Data processing method, device, apparatus and computer readable medium

Abstract

The present invention discloses a method, device, equipment and computer-readable medium for data processing, and relates to the field of cloud computing technology. A specific implementation of the method includes: clustering multiple data parties to obtain a data processing alliance based on the characteristics of the data party; configuring the shared processing mode of the data processing alliance and the independent processing mode of each data party in the data processing alliance; processing the interactive data of the data parties under the data processing alliance based on the shared processing mode and the independent processing mode; and displaying the parameters of the processed interactive data according to the data processing alliance and the data parties under the data processing alliance. This implementation can display the parameters of the same account after cooperation with different partners.

Description

Technical Field

[0001] The present invention relates to the field of cloud computing technology, and in particular to a data processing method, device, equipment and computer-readable medium. Background Art

[0002] The continuous development of Internet finance and third-party payment platforms has brought numerous financial technology dividends and conveniences, but problems have also gradually emerged. With the deepening of supervision, payment platforms and large online merchant customers have received more attention and restrictions in terms of real-name, payment, and fund supervision.

[0003] The overseas model of using a universal account means that one wallet account is used for all partners. Except that traditional offline channels cannot swipe cards, other online channels are no different from offline physical cards. The overseas model of using a dedicated account means that one wallet account is used for a specific partner. However, due to the large number of partners, each partner needs to open a separate account, which easily leads to a waste of account resources.

[0004] In the process of implementing the present invention, the inventors found that there are at least the following problems in the prior art: due to the deep coupling of account functions and scenarios, it is difficult to display the parameters of the same account after cooperation with different partners. Summary of the invention

[0005] In view of this, embodiments of the present invention provide a data processing method, apparatus, device, and computer-readable medium, which can display parameters of the same account after cooperation with different partners.

[0006] To achieve the above object, according to one aspect of an embodiment of the present invention, a data processing method is provided, comprising:

[0007] Based on the characteristics of data cubes, multiple data cubes are clustered to obtain a data processing alliance;

[0008] Configuring a shared processing mode of the data processing alliance and an independent processing mode of each data party in the data processing alliance;

[0009] Based on the shared processing mode and the independent processing mode, process the interactive data of the data parties under the data processing alliance;

[0010] According to the data processing alliance and the data parties under the data processing alliance, the parameters of the processed interactive data are displayed.

[0011] The characteristics of the data subject include one or more of user payment method, business type and user rights and interests.

[0012] The method of clustering multiple data cubes according to the characteristics of the data cubes to obtain a data processing alliance includes:

[0013] According to the characteristics of the data party, the data processing alliance is successfully matched, and the data processing alliance is obtained by clustering multiple data parties;

[0014] Adding the data party to the data processing federation.

[0015] The method of clustering multiple data cubes according to the characteristics of the data cubes to obtain a data processing alliance includes:

[0016] According to the characteristics of the data party, the data processing alliance is not successfully matched, and the data processing alliance is obtained by clustering multiple data parties;

[0017] A new data processing alliance is created according to the characteristics of the data cube, and the data cube is added to the newly created data processing alliance.

[0018] The shared processing method includes one or more of the following: number of accounts opened, product type, transaction account limit, transaction merchant and transaction channel.

[0019] The independent processing method includes one or more of the following: number of accounts opened, product type, transaction account limit, transaction merchant and transaction channel.

[0020] The priority of the shared processing mode is higher than the priority of the independent processing mode.

[0021] The shared processing method includes shared user information of data parties in the data processing alliance and shared user rights and interests of data parties in the data processing alliance.

[0022] The shared user information includes one or more of the following: user activities, user financial shelves, and advertising-guided traffic.

[0023] The shared user rights include one or more of the following: coupons, discount activities, user points and user sign-in discounts.

[0024] The processing of the interactive data of the data parties under the data processing alliance based on the shared processing mode and the independent processing mode includes:

[0025] Based on the shared processing method, process the interactive data of the data parties under the data processing alliance;

[0026] The interactive data processed by the shared processing method is processed according to the independent processing method.

[0027] The processing of the interactive data of the data parties under the data processing alliance based on the shared processing mode and the independent processing mode includes:

[0028] Based on the shared processing mode and the independent processing mode, the interactive data of the data parties under the data processing alliance are screened out;

[0029] The expenditure detail data and income detail data of the interaction data are obtained from the interaction data of the data parties under the data processing alliance.

[0030] The expenditure detail data includes one or more of the following information: payer, payment amount and payment time.

[0031] The income detail data includes one or more of the following information: income source, income amount and income time.

