined, and the alternative data with the highest confidence is used as the target data, and the confidence of each alternative data is determined based on the historical rights and interests of each target data provider among the one or more target data providers that provide each alternative data; the basic data set is determined based on the target data, and the basic data set is sent to the data access party.

[0018] In one aspect, an embodiment of the present application provides a storage medium storing one or more computer programs, wherein the one or more computer programs are suitable for being loaded and executed by a processor:

[0019] If a query request for a basic data set is received from a data access party, the alternative data provided by each of one or more data providers for the target data item in the basic data set within the target data provision period is obtained to obtain one or more alternative data; the historical rights and interests of each data provider are obtained, and the historical rights and interests are obtained based on the comprehensive rights and interests of each data provider in all historical data provision periods before the target data provision period; the confidence of each of the one or more alternative data is determined, and the alternative data with the highest confidence is used as the target data, and the confidence of each alternative data is determined based on the historical rights and interests of each target data provider among the one or more target data providers that provide each alternative data; the basic data set is determined based on the target data, and the basic data set is sent to the data access party.

[0020] In one aspect, an embodiment of the present application provides a computer program product or computer program. The computer program product includes a computer program stored in a computer storage medium. A processor of a data platform reads the computer program from the computer storage medium and executes the computer program, causing the data platform to perform:

[0021] If a query request for a basic data set is received from a data access party, the alternative data provided by each of one or more data providers for the target data item in the basic data set within the target data provision period is obtained to obtain one or more alternative data; the historical rights and interests of each data provider are obtained, and the historical rights and interests are obtained based on the comprehensive rights and interests of each data provider in all historical data provision periods before the target data provision period; the confidence of each of the one or more alternative data is determined, and the alternative data with the highest confidence is used as the target data, and the confidence of each alternative data is determined based on the historical rights and interests of each target data provider among the one or more target data providers that provide each alternative data; the basic data set is determined based on the target data, and the basic data set is sent to the data access party.

[0022] In an embodiment of the present application, when a data conflict exists in a target data item, data fusion is performed by obtaining various alternative data corresponding to the target data item, determining the historical rights and interests of one or more data providers corresponding to each alternative data, and then determining the confidence level of each alternative data based on the historical rights and interests of the one or more data providers, thereby improving the accuracy of the data provided to users by the data platform. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0024] Figure 1a This is a schematic diagram of data flow in a data platform provided in an embodiment of the present application;

[0025] Figure 1b is a schematic diagram of a data processing system provided in an embodiment of the present application;

[0026] Figure 2 This is a flow chart of a data processing method provided in an embodiment of the present application;

[0027] Figure 3a This is a schematic diagram of the structure of a blockchain provided by an embodiment of the present application;

[0028] Figure 3b This is a schematic diagram of the structure of a blockchain network provided by an embodiment of the present application;

[0029] Figure 3c This is a schematic diagram of a target data determination process provided by an embodiment of the present application;

[0030] Figure 4 This is a flow chart of another data processing method provided in an embodiment of the present application;

[0031] Figure 5 is a schematic diagram of a data processing device provided in an embodiment of the present application;

[0032] Figure 6 This is a structural diagram of a data platform provided in an embodiment of the present application. DETAILED DESCRIPTION

[0033] Thanks to the development of Internet technology, data platforms can leverage the advantages of the Internet to integrate information provided by multiple data providers (e.g., multiple business entities) so that users can access information related to the services corresponding to each business entity on the data platform. For example, a medical data platform can access information related to services such as doctor live streaming, online consultation, and registration. For example, the doctor live streaming service may include data such as the doctor's name, doctor's title, and hospital address; the online consultation service may include data such as the doctor's name, doctor's title, and disease name; and the registration service may include data such as the doctor's name, hospital address, and department name. It is understandable that different services may use the same data item. For example, the registration service and the online consultation service may both use the data item of Doctor A's doctor's title. If the data between the various services is not unified, users may see different data for the same data item in different services. For example, the doctor's title seen in the registration service may be inconsistent with the doctor's title seen in the online consultation service, thereby affecting the user experience. Therefore, it's necessary to fuse the data provided by various business entities to generate highly reliable and consistent data for user use. In practical applications, when a data platform has multiple data providers, data fusion may encounter conflicts. In these cases, the data platform typically groups similar objects together based on certain feature values and then uses each data access provider to determine the data they need. However, during this process, a data access provider may modify the data used by other data access providers, impacting their business.

[0034] The data platform includes one or more basic data sets, each of which includes one or more data. Different data correspond to different data items, and each data item may correspond to one or more data. For example, the so-called basic data set can be understood as: a complete piece of information, such as: doctor information (such as: Doctor A - Ophthalmology - Chief Physician), college information, etc.; data items can be understood as: the various fields that make up the complete piece of information, such as: the doctor's name or doctor's title that makes up the doctor's information, and the college name or college address that makes up the college information. Then, it can be further understood that the data provider can refer to: a business party that has established a communication connection with the data platform and can provide the data platform with alternative data for each data item it owns; the data access party can refer to: an application or client that needs to use the basic data set in the data platform, etc.

[0035] In order to solve the above problems, an embodiment of the present application provides a data processing solution, which, when integrating the data provided by various business parties, constructs a proof of traffic rights by calculating the traffic brought to the data platform by each business party, and unifies the data used by each business party based on the proof of traffic rights, so that the data platform can efficiently collect more comprehensive data and become an open data platform. Specifically, the general principle of the data processing solution is as follows: after receiving the query request for the basic data set from the data access party, the alternative data provided by each data provider cooperating with the data platform for the target data item in the basic data set within the target data provision cycle is obtained. The so-called target data provision cycle can be any data provision cycle. In each data provision cycle, the data platform can receive alternative data for any data item provided by one or more data providers. Furthermore, during the target data provision cycle, if there is a situation where the target data item corresponds to multiple different alternative data, the data provider (which may be one or more) of each alternative data in the multiple different alternative data items is determined, and then the data platform can determine the confidence of each alternative data by determining the historical rights and interests of one or more data providers, thereby selecting the alternative data with the highest confidence, and determine the basic data set for the user query based on the alternative data, and then send the basic data set to the data access party.

[0036] The target data item may refer to any one of the one or more data items included in any basic data set of all basic data sets included in the data platform. For example, when the basic data set is college information, if the college information includes two data items: college name and college address, then in the basic data set of college information, the target data item may be the college name or the college address. When the target data item is the college name, the alternative data may be: XX Information College, XX Engineering College, etc. The historical rights and interests of each data provider are related to the various alternative data provided by the data provider during the historical data provision cycle. Specifically, if the data provider adopts more alternative data among all the alternative data provided by the data provider during the historical data provision cycle, the corresponding historical rights and interests of the data provider will be higher; correspondingly, if the number of alternative data adopted is smaller, the corresponding historical rights and interests of the data provider will be lower.

[0037] For example, the data flow between the data provider, data access party and data platform can be found in Figure 1aAs shown, data providers provide basic datasets to the data platform, which then stores the produced basic datasets (i.e., the basic datasets provided by the data providers) in the form of blocks. Data accessors then consume existing basic datasets from the blocks containing the basic datasets and periodically provide the data platform with detailed consumption information. They also pay the data platform based on the traffic corresponding to the data consumption information. After receiving the fees, the data platform can distribute economic benefits to the data provider based on the data provider's traffic rights. For example, if "School X's school address" comes from data provider B, then if data accessor A uses "School X's school address," data accessor A must provide the data platform with traffic proof of using "School X's school address" and pay the data platform based on the traffic in the traffic proof. The data platform can then distribute the fees paid by data accessor A to data provider B based on the data provider's traffic rights during the target data provision period. Since data access parties need to pay the data platform based on traffic, the problem of data access parties over-reporting traffic can be objectively limited. In the case that data access parties under-report traffic, the data platform can verify by randomly accessing one or more businesses of the data access party and checking whether the traffic of the data access party has increased after the access; if there is no increase, it proves that the data access party has under-reported traffic. At this time, the data platform can impose appropriate penalties on the data access party, which can effectively prevent the behavior of under-reporting traffic.

