CN106355391B - Service processing method and device - Google Patents

Service processing method and device Download PDF

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CN106355391B
CN106355391B CN201510419219.XA CN201510419219A CN106355391B CN 106355391 B CN106355391 B CN 106355391B CN 201510419219 A CN201510419219 A CN 201510419219A CN 106355391 B CN106355391 B CN 106355391B
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service processing
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mode
data set
payment
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周豪杰
王丹丹
马海龙
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Advanced New Technologies Co Ltd
Advantageous New Technologies Co Ltd
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Alibaba Group Holding Ltd
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    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q20/00—Payment architectures, schemes or protocols
    • G06Q20/38—Payment protocols; Details thereof
    • G06Q20/40—Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check credit lines or negative lists
    • G06Q20/405—Establishing or using transaction specific rules

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Abstract

The application discloses a service processing method and a device, wherein the method comprises the following steps: receiving a service processing request of a user; determining historical service processing data sets matched with the service processing requests in each pre-divided historical service processing data set, wherein each pre-divided historical service processing data set is obtained by dividing each historical service processing data of the user in advance according to different scene dividing modes; and processing the service processing request according to the service processing mode sequence corresponding to the matched historical service processing data set. By the method, the server can recommend the service processing mode with the front sequence in the service processing mode sequencing to the user, the recommended service processing mode has high possibility to accord with the preference of the user, and the resource waste of the server can be reduced.

Description

Service processing method and device
Technical Field
The present application relates to the field of computer technologies, and in particular, to a method and an apparatus for processing a service.
Background
With the rapid development of internet technology and computer technology, more and more services can be performed on the internet. Specifically, the user may use the terminal to connect to the internet and perform service interaction with the server through the internet, thereby obtaining the service provided by the server.
In some service interaction links, for a service processing request provided by a user, there may be more than one service processing mode that the server may provide for processing the service request, but the user may not support each service processing mode, and therefore, the user may generally select one service processing mode from each service processing mode according to the support condition and preference degree of the user on each service processing mode, so that the server processes the service request provided by the user based on the service processing mode selected by the user.
In the prior art, in order to improve the efficiency of selecting a service processing manner by a user, a server may generally recommend the service processing manner that has been selected by the user most recently to the user, and in this case, the user may only need to directly determine the recommendation of the server.
However, in practical applications, for different scenes, a user may prefer different service processing manners, and when the scene changes frequently, the user may not want to select the service processing manner that has been selected by the user last time.
For example, for a payment service, the service processing request may be a payment request, and the service processing manner may be a payment channel. The payment channel may be a debit card payment, a credit card payment, a third party payment account, etc. Assuming that a user selects to pay with a credit card in the last payment service and the user may be on a third-party payment platform in the next payment service, the user may want to select a corresponding third-party payment account for payment, and in the prior art, the payment channel for payment with the credit card is still recommended to the user, which wastes resources of the server.
Disclosure of Invention
The embodiment of the application provides a service processing method and device, which are used for solving the problem that resources of a server are wasted in a mode of recommending a service processing mode to a user in the prior art.
The embodiment of the application provides a service processing method and device based on payment service, which are used for solving the problem that resources of a server are wasted in a mode of recommending a payment channel to a user in the prior art.
The embodiment of the application provides a method and a device for preprocessing historical service processing data, which are used for solving the problem that resources of a server are wasted in a mode of recommending a service processing mode to a user in the prior art.
The service processing method provided by the embodiment of the application comprises the following steps:
receiving a service processing request of a user;
determining historical service processing data sets matched with the service processing requests in each pre-divided historical service processing data set, wherein each pre-divided historical service processing data set is obtained by dividing each historical service processing data of the user in advance according to different scene dividing modes;
and processing the service processing request according to the service processing mode sequence corresponding to the matched historical service processing data set.
The service processing method based on the payment service provided by the embodiment of the application comprises the following steps:
receiving a payment request of a user;
determining historical payment data sets matched with the payment in each pre-divided historical payment data set, wherein each pre-divided historical payment data set is obtained by dividing each historical payment data of the user in advance according to different scene division modes;
recommending at least one payment channel to the user according to the payment channel sequence corresponding to the matched historical payment data set, and processing the payment request based on the payment channel selected by the user from the at least one payment channel.