[0032] The parameters of the processed interactive data are displayed according to the data processing alliance and the data parties under the data processing alliance, including:

[0033] According to the data processing alliance, display the parameters of the processed interactive data in the data processing alliance;

[0034] According to the data party under the data processing alliance, the parameters of the processed interactive data in the data party under the data processing alliance are displayed.

[0035] The parameters of the interaction data include one or more of the following: recharge, consumption, income and withdrawal.

[0036] The method further comprises:

[0037] A joint account of the data processing alliance is established, and the joint account is determined by the individual accounts of the data parties under the data processing alliance.

[0038] According to a second aspect of an embodiment of the present invention, there is provided a data processing device, including:

[0039] The clustering module is used to cluster multiple data cubes according to the characteristics of the data cubes to obtain a data processing alliance;

[0040] A configuration module, used to configure the shared processing mode of the data processing alliance and the independent processing mode of each data party in the data processing alliance;

[0041] A processing module, used for processing the interactive data of the data parties under the data processing alliance based on the shared processing mode and the independent processing mode;

[0042] The display module is used to display the parameters of the processed interactive data according to the data processing alliance and the data parties under the data processing alliance.

[0043] According to a third aspect of an embodiment of the present invention, there is provided an electronic device for data processing, comprising:

[0044] one or more processors;

[0045] a storage device for storing one or more programs,

[0046] When the one or more programs are executed by the one or more processors, the one or more processors implement the above method.

[0047] According to a fourth aspect of an embodiment of the present invention, there is provided a computer-readable medium on which a computer program is stored, and when the program is executed by a processor, the method as described above is implemented.

[0048] An embodiment of the above invention has the following advantages or beneficial effects: based on the characteristics of the data party, multiple data parties are clustered to obtain a data processing alliance; the shared processing mode of the data processing alliance and the independent processing mode of each data party in the data processing alliance are configured; based on the shared processing mode and the independent processing mode, the interactive data of the data parties under the data processing alliance are processed; according to the data processing alliance and the data parties under the data processing alliance, the parameters of the processed interactive data are displayed. With the data processing alliance as the basis for processing interactive data, the data party to which the account belongs and other partners belong to the same data processing alliance, so the parameters of the same account after cooperation with different partners can be displayed.

[0049] The further effects of the above-mentioned non-conventional optional manner will be described below in conjunction with specific implementation examples. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] The accompanying drawings are used to better understand the present invention and do not constitute an improper limitation of the present invention.

[0051] Figure 1 is a schematic diagram of the main flow of a data processing method according to an embodiment of the present invention;

[0052] Figure 2 is a schematic diagram of data processing alliance clustering according to an embodiment of the present invention;

[0053] Figure 3 is a schematic diagram of a process of clustering multiple data cubes to obtain a data processing alliance according to an embodiment of the present invention;

[0054] Figure 4 is another flowchart of clustering multiple data cubes to obtain a data processing alliance according to an embodiment of the present invention;

[0055] Figure 5 is a schematic diagram of a shared processing method and an independent processing method according to an embodiment of the present invention;

[0056] Figure 6is a schematic diagram of sharing user information and sharing user rights according to an embodiment of the present invention;

[0057] Figure 7 is a schematic diagram of a process for processing interactive data of a data party under a data processing alliance according to an embodiment of the present invention;

[0058] Figure 8 is a schematic diagram of account details according to an embodiment of the present invention;

[0059] Fig. 9 is a schematic diagram of the main structure of a data processing device according to an embodiment of the present invention;

[0060] Fig.10 is an exemplary system architecture diagram to which embodiments of the present invention may be applied;

[0061] Fig.11 It is a schematic diagram of the structure of a computer system of a terminal device or a server suitable for implementing an embodiment of the present invention. DETAILED DESCRIPTION

[0062] The following is a description of exemplary embodiments of the present invention in conjunction with the accompanying drawings, including various details of the embodiments of the present invention to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present invention. Similarly, for clarity and conciseness, the description of well-known functions and structures is omitted in the following description.

[0063] Payment platforms and large online merchants are receiving more attention and restrictions in terms of real-name verification, payment, and fund supervision. Taking this opportunity, commercial banks have gradually begun to leverage their financial technology advantages, actively exploring new models of cooperation between merchants and third-party payment businesses on the merchant side; on the user side, they have implanted Internet genes, seamlessly entered the ecological scene, broken through traditional thinking, and tried to innovate traditional banking service methods and business models through overseas account expansion.