[0038] In a specific implementation, the above data processing solution can be applied to Figure 1b In the data processing system shown in FIG. Figure 1b As shown, the data processing system includes one or more data providers 11, a data platform 12, and one or more data access parties 13. Each of the one or more data providers, or each of the one or more data access parties, can be a terminal or a client running in a terminal; the data platform can exist in a data platform, which can be a terminal or a server. Terminals can include, but are not limited to, smartphones, tablets, laptops, desktop computers, smart TVs, etc.; users can log in to the client through an account login method, and then provide alternative data to the server through the client, etc. The server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms, etc.

[0039] Based on the above data processing solution and the related description of the above data processing system, the embodiment of the present application provides a data processing method, which can be executed by the above-mentioned data platform; see Figure 2 As shown, the data processing method includes:

[0040] S201: If a query request for a basic data set is received from a data access party, obtain candidate data provided by each of one or more data providers for a target data item in the basic data set within a target data provision period to obtain one or more candidate data.

[0041] In practical applications, the data platform may establish a communication connection with one or more data providers to obtain candidate data provided by the one or more data providers for a target data item. The one or more data providers mentioned above refer to at least one data provider. The data platform may obtain candidate data provided by any data provider for a target data item during a target data provision period by: receiving private data synchronized to the data platform by any data provider after the data provider connects to the data platform; and then, the data platform saves the synchronized private data from the data provider in the form of blocks in the block corresponding to the target data provision period.

[0042] The data processing system may constitute a blockchain network, wherein the node devices in the blockchain network may include a data platform, at least one data provider, and at least one data access party. After one or more of the at least one data provider sends candidate data for a target data item to the data platform, the data platform may generate a block based on the candidate data for the target data item provided by each of the one or more data providers, and publish the block to the blockchain network.

[0043] by Figure 3aThe structural diagram of the blockchain shown is taken as an example. Whenever there is new alternative data to be written to the blockchain, these new alternative data will be summarized in a block (block), added to the end of the existing blockchain, and the newly added blocks of each node are guaranteed to be exactly the same by the consensus algorithm. Several data synchronization records are recorded in each block, and the hash (hash) value of the previous block is included at the same time. All blocks are exactly saved in this way. The hash value in the previous block is connected in order to form a blockchain. The hash value of the previous block can be stored in the block header of the next block in the blockchain. When the target data of the data item in the previous block changes, the hash value of this block will also change accordingly, so it is difficult to be tampered with by uploading to the target data in the blockchain network. In order to better understand the data processing method provided by the embodiment of the application, the blockchain network used by the embodiment of the application will be described below. In practical applications, blockchain is a new application mode of computer technologies such as distributed data storage, point-to-point transmission, consensus mechanism, encryption algorithm. Blockchain is essentially a decentralized database, a string of data blocks generated using cryptographic methods. Each data block contains information about a batch of network transactions, which is used to verify the validity of the information (anti-counterfeiting) and generate the next block. The blockchain can include the blockchain underlying platform, the platform product service layer, and the application service layer. Among them, the blockchain underlying platform can include processing modules such as user management, basic services, smart contracts, and operation monitoring. Among them, the user management module is responsible for the identity information management of all blockchain participants, including maintaining public and private key generation (account management), key management, and maintaining the correspondence between the user's real identity and the blockchain address (authority management). In addition, under authorization, it supervises and audits the transactions of certain real identities and provides risk control rule configuration (risk control audit); the basic service module is deployed on all blockchain node devices to verify the validity of business requests and record the valid requests in the storage after consensus is reached. For a new business request, the basic service first performs interface adaptation parsing and authentication processing (interface adaptation). , and then encrypt the business information through the consensus algorithm (consensus management), and transmit it to the shared ledger in a complete and consistent manner after encryption (network communication), and record and store it; the smart contract module is responsible for the registration and issuance of contracts, as well as contract triggering and contract execution. Developers can define the contract logic in a certain programming language and publish it to the blockchain (contract registration). According to the logic of the contract terms, the key or other events are called to trigger the execution to complete the contract logic. At the same time, it also provides the function of contract upgrade and cancellation; the operation monitoring module is mainly responsible for the deployment, configuration modification, contract setting, cloud adaptation and real-time status visualization output of the product during the product release process, such as: alarm, monitoring network conditions, monitoring the health status of node equipment, etc.In addition, the platform product service layer is used to provide the basic capabilities and implementation framework of typical applications. Developers can overlay business characteristics based on these basic capabilities to complete the blockchain implementation of business logic; while the application service layer provides application services based on blockchain solutions for business participants to use.

[0044] See Figure 3b , Figure 3b This is a schematic diagram of the structure of a blockchain network provided by an embodiment of the present application. Figure 3b As shown, the blockchain network includes at least one data provider 301, at least one first blockchain node device 302, and at least one second blockchain node device 303. It should be noted that the structure of the blockchain network in this embodiment is merely an illustration of an embodiment of the present application and does not limit the present solution. The data provider 301 can be a client running on a terminal device, and the first blockchain node device 302 can be any node device among the blockchain node devices. The first blockchain node device 302 is a blockchain node device elected by all blockchain node devices in the blockchain network according to a consensus algorithm, wherein the consensus algorithm includes but is not limited to the Proof of Work (PoW) algorithm, the Proof of Stake (PoS) algorithm, the Delegated Proof of Stake (DPoS) algorithm, the Practical Byzantine Fault Tolerance (PBFT) algorithm, etc. The second blockchain node device is a blockchain node device other than the first blockchain node device in the blockchain network. The first blockchain node device can be periodically elected by the consensus algorithm, and the first blockchain node devices elected in different periods can be the same or different.

[0045] S202, obtaining the historical rights and interests of each data provider.

[0046] In actual applications, the historical rights and interests of each data provider can be determined based on the comprehensive rights and interests obtained by the data provider in all historical data provision cycles before the target data provision cycle. The so-called comprehensive rights and interests refer to the rights and interests obtained by each data provider in any historical data provision cycle. For example, if the target data provision cycle is the third data provision cycle, then the historical rights and interests of data provider a can be determined based on all comprehensive rights and interests obtained by data provider a in the first and second data provision cycles (there are two comprehensive rights and interests in total, one comprehensive right and interest for each data provision cycle). Specifically, assuming that in the first data provision cycle, the comprehensive rights and interests obtained by the data provider through the data a and data b it provided are A; in the second data provision cycle, the comprehensive rights and interests obtained by the data provider through the data a, data b and data c it provided are B; then, in the third data provision cycle, the historical rights and interests of the data provider can be obtained based on the comprehensive rights and interests A and the comprehensive rights and interests B. For example, the data platform can construct comprehensive rights and interests (or traffic rights and interests proof) based on POS (Proof of Stake). The source of the rights and interests proof on the blockchain is the accumulation of revenue from block generation (i.e., the accumulation of comprehensive rights and interests in each historical data provision cycle). It can be understood that the more rights and interests there are, the easier it is to generate blocks, which can further bring more rights and interests to the data provider.

[0047] In one embodiment, the data platform may also deduct the traffic equity of one or more target data providers that provided the original target data from the total amount of traffic equity for the target data in all historical data provision periods before the data provision period in which the target candidate data is used as the target data, and distribute the deducted traffic equity to each data provider that provided the target candidate data. It is understandable that the traffic equity of a data provider in the target data provision period may be negative, that is, the data provider is deducted the traffic equity related to the original target data during the target data provision period. For example, Figure 3c In data provision period 4, the data platform can deduct the total traffic rights obtained by data provider A in data provision period 1 to data provision period 3, and distribute the total traffic rights to data providers B, C, and D. For example, the data platform can distribute the total traffic rights equally to data providers B, C, and D.