The method for preprocessing the historical service processing data provided by the embodiment of the application comprises the following steps:
acquiring historical service processing data of a user;
according to different scene division modes, different historical service processing data sets are obtained by dividing the historical service processing data;
respectively determining the business processing mode sequence corresponding to each historical business processing data set;
and determining credibility representation values of the scene division modes according to the determined service processing mode sequences.
An embodiment of the present application provides a service processing apparatus, including:
the receiving module is used for receiving a service processing request of a user;
the determining module is used for determining a historical service processing data set matched with the service processing request in each pre-divided historical service processing data set, wherein each pre-divided historical service processing data set is obtained by dividing each historical service processing data of the user in advance according to different scene dividing modes;
and the processing module is used for sequencing according to the service processing modes corresponding to the matched historical service processing data set and processing the service processing request.
The service processing device based on payment service provided by the embodiment of the application comprises:
the receiving module is used for receiving a payment request of a user;
the determining module is used for determining historical payment data sets matched with the payment in each pre-divided historical payment data set, wherein each pre-divided historical payment data set is obtained by dividing each historical payment data set of the user in advance according to different scene dividing modes;
and the processing module is used for recommending at least one payment channel to the user according to the payment channel sequence corresponding to the matched historical payment data set, and processing the payment request based on the payment channel selected by the user from the at least one payment channel.
The device for preprocessing historical service processing data provided by the embodiment of the application comprises:
the acquisition module is used for acquiring each historical service processing data of the user;
the dividing module is used for dividing the historical service processing data according to different scene dividing modes to obtain different historical service processing data sets;
the first determining module is used for respectively determining the business processing mode sequence corresponding to each historical business processing data set;
and the second determining module is used for determining the credibility representation value of each scene division mode according to the determined service processing mode sequencing.
In the embodiment of the application, through at least one of the above technical solutions, the scenes to which the historical service processing data divided based on different scene division modes belong may be different, wherein, the scene of the set matched with the service processing request has higher matching degree with the scene of the service processing request, therefore, the service processing modes corresponding to the matched set are sorted, the service processing mode with the top sequence in the service processing mode sequence is also likely to be the service processing mode with higher preference degree for the service processing request, therefore, the server can recommend the service processing modes with the front sequence to the user, compared with the recommendation mode in the prior art, because the recommendation mode takes the scene to which the service processing request belongs into consideration, the recommendation accuracy is higher, and the resource waste of the server is reduced.
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The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
fig. 1 is a service processing procedure provided in an embodiment of the present application;
fig. 2 is a service processing procedure based on payment service according to an embodiment of the present application;
fig. 3 is a preprocessing process of historical service processing data according to an embodiment of the present disclosure;
fig. 4 is a service model that can implement the preprocessing process for the historical service processing data in practical applications according to the embodiment of the present application;
fig. 5 is a method for deciding whether to execute the service processing procedure in practical application according to the embodiment of the present application;
fig. 6 is a schematic structural diagram of a service processing apparatus according to an embodiment of the present application;
fig. 7 is a schematic structural diagram of a service processing device based on payment service according to an embodiment of the present application;
fig. 8 is a schematic structural diagram of a preprocessing device for processing historical service processing data according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be described in detail and completely with reference to the following specific embodiments of the present application and the accompanying drawings. It should be apparent that the described embodiments are only some of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
In the embodiment of the present application, in order to solve the problem provided in the background art, after receiving a service processing request of a user, a server may infer a service processing manner preferred by the user in different scenarios according to each historical service processing data of the user, and preferentially recommend the service processing manner to the user, so that efficiency of selecting the service processing manner by the user may be improved, and resources of the server may be saved. The details will be described below.
In the embodiment of the present application, the specific information of the scenario may be different for different services.
For example, for a payment service, the service processing request may be a payment request, and the service processing manner may be a payment channel. In this case, the specific information of the scene may be: the amount of payment, the type of goods purchased, whether the payment was retried after a payment failure, etc. Assume that the server provides 3 payment channels for the user, respectively: payment with a debit card, payment with a credit card, payment with a third party payment account number.