[0064] Breaking through the original card issuance model, opening second and third-type accounts in third-party scenarios to realize overseas accounts is currently an important model for commercial banks and third-party partners. However, there are currently the following problems with overseas accounts in this model:

[0065] Problem 1: The overseas model of using a universal account, that is, one wallet account is applied to all partners. The universality of the account determines that the overseas model of the account cannot be customized according to the partner, and it is difficult to complete the scene construction according to different ecosystems. Finally, the account balance and account details are no different from traditional bank accounts, and it is impossible to isolate partners and provide differentiated registration.

[0066] Question 2: Using a dedicated account model for going overseas, that is, a wallet account is used for a specific partner. The advantage is that the e-wallet can be customized according to different partner ecosystem scenarios. However, due to the large number of partners, each partner opens a separate account, which is likely to cause a waste of account resources, which is also contrary to the idea of ​​limiting the number of accounts in the account classification management mechanism.

[0067] With a general account, the account function is deeply coupled with multiple scenarios; with a dedicated account, the account function is deeply coupled with a specific scenario. Since the account function is deeply coupled with the scenario, it is difficult to display the parameters of the same account after cooperating with different partners.

[0068] In order to solve the problem of difficulty in displaying parameters of the same account after cooperation with different partners, the following technical solution in the embodiment of the present invention may be adopted.

[0069] See also Figure 1 , Figure 1 Schematic diagram of the main flow of the data processing method according to an embodiment of the present invention, using a data processing alliance to configure independent processing mode and shared processing mode, and then displaying the parameters of the interactive data. Figure 1 As shown, the specific steps include:

[0070] S101. Cluster multiple data cubes according to the characteristics of the data cubes to obtain a data processing alliance.

[0071] In the embodiments of the present invention, the data party is an application involving multiple users. As an example, the data party is a third party or a partner. As an example, the data party is an application APP installed on a mobile terminal. Or, it is a user in social media, etc. Through the data party, users can purchase goods or exchange information with other users.

[0072] For data parties, data related to users. The users involved in multiple data parties overlap. For data parties related to the same user, the interaction data with the user can be displayed in the same way. As an example, data party A and data party B both involve user a. Then, data party A and data party B can share the same account of user a, and user a can get discounts from data party A and data party B.

[0073] For similar data entities that share an account, multiple data entities can be clustered into a data processing alliance based on their characteristics. In this way, data entities of the same type are included in one data processing alliance.

[0074] In one embodiment of the present invention, the characteristics of the data entity include one or more of user payment methods, business types, and user rights. As an example, the user payment method includes payment for bills, cash payment, purchase payment, or travel payment. Business types are the types of business involved in the data entity. As an example, business types include fund transactions, financial transactions, and precious metal transactions. User rights are the benefits enjoyed by the user. As an example, user rights include points and vouchers.

[0075] See also Figure 2 , Figure 2 is a schematic diagram of data processing alliance clustering according to an embodiment of the present invention. Figure 2 The clustering elements of the first data processing alliance are shown in Figure 1. Specifically, the clustering elements of the first data processing alliance are the characteristics of the data party, including user payment methods, business types, and user rights.

[0076] Among them, user payment methods include payment, purchase and travel. The weight of payment is 30%, the weight of purchase is 50%, and the weight of travel is 20%. Business types include funds, financial management and precious metals. The weight of funds is 40%, the weight of financial management is 30%, and the weight of precious metals is 30%. User rights include points and vouchers. The weight of points is 40%, and the weight of vouchers is 60%. Different clustering elements can also be set for other data processing alliances.

[0077] See also Figure 3 , Figure 3 The flowchart of clustering multiple data cubes to obtain a data processing alliance according to an embodiment of the present invention specifically includes the following steps:

[0078] S301. Successfully match a data processing alliance based on the characteristics of the data party. The data processing alliance is obtained by clustering multiple data parties.

[0079] For each data cube, a data processing alliance is matched according to the characteristics of the data cube. The data processing alliance is obtained by clustering multiple data cubes. In other words, if a data processing alliance is successfully matched, it means that the data cube is similar to the data cube in the successfully matched data processing alliance.

[0080] S302. Add the data party to the data processing alliance.

[0081] Since the data party successfully matches the data processing alliance, the data party can be added to the data processing alliance.

[0082] As an example, clustering based on the characteristics of data party A is found to be most similar to the first data processing alliance, so data party A can join the first data processing alliance. Clustering based on the characteristics of data party B is found to be most similar to the second data processing alliance, so data party B can join the second data processing alliance.

[0083] exist Figure 3 In the embodiment, if the data party is successfully matched to the data processing alliance, the data party is added to the data processing alliance.