[0048] Based on this, it can be understood that the historical rights and interests of the data provider will not necessarily increase with the increase in the number of historical data provision cycles (that is, the historical rights and interests of the data provider in the Nth (N is a positive integer) historical data provision cycle are not necessarily greater than the historical rights and interests of the data provider in the N-1th historical data provision cycle). For example, if the alternative data provided by the data provider in the Nth data provision cycle is sent to the data access party by the data platform as the target data in a certain basic data set, then the historical rights and interests of the data provider will increase (it can be understood that the historical rights and interests of the N-1th historical data provision cycle are less than the historical rights and interests of the Nth historical data provision cycle); correspondingly, if the data provider in the Nth data provision cycle If the alternative data provided in a data provision cycle is erroneous data, but the alternative data is sent to the data access party by the data platform as the target data in a certain basic data set, then the historical rights and interests of the data provider will be reduced (it can be understood that the historical rights and interests of the N-1th historical data provision cycle are greater than the historical rights and interests of the Nth historical data provision cycle); if the alternative data provided by the data provider in the Nth data provision cycle to the N+2th data provision cycle are not sent to the data access party by the data platform as the target data in a certain basic data set, then the historical rights and interests of the data provider can remain unchanged (it can be understood that the historical rights and interests of the N+2th data provision cycle can be consistent with the historical rights and interests of the Nth data provision cycle).

[0049] In one embodiment, a data provider can also be a data access provider. Specifically, if a data provider uses the same data as the data platform in its own business after accessing the data platform, it is considered that the data provider has used the basic data set of the data platform and the data provider is also a data access provider. For example, if the data platform has the school address of School X, and Data Provider A provides the data platform with the admissions phone number of School X, and Data Provider A has a school information query business that uses the school address of School X, then the "school address of School X" used by Data Provider A is considered to come from the data platform, and Data Provider A is also considered to be a data access provider in the data platform. As can be seen from the above, the comprehensive rights and interests of the data provider (or the data access provider when it is the data provider) in the target data provision period refer to the rights and interests obtained by the data provider during the target data provision period. Therefore, when the data provider is also a data access provider, it can be understood that the rights and interests obtained by the data provider during the target data provision period (i.e., comprehensive rights and interests) can include: traffic rights and interests (or rights and interests in producing the basic data set) and consumption rights and interests (or rights and interests in consuming the basic data set). It can be further understood that the historical rights and interests of the data provider can be obtained based on the traffic rights and interests of the data provider in all historical data provision periods and the consumption rights and interests in all historical data provision periods.

[0050] Among them, the traffic rights and interests are positively correlated with the consumption of the target data provided by the data provider by the data access party (here refers to all data access parties in the data platform. Since the data provider is also a data access party, all data access parties include: the data provider), that is, the more the data access party consumes the target data provided by the data provider, the greater the traffic rights and interests of the data provider. Consumption can be understood as: the traffic generated by all data access parties when consuming the target data provided by the data provider (such as: access or download, etc.); illustratively, consumption can be visits, daily active users, independent visitors, etc. Further, when the consumption is visits, the traffic rights and interests of the data provider can be understood as: the income of the data provider generated by the data access party accessing all target data provided by the data provider, that is, the traffic rights and interests of the data provider can be determined based on the visits generated by all data access parties accessing all target data provided by the data provider. For example, assuming that the data provider provides data value a for data item A, and among all the data access parties corresponding to the data platform, 3 data access parties have accessed data value a, and a total of 100 times, then it can be understood that the consumption of data value a can be 100 times; therefore, the data platform can determine the traffic rights of the data provider who provides data value a based on these 100 visits.

[0051] In addition, the consumer rights mentioned above may refer to: the income that the data access party (or the data provider as the data access party) generates from consuming the data in the data platform, and the consumption income is positively correlated with the data access party's consumption of the target data; that is, the higher the data access party's consumption of the target data, the greater the consumer rights of the data access party. For example, when the consumption is the number of visits, the higher the data access party's visits to each target data in the data platform, the greater the corresponding consumer rights of the data access party. It should be noted that the "various target data in the data platform" mentioned here refers to: all data in the data platform that can be queried by the data access party.

[0052] In another embodiment, if the data provider does not consume the basic data set in the data platform, the comprehensive rights and interests of the data provider can be traffic rights and interests. Furthermore, the historical rights and interests of the data provider can be obtained based on the traffic rights and interests of the data provider in all historical data provision periods. In another embodiment, if the data access party does not provide the basic data set to the data platform, the comprehensive rights and interests of the data access party can be consumption rights and interests. Furthermore, the historical rights and interests of the data provider can be obtained based on the consumption rights and interests of the data provider in all historical data provision periods.

[0053] S203: Determine the confidence of each candidate data in the one or more candidate data, and use the candidate data with the highest confidence as the target data.

[0054] Among them, the target data can be understood as: the data value sent to the data access party so that the data access party can query it; or, it can be understood as: the data value with the highest confidence determined in the alternative data. For example: the alternative data corresponding to the professional title information of doctor A are "Deputy Chief Physician" and "Chief Physician", and the confidence of "Deputy Chief Physician" is higher than that of "Chief Physician", then the target data is "Deputy Chief Physician". Furthermore, when each data access party obtains the professional title information of doctor A from the data platform, it will obtain the information of "Deputy Chief Physician". The confidence of the alternative data can be determined based on the historical rights and interests of each data provider who provides the alternative data, and the confidence of the alternative data is positively correlated with the historical rights and interests of each data provider. Exemplarily, the confidence of the alternative data can be the weighted summation result of the historical rights and interests of each data provider who provides the alternative data.

[0055] In one embodiment, the data platform may also store other alternative data that are not determined as target data, but does not allow the data access party to use them; if in any data provision period after the target data provision period, there is a target alternative data (the target alternative data is any alternative data among the alternative data) whose confidence level is higher than the confidence level of the target data, then the data platform may use the target alternative data as the new target data for use by the data access party. Specifically, if the data platform obtains the target alternative data provided by the data provider for the target data item in any data provision period after the target data provision period, and there are multiple data providers providing the target alternative data, then the data platform may obtain the historical rights and interests of each data provider providing the target alternative data in the data provision period, and determine the confidence level of the target alternative data based on the historical rights and interests of each data provider providing the target alternative data.

[0056] For example, see Figure 3cAs shown, in data provision cycle 1, "deputy chief physician" is determined as the target data of doctor A. In data provision cycle 2, data provision cycle 3 and data provision cycle 4 after data provision cycle 1, data providers provide target alternative data "chief physician" about doctor A. Then, the confidence of "chief physician" can be determined based on the historical equity of 2% of data provider B in data provision cycle 2, the historical equity of 2% of data provider C in data provision cycle 3, and the historical equity of 2% of data provider D in data provision cycle 4. For example, the data platform can be determined based on the sum of the historical equity of the three data providers (i.e., 6%).

[0057] Furthermore, if the confidence of the target candidate data is greater than the confidence of the target data, the target candidate data is used as the target data. Figure 3c As shown, in the fourth data provision cycle, since the sum of the historical rights and interests of the various data providers who provide the target alternative data "chief physician" is greater than the historical rights and interests of data provider A who provides the target data "deputy chief physician", and since the confidence of the alternative data is positively correlated with the historical rights and interests of the various data providers who provide the alternative data, it can be understood that in data provision cycle 4, the confidence of the target alternative data "chief physician" is greater than the confidence of the original target data "deputy chief physician", so the data platform will determine "chief physician" as the new target data.

[0058] S204: Determine a basic data set according to the target data, and send the basic data set to the data access party.

[0059] After the data platform determines the target data, it can determine the basic data set based on the target data, store the basic data set on the data platform, and allow all data access parties to access or download the basic data set on the data platform. In addition, the data platform can also charge the data consumption platform based on the data access party's consumption of the basic data set in the data platform, and distribute the collected fees to the target data provider. Among them, it is not difficult to understand that the more data the data access party consumes, the more value the data access party contributes to the data platform. The more value contributed, the more consumer rights the data access party will have, which in turn increases the historical rights of the data access party.