The user may select different payment channels according to the amount of the payment. For example, when the payment amount is not greater than 100 dollars, the user may prefer to pay with a debit card, and when the payment amount is greater than 100 dollars, the user may prefer to pay with a credit card; when a user purchases small goods such as food, payment by a third party payment account may be preferred, and when a user purchases large goods such as home appliances, payment by a credit card may be preferred; when the user fails to pay with a debit or credit card, it may be preferable to retry payment with a third party payment account, and so on.
Fig. 1 is a service processing process provided in an embodiment of the present application, which specifically includes the following steps:
s101: and receiving a service processing request of a user.
An execution main body of the service processing method provided by the embodiment of the application may be a server, and the server includes but is not limited to: medium and large computers, computer clusters, personal computers, and the like. The described execution body does not constitute a limitation of the present application.
S102: and determining historical service processing data sets matched with the service processing requests in each pre-divided historical service processing data set, wherein each pre-divided historical service processing data set is obtained by dividing each historical service processing data of the user in advance according to different scene division modes.
For convenience of description, the "historical business process data set" may be referred to as a "set" hereinafter.
In the embodiment of the application, different sets can be obtained by dividing the historical service processing data of the user in advance according to different scene division modes. Each of the historical service processing data may be represented by a record in the database, where the record may include a plurality of Key-Value pairs, and the Key-Value pairs may record: user number, service number, generation time, service processing mode, etc. The "bar" may be described as a unit of the historical traffic processing data.
The scene division manner may reflect: and the scene to which each historical service processing data contained in each set corresponding to the scene division mode belongs. Therefore, the division set may also be considered as being in the division of scenes, and the more contents included in the scene division manner, the more sets may be generated, and accordingly, the more scenes may be reflected (at the same time, the range of each scene may be smaller).
In this embodiment of the present application, the scene division manner may specifically include: and dividing the historical service processing data according to at least one of the number of times of retry processing, the processing type and the size of the service parameter.
In step S102, "determining the historical transaction data set matching the transaction request" may specifically include two sets of actions, as follows:
first, a scene division manner is determined for a user from preset scene division manners, so that the degree of correspondence between each divided scene and each actual scene of the user is higher according to the scene division manner, and thus, the scene division manner can be considered to be more suitable for the user.
Still taking the payment service as an example, assume that the user prefers to pay with a debit card when the payment amount is not more than 100 dollars, and prefers to pay with a credit card when the payment amount is more than 100 dollars. In this way, the "differentiated payment amount size" and the "differentiated point using 100 yuan as the differentiated payment amount size" can be used as a scene division mode, and it can be seen that there are two value combinations (one is that the payment amount is not greater than 100 yuan, and the other is that the payment amount is greater than 100 yuan) in the scene division mode, and a set can be divided according to each value combination, where the payment amount contained in each historical transaction data in one set (referred to as set 1) is not greater than 100 yuan (belonging to the scene where the payment amount is not greater than 100 yuan), and the payment amount contained in each historical transaction data in the other set (referred to as set 2) is greater than 100 yuan (belonging to the scene where the payment amount is greater than 100 yuan). It can be seen that the scene division manner in this example is suitable for the user.
The two sets divided according to the value combinations may be referred to as: the scene division mode corresponds to a set.
In this example, since the preference of the user is assumed, an applicable scene division manner can be determined for the user relatively accurately. However, in practical applications, unless the user sets his or her preference in advance on the server, the server may not directly determine the applicable scene division manner for the user, and therefore, the server may preset different scene division manners, and further determine one scene division manner from the scene division manners according to the scene division manners and the historical service processing data of the user (a specific method will be described later), as the scene division manner that is inferred by the server and is applicable to the user.
Secondly, after determining the scene division manner, the server may further determine a set matching the service processing request of the user in each set corresponding to the scene division manner. It should be noted that the set of matches may refer to: in each set corresponding to the scene division manner, at least one set, to which the scene to which the service processing request of the user belongs, is highly matched (may be the highest) with the scene to which the service processing request of the user belongs.
Still continuing with the above example, assuming that the payment amount contained in the user's payment request is 500 dollars, the payment request belongs to a scenario in which the payment amount is greater than 100 dollars, and does not belong to a scenario in which the payment amount is not greater than 100 dollars, and therefore, for set 1 and set 2, the server may determine set 2 as the set matching the payment request.
It should be noted that two sets can be divided according to the scene division manner in the above example. In practical application, the scene division mode may further include more contents, and accordingly, a larger number of sets may be divided according to the scene division mode.