[0084] See also Figure 4 , Figure 4 FIG. 1 is another flow chart of clustering multiple data cubes to obtain a data processing alliance according to an embodiment of the present invention, which specifically includes:

[0085] S401. According to the characteristics of the data cube, a data processing alliance is not successfully matched. The data processing alliance is obtained by clustering multiple data cubes.

[0086] The data processing alliance is obtained by clustering multiple data cubes. If the data cube is not successfully matched to a data processing alliance based on its characteristics, it means that the data cube is not similar to any current data processing alliance.

[0087] S402. Create a new data processing alliance according to the characteristics of the data party, and add the data party to the newly created data processing alliance.

[0088] If the data party is not similar to any current data processing alliance, a new data processing alliance needs to be created. Specifically, a new data processing alliance is created according to the characteristics of the data party, and the data party is added to the newly created data processing alliance.

[0089] As an example, if clustering is performed based on the characteristics of data party A and no data processing alliance is successfully matched, a third data processing alliance is newly created based on the characteristics of data party A, and the third data processing alliance includes data party A.

[0090] exist Figure 4 In the embodiment, if the data party fails to successfully match with the data processing alliance, a new data processing alliance will be created, and the new data processing alliance includes the above-mentioned data party.

[0091] As an example, data party A and data party B are both e-commerce platforms and need to use the account function of a commercial bank as their platform user wallet. Using this wallet, the platform users' payment, user rights, fee payment and fund purchase functions can be realized. Data party A and data party B establish the first data processing alliance. Platform users in the first data processing alliance can use the same wallet account in data party A and data party B. After the user opens it in data party A, it can be used directly in data party B. At the same time, users in the first data processing alliance share account functions and user rights, and have their own independent ledgers and capital pools.

[0092] S102. Configure the shared processing mode of the data processing alliance and the independent processing mode of each data party in the data processing alliance.

[0093] For data parties in the data processing alliance, there are two processing methods involved, namely shared processing and independent processing.

[0094] The shared processing method is a processing method that applies to all data parties in the data processing alliance. The shared processing method includes one or more of the following: number of account openings, product type, trading account limit, trading merchant, and trading channel. As an example, shared account funds belong to the trading account limit. The shared processing method includes shared account funds. The shared account balance is 1,000 yuan. After using 300 yuan in data party A, only 700 yuan can be used in data party B.

[0095] Independent processing is a processing method applicable to specific data parties in the data processing alliance. Independent processing includes one or more of the following: number of accounts opened, product type, transaction account limit, transaction merchant and transaction channel. As an example, if the transaction account limit of data party A is 10,000 yuan, and the user has paid 6,000 yuan to data party A, then the maximum amount of consumption at data party A is 4,000 yuan. The transaction account limit of data party A has nothing to do with the user's consumption at data party B.

[0096] It should be noted that the priority of the shared processing method is higher than that of the independent processing method. In other words, when there is a conflict between the shared processing method and the independent processing method, the shared processing method shall prevail. As an example, the shared processing method includes a transaction account limit of 1,000 yuan, and the independent processing method of data party A includes a transaction account limit of 2,000 yuan. In the above case, the transaction account limit of data party A is 1,000 yuan.

[0097] See also Figure 5 , Figure 5 It is a schematic diagram of a shared processing method and an independent processing method according to an embodiment of the present invention. Figure 5In the , shared processing methods include trading account limits, product types and account opening quantity, as well as the weights of the above three methods. Independent processing methods include trading limits, trading channels, product types and trading merchants, as well as the weights of the above four methods.

[0098] Different from customers and accounts, users refer to registered members on a platform. A customer can register multiple users on different platforms. User rights refer to a series of business activities carried out by third-party platforms around users, such as membership system, full discount activities and sign-in tasks.

[0099] The shared processing method includes two parts. One part is the shared user information of the data party in the data processing alliance, and the other part is the shared user rights and interests of the data party in the data processing alliance. That is, the shared processing method includes the shared user information of the data party in the data processing alliance and the shared user rights and interests of the data party in the data processing alliance. Shared user information includes one or more of the following: user activities, user financial shelves, and advertising-guided traffic. Shared user rights and interests include one or more of the following: coupons, full-reduction activities, user points, and user sign-in discounts.

[0100] By sharing user information, data parties within the same data processing alliance are allowed to share user information and attract traffic to data parties, thereby promoting mutual benefit on the platform. By sharing user rights, data parties within the same data processing alliance can share preferential lists. As an example, a user of data party A signs in at the bank area of ​​data party A and accumulates 10 points. The points can be used at data party B to achieve the purpose of sharing user rights. As another example, within the first data processing alliance, shared user rights include activities of 100-10, which each user is allowed to enjoy once. If user A has already enjoyed the user rights when paying at data party A, user A cannot enjoy the user rights again at data party B.