[0060] After obtaining multiple candidate data for the same data item, the embodiment of the present application determines the target data by obtaining the historical equity of the data providers that provide each candidate data item. Since historical equity is positively correlated with the consumption of the target data provided by each data provider during the historical data provision period, and it is not difficult to understand that high consumption indicates a high number of visits to the target data, the greater the traffic equity brought to the data provider. Therefore, this method can motivate each data provider to provide more and more accurate data as much as possible to improve its own historical equity, thereby enabling the data platform to more efficiently obtain a more comprehensive basic data set.

[0061] See Figure 4 , Figure 4 This is a flow chart of a data processing method provided in an embodiment of the present application. The data processing method can be executed by the data platform mentioned above, such as Figure 4 As shown, the method includes:

[0062] S401: If a query request for a basic data set is received from a data access party, obtain candidate data provided by each of one or more data providers for a target data item in the basic data set within a target data provision period to obtain one or more candidate data.

[0063] In one embodiment, different data providers can provide the same candidate data for a target data item within the target data provision period. That is, the same candidate data can be provided by one or more data providers within the target data provision period. For example, the department name in the department information on the medical data platform, such as dermatology, can be provided by one or more data providers within the target data provision period.

[0064] S402, obtaining the historical rights and interests of each data provider.

[0065] As can be seen from the description of step S202, the historical rights and interests of each data provider are related to the comprehensive rights and interests of the data provider in all historical data provision cycles, and the comprehensive rights and interests of the data provider in the target data provision cycle can be obtained based on the consumption rights and interests and traffic rights of the data provider in the target data provision cycle. Based on this, in one embodiment, the method of determining traffic rights and interests can be as follows: If the target data has not been provided in all historical data provision cycles (that is, the target data appears for the first time in the target data provision cycle), then when the data platform obtains the comprehensive rights and interests of the data provider in the target data provision cycle, it can first determine one or more target data providers that provide the target data in the target data provision cycle. If the number of the one or more target data providers is one, the data platform can determine the consumption of the target data by all data access parties as the consumption of the target data provider, and then obtain the traffic rights and interests of the target data provider based on the consumption. For example, assuming that the target data provision cycle is the third data provision cycle, then the historical data provision cycle includes: the first data provision cycle and the second data provision cycle; further, if the target data "Doctor A" exists in the third target data provision cycle, and only data provider A provides the data "Doctor A" in the first data provision cycle, the second data provision cycle and the third data provision cycle, then, in the third data provision cycle, the consumption corresponding to Doctor A can be used as the consumption of data provider A, and further, the traffic rights corresponding to the consumption can be used as part of the traffic rights of data provider A.

[0066] Furthermore, if the target data provider provides one or more target data within the target data provision period, the data platform can determine the traffic rights and interests of the target data provider in the following manner: the data platform obtains one or more target data of the target data provider within the target data provision period, and obtains the traffic rights and interests corresponding to each target data in the one or more target data, so as to obtain the traffic rights and interests of the target data provider within the target data provision period. In a specific implementation, the data platform can obtain the traffic rights and interests corresponding to the target data in the following manner: the data platform obtains the weight value of the target data item corresponding to the target data, and the consumption of the basic data set where the target data is located; further, the data platform can determine the consumption of the target data based on the weight value of the target data item corresponding to the target data and the consumption of the basic data set where the target data item is located, and then obtain the traffic rights and interests corresponding to all target data provided by the target data provider, and use the sum of the traffic rights and interests corresponding to all target data as the traffic rights and interests of the target data provider within the target data provision period.

[0067] The basic data set may include one or more data items, and the sum of the weight values of the one or more data items is 1. For example, if the basic data set where the target data "XX College" is located is "College Information", then it can be understood that "College Information" may include three data items: College Name, Total Number of College Students, and College Address, and the sum of the weight values of the three data items is 1. Exemplarily, when the basic data set includes m (m ≥ 0, and m is an integer) data items, the sum of the weights of the data items in the basic data set can be shown as Formula 1:

[0068]

[0069] Among them, F i Indicates the weight value of the i-th data item, where i is an integer. For example, the weight values of the various data items in the college information can be assigned by the data platform as shown in Table 1:

[0070] Table 1

[0071] College Information Weight value College Name F＝20％ College Address F＝50％ Total number of students in the college F＝30％

[0072] In a specific embodiment, assuming that the data items of j (j is a positive integer) target data in the one or more target data are data items of the same basic data set, where the data items of different target data are different, then the data platform can obtain the sum of the weight values corresponding to the j target data included in the basic data set in a manner as shown in Formula 2.

[0073]

[0074] Among them, R′ represents the sum of the weight values of the j target data in the basic data set, F i The weight value of the target data item corresponding to the i-th target data among the j target data items is represented by , where i is an integer and i≤j. For example, the weight value of each target data item can be determined by the data platform based on the basic data set in which the target data item is located.

[0075] It is not difficult to understand that when a data provider provides alternative data to a data platform, it does not necessarily bring traffic rights and interests. Traffic rights and interests can only be generated after the alternative data is used by the data access party. That is, if the target data corresponding to the data item comes from data provider A, then the consumption corresponding to the target data and the traffic rights and interests brought by this consumption belong to data provider A; if data provider A provides alternative data for the target data item, but the alternative data is not selected as the target data for use by the data access party, then data provider A does not have the traffic rights and interests brought by the target data corresponding to the target data item. For example, if data provider A provides alternative data a for the data item of school name, and data provider B provides alternative data b for the data item of school name, and alternative data a is used as the target data for the school name, then data provider A will have the traffic rights and interests generated when the data access party queries the school name, and data provider B will not have the traffic rights and interests generated when the data access party queries the school name.

[0076] For example, the data platform may determine the consumption of j target data included in each basic data set by the method shown in Formula 3:

[0077] R=R′×PV Formula 3

[0078] Wherein, R′ represents the sum of the weight values of the j target data in the basic data set, and pv represents the consumption corresponding to the basic data set. For example, pv can represent the total consumption corresponding to the target data of each data item in the basic data set.

[0079] Furthermore, assuming that one or more data items of target data are data items of basic data sets included in the same set of basic data sets, and the set of basic data sets includes one or more basic data sets, the data platform calculates the consumption of all target data provided by the target data provider in a manner as shown in Formula 4:

[0080]

[0081] Wherein, a represents the number of the one or more basic data sets, i represents the i-th basic data set, and a≥i, a and i are both integers; R i represents the consumption of each target data in the i-th basic data set; T represents the sum of the consumption of all target data included in a set of basic data sets.

[0082] Furthermore, assuming that the one or more target data exist in one or more sets of basic data sets, the data platform can calculate the traffic equity of the target data provider based on the method shown in Formula 5:

[0083]

[0084] Among them, S1 represents the traffic rights of the target data provider during the target data provision period, PV represents the sum of the consumption of all basic data sets in the data platform, T i Represents the sum of the consumption corresponding to all target data included in each set of basic data sets. b is the number of one or more sets of basic data sets, and b is a positive integer. Furthermore, after the data platform determines the traffic rights and interests of the target data provider, the data platform can determine the comprehensive rights and interests of the target data provider in the target data provision period based on the traffic rights and interests. It can be understood that the comprehensive rights and interests of the target data provider in the target data provision period are positively correlated with the traffic rights and interests of the target data provider in the target data provision period. For example, when the target data provider has not consumed any basic data set in the data platform, the data platform can directly use the traffic rights and interests as the comprehensive rights and interests of the target data provider.