S103: and processing the service processing request according to the service processing mode sequence corresponding to the matched historical service processing data set.
In this embodiment of the present application, for each set, a service processing manner ranking corresponding to the set may be determined in advance. The service processing mode ordering will be explained below.
The set may include a plurality of pieces of historical service processing data, for any one of the historical service processing data, the historical service processing data may correspond to a historical service processing request that the user has sent, the server may generate the historical service processing data after processing the historical service request based on a certain service processing mode selected by the user, and the historical service processing data may include the service processing mode.
In the service processing mode sequencing, the sequence of each service processing mode contained in the corresponding set can be recorded; the order of the service processing modes may be determined according to the scores of the service processing modes, for example, the service processing mode with the higher score is earlier in the order of the service processing mode.
The scoring of the business process patterns is used to reflect: based on the set, the degree of preference of the user for each service processing manner can be estimated. The higher the score of a business process, the more preferred the business process may be by the user.
In this embodiment of the application, the service processing request may be processed according to the service processing mode with the top order (or the top order) in the service processing mode sorting in step S103. In practical applications, the processing may be recommending the service processing mode with the top order to the user (in this application, the processing mainly refers to this type), or directly adopting the service processing mode with the top order to process the service processing request, and so on.
Through the above method, according to the description in the step S102, since the scene to which the set matching the service processing request belongs has a higher matching degree (may also be the highest) with the scene to which the service processing request belongs, for the service processing manner ranking corresponding to the matched set, the service processing manner with the top order in the service processing manner ranking is also likely to be the service processing manner with the higher preference degree for the service processing request by the user, so that the server can recommend the service processing manner with the top order to the user.
The description continues with the service processing mode sequencing.
In this embodiment of the present application, the service processing manner ordering corresponding to the historical service processing data set may be determined according to the following method: determining the grade of the service processing mode according to the generation time of each historical service processing data in the historical service processing data set and the service processing mode contained in each historical service processing data; and determining the service processing mode sequence corresponding to the historical service processing data set according to the scores of the service processing modes.
The service processing mode ordering corresponding to the historical service processing data set may be predetermined by the server, or may be determined by the server after receiving a service processing request from a user.
Further, for the convenience of understanding, a specific formula is used to describe a method for determining the score of the business processing mode.
Today (i.e., the current day) is denoted as tth day, yesterday is denoted as tth-1 day, and so on, and a day N days before today (e.g., in practical applications, N may generally take on the value of 180 or 90, etc.) is denoted as tth-N day.
Assuming that a historical service processing data set is obtained by dividing according to the scene division mode i, the historical service processing data set is marked as Di. Suppose DiThe method comprises the historical service processing data of the user j from the T-N day to the T-1 day, DiThe medium includes C service processing modes (corresponding to D)iThe service processing modes of the historical service processing data included and selected by the user from the T-N day to the T-1 day).
For the service processing mode k in the C service processing modes, in DiThe historical business processing data of the user j on the t day contained in the data list comprises ltThe historical service processing data comprises a service processing mode k, wherein T, T and N are integers, and T is more than or equal to T-180 and less than or equal to T-1. Then, for user j, the following formula (called formula 1) can be used to determine that the service processing mode k is at D on the T-th dayiScore in (1)
Figure BDA0000760972450000107
Figure BDA0000760972450000101
Wherein,
Figure BDA0000760972450000102
actually, the service processing mode k is in DiThe sum of the weighted numbers of occurrences of (a), wherein,
Figure BDA0000760972450000103
the weights used for weighting (which may also be referred to as forgetting factors) have the meaning: for the times of selecting the service processing mode k by the user on the T day, if the T day is farther away from the T day, the times of selecting the service processing mode k by the user on the T day is scored
Figure BDA0000760972450000104
The effect of (c) is smaller.
It should be noted that, in the following description,
Figure BDA0000760972450000105
the forgetting factor is only one of the expressions, and the forgetting factor can have other expressions. For example, the forgetting factor can also be expressed as
Figure BDA0000760972450000106
And the like; wherein a is a positive integer. In practical applications, the expression form of the forgetting factor conforming to the meaning of the forgetting factor can be adopted.