[0101] See also Figure 6 , Figure 6 2 is a schematic diagram of sharing user information and sharing user rights according to an embodiment of the present invention. Figure 6 The shared user information of the First Data Processing Alliance includes user financial shelves, advertising-guided traffic and user activities. The shared user rights of the First Data Processing Alliance include coupons, full-reduction activities, user points and user sign-in discounts.

[0102] S103. Process the interactive data of the data parties under the data processing alliance based on the shared processing mode and the independent processing mode.

[0103] After determining the shared processing mode and the independent processing mode, the interactive data of the data parties under the data processing alliance can be processed based on the shared processing mode and the independent processing mode. The interactive data is the data between the data party and other data parties or financial institutions. As an example, the interactive data includes the consumption amount, the recharge amount and the income amount.

[0104] Specifically, based on the shared processing method, the interactive data of the data parties under the data processing alliance is processed; according to the independent processing method, the interactive data processed by the shared processing method is processed. Since the priority of the shared processing method is higher than that of the independent processing method, then for the interactive data of the data, the shared processing method is executed first, and then the independent processing method is executed.

[0105] See also Figure 7 , Figure 7 The flowchart of processing interactive data of a data party under a data processing alliance according to an embodiment of the present invention specifically includes the following steps:

[0106] S701. Based on the shared processing mode and the independent processing mode, the interactive data of the data parties under the data processing alliance are screened out.

[0107] For data parties, the interactive data can be screened out based on the shared processing mode and the independent processing mode. That is, based on the shared processing mode and the independent processing mode, the interactive data of the data parties under the data processing alliance are screened out.

[0108] As an example, the shared processing method includes product type 1 and product type 2. The independent processing method includes transaction merchant 1 and transaction merchant 2. In the data of the data party under the data processing alliance, based on the above shared processing method and independent processing method, the interactive data of the data party under the data processing alliance is screened out. The screened interactive data involves at least one of product type 1, product type 2, transaction merchant 1, and transaction merchant 2.

[0109] S702. Obtain expenditure details and income details of the interactive data from the interactive data of the data party under the data processing alliance.

[0110] The interactive data of the data party under the data processing alliance includes expenditure detail data and income detail data. In order to display the expenditure detail data and income detail data in the interactive data, the expenditure detail data and income detail data of the interactive data are obtained in the interactive data of the data party under the data processing alliance. As an example, it is known based on the summary of the detail data that the detail data is expenditure detail data or income detail data.

[0111] The expenditure details include one or more of the following information: payer, payment amount and payment time. The income details include one or more of the following information: income source, income amount and income time.

[0112] See also Figure 8 , Figure 8 is a schematic diagram of account details according to an embodiment of the present invention. Figure 8 The First Data Processing Alliance includes data party A and data party B. The partner account book, that is, the data party account book, records the transaction time, amount, summary and remarks. The account details include detailed data, which include: transaction time, amount, summary and remarks. Among them, the partner account book includes the account book of data party A and the account book of data party B.

[0113] S104. Display parameters of the processed interactive data according to the data processing alliance and the data parties under the data processing alliance.

[0114] For each data party, they all belong to the data processing alliance. From the perspective of the data processing alliance, the parameters of the processed interaction data are displayed according to the data processing alliance. The parameters of the processed interaction data are displayed to the user according to the data processing alliance. As an example, the parameters of the interaction data include one or more of the following: recharge, consumption, income and withdrawal.

[0115] In addition, from the perspective of the data party, the parameters of the processed interactive data in the data party under the data processing alliance are displayed according to the data party under the data processing alliance. The parameters of the processed interactive data in the data party are displayed to the user.

[0116] It is understandable that the parameters of the processed interactive data can be displayed according to the data processing alliance or according to the data party.

[0117] In one embodiment of the present invention, a joint account of a data processing alliance is established, and the joint account is determined by the individual accounts of the data parties under the data processing alliance. Since the data processing alliance has multiple data parties, in order to facilitate the processing of data of the data parties in the data processing alliance, a joint account and an individual account are established.

[0118] The joint account is based on the premise of the same data processing alliance, and an independent individual account is established for each data party. The balance of the individual account is accumulated as the balance of the joint account. Each individual account is assigned different keys according to different platforms to manage the funds held by users on different platforms and the use of funds. Balance separation and account integration can be achieved. It is understandable that a personal account can be a fund pool.