[0085] In another embodiment, if the target data provider is also a data access provider, that is, if the target data provider also uses the target data in the data platform, then considering that the data access provider is the primary source of commercial value for the data platform, consumer rights can be assigned to the data access provider (or the data provider that can serve as the data access provider) to allow the data access provider to have a certain degree of decision-making power over the accuracy of the data. Specifically, the data platform can determine the consumer rights of the target data provider based on the target data provider's consumption of the target data. For example, the method by which the data platform determines the consumer rights of the target data provider can be shown in Formula 6:

[0086]

[0087] Where V represents the fee paid by the data access party to the data platform for consuming data from the data platform, p represents the number of data access parties on the data platform, and S2 represents the consumer rights of the data access party. It can be understood that when the data access party is also a data provider, S2 can also represent the consumer rights of the data provider (such as the target data provider). Furthermore, after obtaining the consumer rights of the target data provider, the data platform can determine the comprehensive rights of the target data provider in the target data provision period based on the traffic rights and consumer rights. For example, when the target data provider is also a data access party, the data platform can determine the comprehensive rights of the target data provider based on the method shown in Formula 7.

[0088] Si=x×S1+y×S2 Formula 7

[0089] Among them, x+y=1, x and y are the weights of traffic rights and consumption rights, respectively; the data platform has the right to adjust the ratio of x and y. For example, in the early stage of the data platform, there are fewer basic data sets, and x can be appropriately increased. In the later stage of the data platform, there are more basic data sets, and y can be appropriately increased. In actual applications, the data platform can distribute the value of the data platform in the data provision cycle according to the above-mentioned comprehensive rights Si to each data provider based on the data provision cycle (also known as the operation cycle of the block) and its own operating conditions. Through the above-mentioned process of constructing proof of rights, it can be seen that traffic rights and interests are positively correlated with correct alternative data. If the alternative data is wrong, it will eventually not bring rights improvement to the provider of the wrong alternative data (such as: improvement of traffic rights and interests, improvement of historical rights and interests, etc.) because no one accesses it.

[0090] In another embodiment, if the data platform determines that there are multiple target data providers that provide target data, and the target data has not been provided in all historical data provision cycles, then the data platform can determine the traffic rights and interests corresponding to the target data based on the consumption of the target data by the data access party, and then determine the traffic rights and interests of each target data provider in the target data provision cycle according to the traffic rights and interests and the number of target data providers. For example, assuming that there are two data providers that provide target data a during the target data provision cycle, the data platform can first determine the consumption brought by target data a to the data platform, and determine the traffic rights and interests brought by target data a to the data platform based on the consumption (assuming it is b). Further, the data platform can distribute the traffic rights and interests b to the two data providers according to the number of data providers (i.e., 2). For example, the data platform can evenly distribute the traffic rights and interests among the multiple target data providers to each of the multiple target data providers. Please refer to Table 2, which shows the distribution of traffic rights and interests brought by the same alternative data after the data platform obtains the same alternative data provided by different data providers within the target data provision cycle.

[0091] Table 2

[0092] Data provider Traffic rights Alternative data provided P1 S1＝1％ Zhang San's job title: Chief Physician P2 S1＝1％ Zhang San's job title: Chief Physician P3 S1＝1％ Zhang San's job title: Chief Physician P4 S1＝1％ Zhang San's job title: Chief Physician P5 S1＝1％ Zhang San's job title: Chief Physician

[0093] It can be seen that since data providers P1, P2, P3, P4 and P5 all provided the alternative data "Zhang San's title: Chief Physician", the data platform can distribute the traffic rights (5%) generated after "Zhang San's title: Chief Physician" is used as the target data equally to the above five data providers.

[0094] Based on the above description, it can be understood that if within the target data provision cycle, the number of target data providers providing target data is one, and in all historical data provision cycles before the target data provision cycle, no data provider provides the target data, then the traffic rights and interests corresponding to the consumption of the target data will be exclusively owned by the one target data provider; for example, if there are N data provision cycles in total, and only data provider A provides alternative data 1 in the N data provision cycles, then after the data platform determines alternative data 1 as the target data, the traffic rights and interests generated by each data access party accessing the target data will belong to data provider A alone. Correspondingly, if within the target data provision period, the number of target data providers providing target data is one, and within the target data provision period and all historical data provision periods before the target data provision period, multiple data providers provide the target data, then the traffic rights and interests generated by the consumption corresponding to the target data can be distributed to the multiple data providers and the target data provider. For example: within the target data provision period, there is one data provider providing target data A, and within all historical data provision periods, there are two data providers providing target data A. Then it can be understood that there are three target data providers corresponding to the target data A. For example, the traffic rights and interests corresponding to the consumption of the target data A can be equally divided among the three target data providers.

[0095] S403: Determine one or more target data providers for each piece of candidate data.

[0096] In one embodiment, if the target data provision cycle is the Nth data provision cycle, N ≥ 2 and N is an integer, then the data platform can obtain one or more data providers that provided each candidate data item in each of the previous N-1 historical data provision cycles. For example, assuming N is 3, the target data item is the address of School A, and in the previous two historical data provision cycles, School A has two addresses, "No. 1, B Street" and "No. 5, B Street", then the data platform can obtain the data provider that provided "No. 1, B Street" and the data provider that provided "No. 5, B Street".

[0097] Furthermore, the data platform can use all data providers that provided each candidate data item obtained in the previous N-1 data provision cycles as one or more target data providers for that candidate data item. For example, assuming that the data providers providing "No. 1, Street B" in the above example are Data Provider 1 and Data Provider 2, then Data Provider 1 and Data Provider 2 are the target data providers for the data candidate value "No. 1, Street B".

[0098] S404: Acquire the historical rights and interests of each target data provider among the one or more target data providers to obtain one or more historical rights and interests.

[0099] S405 , determining the confidence of each candidate data according to one or more historical rights and interests, and using the candidate data with the highest confidence as the target data.

[0100] In one embodiment, the data platform may perform a weighted sum operation on the historical rights of the data providers who provide each candidate data to obtain the confidence level of each candidate data. For example, please refer to Table 3, which shows a data conflict situation that the data platform may face when obtaining multiple candidate data for the same data item during the target data provision cycle and all historical data provision cycles.

[0101] Table 3

[0102]

[0103]

[0104] It can be seen that P5's historical equity (10%) is greater than the sum of the historical equity of P1, P2, P3 and P4 (4%). Then, according to the situation shown in Table 3, the data platform can determine that the confidence level of "Zhang San's title: deputy chief physician" is higher than the confidence level of "Zhang San's title: chief physician".

[0105] Please continue to refer to Table 4, which also shows a data conflict situation that the data platform may face when obtaining multiple alternative data for the same data item during the target data provision cycle and all historical data provision cycles.

[0106] Table 4

[0107] Data provider Historical Rights Alternative data provided P1 S＝1％ Zhang San's job title: Chief Physician P2 S＝1％ Zhang San's job title: Chief Physician P3 S＝1％ Zhang San's job title: Chief Physician P4 S＝1％ Zhang San's job title: Chief Physician P5 S＝3％ Zhang San's title: Deputy Chief Physician

[0108] It can be seen that although P5's historical equity (3%) is the largest among all data providers, P5's historical equity is less than the sum of the historical equity of P1, P2, P3 and P4 (4%). Then, according to the situation shown in Table 4, the data platform can determine that the confidence of "Zhang San's title: Chief Physician" is higher than the confidence of "Zhang San's title: Deputy Chief Physician". Based on the relevant descriptions of Tables 3 and 4, it is not difficult to understand that when the same data item corresponds to multiple different alternative data, the data platform can use the alternative data with the largest corresponding historical equity as the target data to resolve the data conflicts shown in Tables 3 and 4. It can be seen from the above data conflict resolution method that the root of traffic equity is traffic. By resolving data conflicts based on traffic equity proof, the constructed data platform can have a natural ability to improve itself and be more convenient to open to the outside world on the Internet.

[0109] Furthermore, if the data platform obtains the target data provided by the data provider in the Mth data provision cycle, and keeps the target data unchanged in the Mth data provision cycle, where M>N and M is an integer; then, the data platform can determine the traffic rights and interests of one or more target data providers in the Mth data provision cycle based on the consumption of the target data by the data access party in the Mth data provision cycle, wherein the data provider who provides the target data in the Mth data provision cycle has a traffic right and interest for the target data in the Mth data provision cycle, that is, when the same alternative data of the same target data item is provided, the target data provision cycle in which the alternative data is adopted as the target data, and the data providers who provided the alternative data in all historical data provision cycles before the target data provision cycle are the target data providers, and the data providers who provide the alternative data in subsequent data provision cycles will not obtain the traffic rights and interests generated based on the alternative data.

[0110] It is understandable that although the candidate data was provided before the target data provision period, it was not used as the target data. The candidate data was determined as the target data during the target data provision period. It should be noted that although the candidate data was not used as the target data before the target data provision period, it does not mean that the candidate data is invalid data. Figure 3a As shown, data providers B and C provided the candidate data "Chief Physician." Although the data platform's title information for Doctor A was not changed from "Deputy Chief Physician" to "Chief Physician" because of B and C's provision of the candidate data "Chief Physician," it can be understood that both data providers B and C voted for the candidate data "Chief Physician," and this voting behavior can influence the determination of the target data for Doctor A's title information. For example, after data provider D voted for "Chief Physician" in the fourth data provision cycle, the confidence level for "Chief Physician" reached 6%, exceeding the confidence level of "Deputy Chief Physician" at 5%. Therefore, the data platform will change the target data for Doctor A's title information from "Deputy Chief Physician" to "Chief Physician" in the fourth data provision cycle. Furthermore, the traffic rights and interests generated by the consumption of "Chief Physician" can be equally divided among the three data providers, B, C, and D.

[0111] S406: Determine a basic data set according to the target data, and send the basic data set to the data access party.

[0112] In one embodiment, the relevant embodiments in step S406 can refer to the description in step S204, and the embodiments of this application will not be repeated here.

[0113] based on Figure 2and Figure 4 In accordance with the relevant description, in one embodiment, the data platform may establish a security protection mechanism to prevent data providers from stealing data from the data platform while using the basic data sets of the data platform. For example, the data platform may require the data provider's business to be hosted on the data platform.

[0114] In the embodiment of the present application, the greater the historical rights, the more traffic rights can be brought to the data provider, thereby generating greater economic benefits. Since different data providers are equal and opaque, each data provider in the data platform is in a scene of mutual game. At this time, the data provider maliciously provides false data (fake alternative data) for itself, which is of no benefit. Providing wrong data will not only reduce the rights of the data provider itself, but also be punished accordingly by the data platform. It can be seen that the use of the POS (Proof of Stake) algorithm to construct relevant comprehensive rights can objectively avoid the malicious behavior of each data provider and encourage each data provider to provide more correct data. Therefore, it can be seen that the data processing method provided by the embodiment of the present application can speed up the progress of the data platform in collecting various basic data sets and ensure that the collected basic data sets have a high degree of confidence.

[0115] Based on the description of the above data processing method embodiments, the present application also discloses a data processing device, which may be a computer program (including program code) running on the above-mentioned data platform. The data processing device may execute the following steps: Figure 2 and Figure 4 For the method shown, see Figure 5 The data processing device may at least include: an acquiring unit 501, a determining unit 502 and a sending unit 503.

[0116] The acquisition unit 501 is configured to, upon receiving a query request for a basic data set from a data access party, acquire candidate data provided by each of one or more data providers within a target data provision period for a target data item in the basic data set, thereby obtaining one or more pieces of candidate data;

[0117] The acquisition unit 501 is further configured to acquire the historical rights and interests of each data provider, where the historical rights and interests are obtained based on the comprehensive rights and interests of each data provider in all historical data provision periods before the target data provision period.

[0118] a determining unit 502 configured to determine a confidence level of each candidate data item among the one or more candidate data items, and select the candidate data item with the highest confidence level as the target data item, wherein the confidence level of each candidate data item is determined based on the historical equity of each target data provider among the one or more target data providers providing the candidate data item;

[0119] The sending unit 503 is configured to determine a basic data set according to the target data, and send the basic data set to the data access party.

[0120] In one embodiment, when determining the confidence level of each candidate data in the one or more candidate data, the determining unit 502 is specifically configured to perform:

[0121] determining one or more target data providers for providing each piece of candidate data;

[0122] Acquire the historical rights and interests of each target data provider among the one or more target data providers to obtain one or more historical rights and interests;

[0123] The confidence level of each candidate data is determined according to the one or more historical interests.

[0124] In another embodiment, the target data providing period is the Nth data providing period, where N≥2 and N is an integer; when determining one or more target data providers providing each candidate data, the determining unit 502 is specifically configured to perform:

[0125] Obtain one or more data providers that provided each candidate data in each of the previous N-1 historical data provision periods;

[0126] All data providers that provide each piece of candidate data and are acquired in the first N-1 data providing cycles are used as one or more target data providers for each piece of candidate data.

[0127] In yet another embodiment, the determining unit 502 may be further configured to execute:

[0128] determining one or more target data providers that provide the target data;

[0129] If the target data has not been provided in all historical data provision periods, and the number of one or more target data providers providing the target data in the target data provision period is one, the traffic equity of the target data provider providing the target data is determined based on the consumption of the target data by the data access party, and the traffic equity is positively correlated with the consumption of the target data by the data access party;

[0130] Based on the traffic equity, the comprehensive equity of the target data provider in the target data provision period is determined, and the comprehensive equity of the target data provider in the target data provision period is positively correlated with the traffic equity.

[0131] In another embodiment, the target data provider is the data access party, and the determining unit 502 may further be configured to execute:

[0132] Determining the consumer rights and interests of the target data provider based on the target data provider's consumption of the target data, wherein the consumer rights and interests are positively correlated with the target data provider's consumption of the target data;

[0133] Determining the comprehensive rights and interests of the target data provider in the target data provision period based on the traffic rights and interests includes:

[0134] The comprehensive rights and interests of the target data provider in the target data provision period are determined based on the traffic rights and interests and the consumption rights and interests.

[0135] In yet another embodiment, the determining unit 502 may also be configured to execute:

[0136] determining one or more target data providers that provide the target data;

[0137] If the target data has not been provided in all historical data provision periods, and there are multiple target data providers providing the target data in the target data provision period, the traffic equity of the target data provider providing the target data is determined based on the consumption of the target data by the data access party, and the traffic equity is positively correlated with the consumption of the target data by the data access party;

[0138] The comprehensive equity of each of the one or more target data providers in the target data providing period is determined according to the traffic equity and the number of the target data providers.

[0139] In yet another embodiment, the acquiring unit 501 may also be configured to execute:

[0140] If target candidate data provided by a data provider for the target data item is obtained in any data provision period after the target data provision period, and there are multiple data providers providing the target candidate data, then the historical rights and interests of each data provider providing the target candidate data in the data provision period of providing the target candidate data are obtained;

[0141] The determining unit 502 may also be configured to perform:

[0142] determining the confidence level of the target candidate data according to the historical equity of each data provider providing the target candidate data;

[0143] If the confidence level of the target candidate data is greater than the confidence level of the target data, the target candidate data is used as the target data;

[0144] The sending unit 503 is configured to determine a basic data set according to the target data, and send the basic data set to the data access party.

[0145] In another embodiment, the data processing device further includes a deduction unit 504 and an allocation unit 505, wherein the deduction unit 504 is configured to execute:

[0146] Deduct the total traffic equity of one or more target data providers for the target data in all historical data provision periods before the target candidate data is used as the data provision period for the target data;

[0147] The allocating unit 505 is configured to allocate the deducted traffic equity sum to each data provider that provides the target candidate data.

[0148] In yet another embodiment, the target data providing period is the Nth data providing period, where N is a positive integer, and the determining unit 502 may further be configured to execute:

[0149] If the target data is obtained from the data provider in the Mth data providing period, and the target data remains unchanged during the Mth data providing period, M>N, and M is an integer;

[0150] Based on the consumption of the target data by the data access party in the Mth data provision cycle, the traffic rights of the one or more target data providers in the Mth data provision cycle are determined, and the traffic rights of the data providers who provide the target data in the Mth data provision cycle for the target data in the Mth data provision cycle are zero.