[0119] As an example, Xiao Li opens an account in the First Data Processing Alliance, which includes Data Cube A and Data Cube B. Xiao Li recharges 1,000 yuan in Data Cube A and spends 100 yuan. The balance of Data Cube A's individual account is 900 yuan. In the joint account, the balance is 900 yuan. Xiao Li recharges 500 yuan in Data Cube B and then purchases 200 yuan of funds. The balance of Data Cube B's individual account is 300 yuan. At this point, the balance of the joint account is 1,200 yuan.

[0120] In the above embodiment, according to the characteristics of the data party, multiple data parties are clustered to obtain a data processing alliance; the shared processing mode of the data processing alliance and the independent processing mode of each data party in the data processing alliance are configured; based on the shared processing mode and the independent processing mode, the interactive data of the data parties under the data processing alliance are processed; according to the data processing alliance and the data parties under the data processing alliance, the parameters of the processed interactive data are displayed. With the data processing alliance as the basis for processing interactive data, the data party to which the account belongs and other partners belong to the same data processing alliance, so the parameters of the same account after cooperation with different partners can be displayed.

[0121] See also Fig. 9 , Fig. 9 is a schematic diagram of the main structure of a data processing device according to an embodiment of the present invention. The data processing device can implement a data processing method, such as Fig. 9 As shown, the data processing device specifically includes:

[0122] A clustering module 901 is used to cluster multiple data cubes according to the characteristics of the data cubes to obtain a data processing alliance;

[0123] Configuration module 902, used to configure the shared processing mode of the data processing alliance and the independent processing mode of each data party in the data processing alliance;

[0124] A processing module 903, configured to process the interactive data of the data parties under the data processing alliance based on the shared processing mode and the independent processing mode;

[0125] The display module 904 is used to display the parameters of the processed interactive data according to the data processing alliance and the data parties under the data processing alliance.

[0126] In one embodiment of the present invention, the characteristics of the data subject include one or more of user payment method, business type and user rights and interests.

[0127] In one embodiment of the present invention, the clustering module 901 is specifically used to successfully match a data processing alliance based on the characteristics of a data cube, wherein the data processing alliance is obtained by clustering multiple data cubes;

[0128] Adding the data party to the data processing federation.

[0129] In one embodiment of the present invention, the clustering module 901 is specifically used to match the data processing alliance unsuccessfully based on the characteristics of the data cube, wherein the data processing alliance is obtained by clustering multiple data cubes;

[0130] A new data processing alliance is created according to the characteristics of the data cube, and the data cube is added to the newly created data processing alliance.

[0131] In one embodiment of the present invention, the shared processing method includes one or more of the following: number of account openings, product type, transaction account limit, transaction merchant and transaction channel.

[0132] In one embodiment of the present invention, the independent processing method includes one or more of the following: number of account openings, product type, transaction account limit, transaction merchant and transaction channel.

[0133] In one embodiment of the present invention, the priority of the shared processing mode is higher than the priority of the independent processing mode.

[0134] In one embodiment of the present invention, the shared processing method includes shared user information of data parties in the data processing alliance and shared user rights and interests of data parties in the data processing alliance.

[0135] In one embodiment of the present invention, the shared user information includes one or more of the following: user activities, user financial shelves, and advertising-guided traffic.

[0136] In one embodiment of the present invention, the shared user rights and interests include one or more of the following: coupons, full-discount activities, user points and user sign-in discounts.

[0137] In one embodiment of the present invention, the processing module 903 is specifically used to process the interactive data of the data parties under the data processing alliance based on the shared processing mode;

[0138] The interactive data processed by the shared processing method is processed according to the independent processing method.

[0139] In one embodiment of the present invention, the processing module 903 is specifically used to filter out the interactive data of the data parties under the data processing alliance based on the shared processing mode and the independent processing mode;

[0140] The expenditure detail data and income detail data of the interaction data are obtained from the interaction data of the data parties under the data processing alliance.

[0141] In one embodiment of the present invention, the expenditure detail data includes one or more of the following information: payer, payment amount and payment time.

[0142] In one embodiment of the present invention, the income detail data includes one or more of the following information: income source, income amount and income time.

[0143] In one embodiment of the present invention, the display module 904 is specifically configured to display parameters of the processed interaction data in the data processing alliance according to the data processing alliance;

[0144] According to the data party under the data processing alliance, the parameters of the processed interactive data in the data party under the data processing alliance are displayed.

[0145] In one embodiment of the present invention, the parameters of the interaction data include one or more of the following: recharge, consumption, income and withdrawal.

[0146] In one embodiment of the present invention, the processing module 903 is further used to establish a joint account of the data processing alliance, and the joint account is determined by the individual accounts of the data parties under the data processing alliance.