[0151] According to one embodiment of the present application, Figure 2 and Figure 4 The steps involved in the data processing method shown can be Figure 5 The data processing apparatus shown in FIG. 1 is executed by each unit. For example, Figure 2 Step S201 and step S202 shown in FIG. Figure 5 The data processing device shown in FIG. 5 is used to obtain the unit 501; step S203 can be performed by Figure 5The data processing device shown in FIG. 5 is used to determine the unit 502; step S204 can be performed by Figure 5 The sending unit 503 in the data processing device shown in FIG. Figure 4 Steps S401, S402 and S404 shown in FIG. Figure 5 The data processing device shown in FIG. 5 is used to obtain the unit 501; Step S403 and Step S405 can be performed by Figure 5 The data processing device shown in FIG. 5 is used to determine the unit 502; step S406 can be performed by Figure 5 The sending unit 503 in the data processing device shown is executed.

[0152] According to another embodiment of the present application, Figure 5 The various units in the data processing device shown are divided based on logical functions. The above-mentioned various units can be individually or all combined into one or more other units to form a structure, or one (or some) of the units can be further divided into multiple functionally smaller units to form a structure, which can achieve the same operation without affecting the realization of the technical effects of the embodiments of the present application. In other embodiments of the present application, the above-mentioned data processing device can also include other units. In actual applications, these functions can also be implemented with the assistance of other units, and can be implemented by the collaboration of multiple units.

[0153] According to another embodiment of the present application, the program can be executed by running on a general computing device such as a computer including a central processing unit (CPU), a random access memory (RAM), a read-only memory (ROM) and other processing elements and storage elements. Figure 2 or Figure 4 A computer program (including program code) for each step of the method shown is used to construct Figure 5 The data processing device shown in and the data processing method of the embodiment of the present application are implemented. The computer program can be recorded on, for example, a computer storage medium, and loaded into the above-mentioned computing device through the computer storage medium and run therein.

[0154] After obtaining multiple candidate data for the same data item, the embodiment of the present application determines the target data by obtaining the historical equity of the data providers that provide each candidate data item. Since historical equity is positively correlated with the consumption of the target data provided by each data provider during the historical data provision period, and it is not difficult to understand that high consumption indicates a high number of visits to the target data, the greater the traffic equity brought to the data provider. Therefore, this method can motivate each data provider to provide more and more accurate data as much as possible to improve its own historical equity, thereby enabling the data platform to more efficiently obtain a more comprehensive basic data set.

[0155] Based on the description of the above method embodiment and device embodiment, this application also provides a data platform, see Figure 6 The data platform at least includes a processor 601, an output interface 602, and a computer storage medium 603, and the processor 601, output interface 602, and computer storage medium 603 of the data platform can be connected via a bus or other means.

[0156] The computer storage medium 603 is a memory device in the data platform, used to store programs and data. It is understandable that the computer storage medium 603 here can include both the built-in storage medium in the data platform and, of course, the extended storage medium supported by the data platform. The computer storage medium 603 provides storage space, which stores the operating system of the data platform. In addition, the storage space also stores one or more computer programs suitable for being loaded and executed by the processor 601. These computer programs can be one or more program codes. It should be noted that the computer storage medium here can be a high-speed RAM memory or a non-volatile memory (non-volatile memory), such as at least one disk storage; optionally, it can also be at least one computer storage medium located away from the aforementioned processor. The processor 601 (or CPU (Central Processing Unit)) is the computing core and control core of the data platform. It is suitable for implementing one or more computer programs, specifically suitable for loading and executing one or more computer programs to implement the corresponding method flow or corresponding function.

[0157] In one embodiment, the processor 601 may load and execute one or more computer programs stored in the computer storage medium 603 to implement the above-mentioned Figure 2 and Figure 4 The corresponding method steps in the method embodiment shown; in a specific implementation, one or more computer programs in the computer storage medium 603 are loaded by the processor 601 and execute the following steps:

[0158] If a query request for a basic data set is received from a data access party, obtaining candidate data provided by each of one or more data providers for a target data item in the basic data set within a target data provision period, thereby obtaining one or more candidate data;

[0159] Acquire the historical rights and interests of each data provider, where the historical rights and interests are obtained based on the comprehensive rights and interests of each data provider in all historical data provision periods before the target data provision period;

[0160] determining a confidence level of each candidate data piece among the one or more candidate data pieces, and selecting the candidate data piece with the highest confidence level as the target data piece, wherein the confidence level of each candidate data piece is determined based on the historical equity of each target data provider among the one or more target data providers providing the candidate data piece;

[0161] A basic data set is determined according to the target data, and the basic data set is sent to the data access party.

[0162] In one embodiment, when determining the confidence level of each candidate data in the one or more candidate data, the processor 601 is specifically configured to load and execute:

[0163] determining one or more target data providers for providing each piece of candidate data;

[0164] Acquire the historical rights and interests of each target data provider among the one or more target data providers to obtain one or more historical rights and interests;

[0165] The confidence level of each candidate data is determined according to the one or more historical interests.

[0166] In another embodiment, the target data providing period is the Nth data providing period, where N≥2 and N is an integer; when determining one or more target data providers providing each candidate data, the processor 601 is specifically configured to load and execute:

[0167] Obtain one or more data providers that provided each candidate data in each of the previous N-1 historical data provision periods;

[0168] All data providers that provide each piece of candidate data and are acquired in the first N-1 data providing cycles are used as one or more target data providers for each piece of candidate data.

[0169] In yet another embodiment, the processor 601 may also be configured to load and execute:

[0170] determining one or more target data providers that provide the target data;

[0171] If the target data has not been provided in all historical data provision periods, and the number of one or more target data providers providing the target data in the target data provision period is one, the traffic equity of the target data provider providing the target data is determined based on the consumption of the target data by the data access party, and the traffic equity is positively correlated with the consumption of the target data by the data access party;

[0172] Based on the traffic equity, the comprehensive equity of the target data provider in the target data provision period is determined, and the comprehensive equity of the target data provider in the target data provision period is positively correlated with the traffic equity.

[0173] In another embodiment, the target data provider is the data access party, and the processor 601 may further be configured to load and execute:

[0174] Determining the consumer rights and interests of the target data provider based on the target data provider's consumption of the target data, wherein the consumer rights and interests are positively correlated with the target data provider's consumption of the target data;

[0175] Determining the comprehensive rights and interests of the target data provider in the target data provision period based on the traffic rights and interests includes:

[0176] The comprehensive rights and interests of the target data provider in the target data provision period are determined based on the traffic rights and interests and the consumption rights and interests.

[0177] In yet another embodiment, the processor 601 may also be configured to load and execute:

[0178] determining one or more target data providers that provide the target data;

[0179] If the target data has not been provided in all historical data provision periods, and there are multiple target data providers providing the target data in the target data provision period, the traffic equity of the target data provider providing the target data is determined based on the consumption of the target data by the data access party, and the traffic equity is positively correlated with the consumption of the target data by the data access party;

[0180] The comprehensive equity of each of the one or more target data providers in the target data providing period is determined according to the traffic equity and the number of the target data providers.

[0181] In yet another embodiment, the processor 601 may also be configured to load and execute:

[0182] If target candidate data provided by a data provider for the target data item is obtained in any data provision period after the target data provision period, and there are multiple data providers providing the target candidate data, then the historical rights and interests of each data provider providing the target candidate data in the data provision period of providing the target candidate data are obtained;

[0183] determining the confidence level of the target candidate data according to the historical equity of each data provider providing the target candidate data;

[0184] If the confidence level of the target candidate data is greater than the confidence level of the target data, the target candidate data is used as the target data;

[0185] The output interface 602 is configured to determine a basic data set according to the target data, and send the basic data set to the data access party.

[0186] In yet another embodiment, the processor 601 may also be configured to load and execute:

[0187] Deduct the total traffic equity of one or more target data providers for the target data in all historical data provision periods before the target candidate data is used as the data provision period for the target data;

[0188] The total amount of the deducted traffic benefits is distributed to each data provider that provides the target candidate data.

[0189] In yet another embodiment, the target data providing cycle is the Nth data providing cycle, where N is a positive integer, and the processor 601 may further be configured to load and execute:

[0190] If the target data is obtained from the data provider in the Mth data providing period, and the target data remains unchanged during the Mth data providing period, M>N, and M is an integer;

[0191] Based on the consumption of the target data by the data access party in the Mth data provision cycle, the traffic rights of the one or more target data providers in the Mth data provision cycle are determined, and the traffic rights of the data providers who provide the target data in the Mth data provision cycle for the target data in the Mth data provision cycle are zero.

[0192] After obtaining multiple candidate data for the same data item, the embodiment of the present application determines the target data by obtaining the historical equity of the data providers that provide each candidate data item. Since historical equity is positively correlated with the consumption of the target data provided by each data provider during the historical data provision period, and it is not difficult to understand that high consumption indicates a high number of visits to the target data, the greater the traffic equity brought to the data provider. Therefore, this method can motivate each data provider to provide more and more accurate data as much as possible to improve its own historical equity, thereby enabling the data platform to more efficiently obtain a more comprehensive basic data set.

[0193] The present application also provides a storage medium that stores a computer program for the above-mentioned data processing method. The computer program includes program instructions. When one or more processors load and execute the program instructions, the description of the data processing method in the embodiment can be implemented, which will not be repeated here. The description of the beneficial effects of adopting the same method will not be repeated here. It is understood that the program instructions can be deployed on one or more devices that can communicate with each other for execution.

[0194] It should be noted that according to one aspect of the embodiments of the present application, a computer program product or computer program is also provided, the computer program product or computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. The processor in the data platform reads the computer instructions from the computer-readable storage medium and then executes the computer instructions, thereby enabling the data platform to perform the above Figure 2 and Figure 4 The data processing method shown in the embodiment is provided in various optional aspects.

[0195] Those skilled in the art will appreciate that all or part of the processes in the above-described method embodiments can be implemented by instructing related hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When executed, the computer program can include the processes in the above-described data processing method embodiments. The computer-readable storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

[0196] The above disclosure is only a partial embodiment of the embodiment of the present application, and of course it cannot be used to limit the scope of rights of the embodiment of the present application. Ordinary technicians in this field can understand that implementing all or part of the processes of the above embodiment and making equivalent changes according to the claims of the embodiment of the present application still fall within the scope of the invention.

Claims

1. A data processing method, characterized in that: include: If a query request for a basic data set is received from a data access party, obtaining candidate data provided by each of one or more data providers for a target data item in the basic data set within a target data provision period, thereby obtaining one or more candidate data; Acquire the historical rights and interests of each data provider, where the historical rights and interests are obtained based on the comprehensive rights and interests of each data provider in all historical data provision periods before the target data provision period; determining a confidence level of each candidate data piece among the one or more candidate data pieces, and selecting the candidate data piece with the highest confidence level as the target data piece, wherein the confidence level of each candidate data piece is determined based on the historical equity of each target data provider among the one or more target data providers providing the candidate data piece; Determine a basic data set according to the target data, and send the basic data set to the data access party; determining one or more target data providers that provide the target data; If the target data has not been provided in all historical data provision periods, and the number of one or more target data providers providing the target data in the target data provision period is one, the traffic equity of the target data provider providing the target data is determined based on the consumption of the target data by the data access party, and the traffic equity is positively correlated with the consumption of the target data by the data access party; Based on the traffic equity, the comprehensive equity of the target data provider in the target data provision period is determined, and the comprehensive equity of the target data provider in the target data provision period is positively correlated with the traffic equity.

2. The method according to claim 1, characterized in that Determining the confidence level of each candidate data in the one or more candidate data includes: determining one or more target data providers for providing each piece of candidate data; Acquire the historical rights and interests of each target data provider among the one or more target data providers to obtain one or more historical rights and interests; The confidence level of each candidate data is determined according to the one or more historical interests.

3. The method according to claim 2, characterized in that The target data providing period is the Nth data providing period, where N≥2 and N is an integer; and determining one or more target data providers for each candidate data includes: Obtain one or more data providers that provided each candidate data in each of the previous N-1 historical data provision periods; All data providers that provide each piece of candidate data and are acquired in the first N-1 data providing cycles are used as one or more target data providers for each piece of candidate data.

4. The method according to claim 1, wherein The target data provider is the data access party, and the method further includes: Determining the consumer rights and interests of the target data provider based on the target data provider's consumption of the target data, wherein the consumer rights and interests are positively correlated with the target data provider's consumption of the target data; Determining the comprehensive rights and interests of the target data provider in the target data provision period based on the traffic rights and interests includes: The comprehensive rights and interests of the target data provider in the target data provision period are determined based on the traffic rights and interests and the consumption rights and interests.

5. The method according to claim 1, wherein The method further comprises: determining one or more target data providers that provide the target data; If the target data has not been provided in all historical data provision periods, and there are multiple target data providers providing the target data in the target data provision period, the traffic equity of the target data provider providing the target data is determined based on the consumption of the target data by the data access party, and the traffic equity is positively correlated with the consumption of the target data by the data access party; The comprehensive equity of each of the one or more target data providers in the target data providing period is determined according to the traffic equity and the number of the target data providers.

6. The method according to claim 1, characterized in that The method further comprises: If target candidate data provided by a data provider for the target data item is obtained in any data provision period after the target data provision period, and there are multiple data providers providing the target candidate data, then the historical rights and interests of each data provider providing the target candidate data in the data provision period of providing the target candidate data are obtained; determining the confidence level of the target candidate data according to the historical equity of each data provider providing the target candidate data; If the confidence level of the target candidate data is greater than the confidence level of the target data, the target candidate data is used as the target data; A basic data set is determined according to the target data, and the basic data set is sent to the data access party.

7. The method according to claim 6, characterized in that The method further comprises: Deduct the total traffic equity of one or more target data providers for the target data in all historical data provision periods before the target candidate data is used as the data provision period for the target data; The total amount of the deducted traffic benefits is distributed to each data provider that provides the target candidate data.

8. The method according to claim 1, characterized in that The target data providing period is the Nth data providing period, where N is a positive integer, and the method further includes: If the target data is obtained from the data provider in the Mth data providing period, and the target data remains unchanged during the Mth data providing period, M>N, and M is an integer; Based on the consumption of the target data by the data access party in the Mth data provision cycle, the traffic rights of the one or more target data providers in the Mth data provision cycle are determined, and the traffic rights of the data providers who provide the target data in the Mth data provision cycle for the target data in the Mth data provision cycle are zero.

9. A data processing device, characterized in that: include: an acquiring unit configured to, upon receiving a query request for a basic data set from a data access party, acquire candidate data provided by each of one or more data providers for a target data item in the basic data set within a target data provision period, thereby obtaining one or more pieces of candidate data; The acquisition unit is further configured to acquire the historical rights and interests of each data provider, where the historical rights and interests are obtained based on the comprehensive rights and interests of each data provider in all historical data provision periods before the target data provision period; a determining unit, configured to determine a confidence level of each candidate data piece among the one or more candidate data pieces, and select the candidate data piece with the highest confidence level as the target data piece, wherein the confidence level of each candidate data piece is determined based on the historical equity of each target data provider among the one or more target data providers providing the candidate data piece; a sending unit, configured to determine a basic data set according to the target data, and send the basic data set to the data access party; The determining unit is further configured to determine one or more target data providers that provide the target data; If the target data has not been provided in all historical data provision periods, and the number of one or more target data providers providing the target data in the target data provision period is one, the traffic equity of the target data provider providing the target data is determined based on the consumption of the target data by the data access party, and the traffic equity is positively correlated with the consumption of the target data by the data access party; Based on the traffic equity, the comprehensive equity of the target data provider in the target data provision period is determined, and the comprehensive equity of the target data provider in the target data provision period is positively correlated with the traffic equity.

10. A computer-readable storage medium comprising a computer program, characterized in that When the computer program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

11. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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