[0147] Fig.10 An exemplary system architecture 1000 is shown to which the data processing method or data processing apparatus according to the embodiment of the present invention can be applied.

[0148] like Fig.10 As shown, the system architecture 1000 may include terminal devices 1001, 1002, 1003, a network 1004, and a server 1005. The network 1004 is used to provide a medium for communication links between the terminal devices 1001, 1002, 1003 and the server 1005. The network 1004 may include various connection types, such as wired, wireless communication links, or optical fiber cables, etc.

[0149] Users can use terminal devices 1001, 1002, 1003 to interact with server 1005 through network 1004 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 1001, 1002, 1003, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social platform software, etc. (only as examples).

[0150] The terminal devices 1001 , 1002 , and 1003 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop computers, and desktop computers, etc.

[0151] The server 1005 may be a server that provides various services, such as a backend management server (only an example) that provides support for shopping websites browsed by users using the terminal devices 1001, 1002, and 1003. The backend management server may analyze and process the received product information query request and other data, and feed back the processing results (such as target push information, product information - only an example) to the terminal device.

[0152] It should be noted that the data processing method provided in the embodiment of the present invention is generally executed by the server 1005 , and accordingly, the data processing device is generally set in the server 1005 .

[0153] It should be understood that Fig.10 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to implementation requirements.

[0154] Reference below Fig.11 , which shows a schematic diagram of the structure of a computer system 1100 of a terminal device suitable for implementing an embodiment of the present invention. Fig.11 The terminal device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0155] like Fig.11 As shown, the computer system 1100 includes a central processing unit (CPU) 1101, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1102 or a program loaded from a storage portion 1108 into a random access memory (RAM) 1103. In the RAM 1103, various programs and data required for the operation of the system 1100 are also stored. The CPU 1101, the ROM 1102, and the RAM 1103 are connected to each other via a bus 1104. An input / output (I / O) interface 1105 is also connected to the bus 1104.

[0156] The following components are connected to the I / O interface 1105: an input section 1106 including a keyboard, a mouse, etc.; an output section 1107 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 1108 including a hard disk, etc.; and a communication section 1109 including a network interface card such as a LAN card, a modem, etc. The communication section 1109 performs communication processing via a network such as the Internet. A drive 1110 is also connected to the I / O interface 1105 as needed. A removable medium 1111, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 1110 as needed, so that a computer program read therefrom is installed into the storage section 1108 as needed.

[0157] In particular, according to the embodiments disclosed in the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present invention include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 1109, and / or installed from the removable medium 1111. When the computer program is executed by the central processing unit (CPU) 1101, the above-mentioned functions defined in the system of the present invention are executed.

[0158] It should be noted that the computer-readable medium shown in the present invention may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In the present invention, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0159] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present invention. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0160] The modules involved in the embodiments of the present invention may be implemented by software or hardware. The modules described may also be set in a processor. For example, they may be described as: a processor includes a clustering module, a configuration module, a processing module, and a display module. The names of these modules do not, in some cases, constitute limitations on the modules themselves. For example, the clustering module may also be described as "used to cluster multiple data cubes according to the characteristics of the data cubes to obtain a data processing alliance."

[0161] As another aspect, the present invention further provides a computer-readable medium, which may be included in the device described in the above embodiment; or may exist independently without being assembled into the device. The above computer-readable medium carries one or more programs, and when the above one or more programs are executed by a device, the device includes:

[0162] Based on the characteristics of data cubes, multiple data cubes are clustered to obtain a data processing alliance;

[0163] Configuring a shared processing mode of the data processing alliance and an independent processing mode of each data party in the data processing alliance;

[0164] Based on the shared processing mode and the independent processing mode, process the interactive data of the data parties under the data processing alliance;

[0165] According to the data processing alliance and the data parties under the data processing alliance, the parameters of the processed interactive data are displayed.

[0166] According to the technical solution of the embodiment of the present invention, based on the characteristics of the data party, multiple data parties are clustered to obtain a data processing alliance; the shared processing mode of the data processing alliance and the independent processing mode of each data party in the data processing alliance are configured; based on the shared processing mode and the independent processing mode, the interactive data of the data parties under the data processing alliance are processed; according to the data processing alliance and the data parties under the data processing alliance, the parameters of the processed interactive data are displayed. With the data processing alliance as the basis for processing interactive data, the data party to which the account belongs and other partners belong to the same data processing alliance, so the parameters of the same account after cooperation with different partners can be displayed.

[0167] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may occur depending on design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for data processing, characterized in that: include: Based on the characteristics of data cubes, multiple data cubes are clustered to obtain a data processing alliance; Configuring a shared processing mode of the data processing alliance and an independent processing mode of each data party in the data processing alliance; Based on the shared processing mode and the independent processing mode, process the interactive data of the data parties under the data processing alliance; Displaying parameters of the processed interactive data according to the data processing alliance and the data parties under the data processing alliance; The shared processing method includes shared user information of data parties in the data processing alliance and shared user rights and interests of data parties in the data processing alliance; The processing of the interactive data of the data parties under the data processing alliance based on the shared processing mode and the independent processing mode includes: Based on the shared processing method, process the interactive data of the data parties under the data processing alliance; Processing the interactive data processed by the shared processing method according to the independent processing method; Based on the shared processing mode and the independent processing mode, the interactive data of the data parties under the data processing alliance are screened out; Obtaining expenditure details and income details of the interactive data from the data parties under the data processing alliance; The characteristics of the data subject include one or more of user payment method, business type and user rights; The method of clustering multiple data cubes according to the characteristics of the data cubes to obtain a data processing alliance includes: According to the characteristics of the data party, the data processing alliance is successfully matched, and the data processing alliance is obtained by clustering multiple data parties; adding the data party to the data processing alliance; According to the characteristics of the data party, the data processing alliance is not successfully matched, and the data processing alliance is obtained by clustering multiple data parties; A new data processing alliance is created according to the characteristics of the data cube, and the data cube is added to the newly created data processing alliance.

2. The data processing method according to claim 1, characterized in that: The shared processing method includes one or more of the following: number of accounts opened, product type, transaction account limit, transaction merchant and transaction channel.

3. The data processing method according to claim 1, characterized in that: The independent processing method includes one or more of the following: number of accounts opened, product type, transaction account limit, transaction merchant and transaction channel.

4. The data processing method according to claim 1, characterized in that: The priority of the shared processing mode is higher than the priority of the independent processing mode.

5. The data processing method according to claim 1, characterized in that: The shared user information includes one or more of the following: user activities, user financial shelves, and advertising-guided traffic.

6. The data processing method according to claim 1, characterized in that: The shared user rights include one or more of the following: coupons, discount activities, user points and user sign-in discounts.

7. The data processing method according to claim 1, characterized in that: The expenditure detail data includes one or more of the following information: payer, payment amount and payment time.

8. The data processing method according to claim 1, characterized in that: The income detail data includes one or more of the following information: income source, income amount and income time.

9. The data processing method according to claim 1, characterized in that: The parameters of the processed interactive data are displayed according to the data processing alliance and the data parties under the data processing alliance, including: According to the data processing alliance, display the parameters of the processed interactive data in the data processing alliance; According to the data party under the data processing alliance, the parameters of the processed interactive data in the data party under the data processing alliance are displayed.

10. The data processing method according to claim 1, characterized in that: The parameters of the interaction data include one or more of the following: recharge, consumption, income and withdrawal.

11. The data processing method according to claim 1, characterized in that: The method further comprises: A joint account of the data processing alliance is established, and the joint account is determined by the individual accounts of the data parties under the data processing alliance.

12. A data processing device, characterized in that: include: A clustering module is used to cluster multiple data parties to obtain a data processing alliance based on the characteristics of the data party; the characteristics of the data party include one or more of user payment methods, business types and user rights; and, based on the characteristics of the data party, successfully matched to the data processing alliance, the data processing alliance is obtained by clustering multiple data parties; adding the data party to the data processing alliance; and, based on the characteristics of the data party, failed to successfully match to the data processing alliance, the data processing alliance is obtained by clustering multiple data parties; creating a new data processing alliance according to the characteristics of the data party, and adding the data party to the newly created data processing alliance; A configuration module, used to configure the shared processing mode of the data processing alliance and the independent processing mode of each data party in the data processing alliance; A processing module, for processing the interactive data of the data parties under the data processing alliance based on the shared processing mode and the independent processing mode; the shared processing mode includes the shared user information of the data parties in the data processing alliance and the shared user rights and interests of the data parties in the data processing alliance; and, based on the shared processing mode, processing the interactive data processed by the shared processing mode; and, based on the shared processing mode and the independent processing mode, screening out the interactive data of the data parties under the data processing alliance; and obtaining the expenditure detail data and income detail data of the interactive data from the interactive data of the data parties under the data processing alliance; The display module is used to display the parameters of the processed interactive data according to the data processing alliance and the data parties under the data processing alliance.

13. An electronic device for data processing, characterized in that: include: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 11.

14. A computer readable medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 11 is implemented.

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