In this embodiment of the application, the server may determine a scene division manner from the scene division manners based on the credit characteristic value of each scene division manner (the specific implementation method of the determination is described later), and the determined scene division manner is used as the scene division manner that is inferred by the server and is suitable for the user. The following is a detailed description.
The credibility characteristic value of the scene division mode is used for representing the applicability degree of the scene division mode to the user, the larger the credibility characteristic value of the scene division mode is, the higher the applicability degree of the scene division mode to the user is, and correspondingly, the service processing mode determined and recommended to the user is more likely to accord with the preference of the user according to each set divided according to the scene division mode.
According to the above description, for step S102, determining the historical service processing data set matching the service processing request may specifically include: according to the credibility representation value of each scene division mode, determining a historical service processing data set matched with the service processing request from each historical service processing data set corresponding to the scene division mode with the largest credibility representation value; the credibility representation value of the scene division mode is determined according to each historical service processing data set corresponding to the scene division mode.
Further, the credibility characteristic value of the scene division mode can be determined according to the following method: acquiring a stored historical service processing request of the user and a processing result of the historical service processing request, and taking the processing result of the historical service processing request as a standard result; processing the historical service processing request according to the service processing mode sequence corresponding to each historical service processing data set divided by the scene division mode to obtain a processing result as a test result; comparing the standard result with the test result to obtain a comparison result; and determining the credibility representation value of the scene division mode according to the comparison result.
The credibility representation value of the scene division mode may be predetermined by the server, or may be determined by the server after receiving a service processing request from a user.
For the convenience of understanding, a method for determining the credibility representation value of the scene division mode is also described by using a specific formula. Here, the above description is continued with the respective assumption conditions used when describing the method of determining the score of the traffic processing method.
For user j, the following can be adoptedThe formula of the surface (called formula 2) determines the credibility representation value of the scene division mode i on the Tth day
Figure BDA0000760972450000111
Figure BDA0000760972450000112
Equation 2 is explained below. In practical applications, a user may send a service processing request to a server every day, and therefore, since historical service processing data of the user may be increased day by day, correspondingly, each piece of historical service processing data of the user acquired by the server is also increased, the server may divide sets and determine a service processing manner corresponding to each set according to each piece of historical service processing data of the user acquired at the current time (for example, once a day) periodically (for example). For convenience of description, the service processing mode sequence determined on the t-th day may be simply referred to as: and (5) sequencing the service processing modes on the t day.
For the formula 2, T-1 is taken as an example to explain
Figure BDA0000760972450000113
The meaning of (a).
And acquiring the stored historical service processing request of the user on the T-1 th day and the processing result of the historical service processing request (based on the processing result, the service processing mode selected by the user for the historical service processing request of the T-1 th day can be determined), and taking the processing result of the historical service processing request as a standard result.
And recommending the service processing mode with the highest grade in the T-2 day service processing mode sequencing to the user as a test result aiming at the historical service processing request of the T-1 day according to the T-2 day service processing mode sequencing.
By comparing each standard result (the service processing mode actually selected by the user) with the corresponding test result (the service processing mode recommended to the user based on the method of the present application), a comparison result can be obtained, which is obtainedThe number of times the standard result is the same as the corresponding test result (i.e., the recommendation was successful) may be counted as
Figure BDA0000760972450000121
That is, the above-mentioned
Figure BDA0000760972450000122
T in (1) is assigned as T-1.
The above T ═ T-1 is taken as an example, and the description is given
Figure BDA0000760972450000123
Analogously, for T in the value range [ T-N, T-1 ]]The corresponding value can be calculated
Figure BDA0000760972450000124
And will not be described in detail herein.
In addition, it can be seen that similar to equation 1, a forgetting factor is also added to equation 2
Figure BDA0000760972450000125
The meaning of the forgetting factor is similar to that of the forgetting factor in equation 1.
In this embodiment of the application, for step S103, processing the service processing request according to the service processing mode sequence corresponding to the matched historical service processing data set may specifically include: in each service processing mode, selecting at least one service processing mode according to the sequence from front to back of the service processing mode sequence, and recommending the service processing mode to the user; and processing the service processing request based on the service processing mode selected by the user from the recommended service processing modes.
In practical application, the service processing method provided by the application can be applied to various services. For example, when applied to a payment service, the service processing request includes a payment request, the historical service processing data includes historical payment data, and the service processing manner includes a payment channel; the scene division mode specifically includes: a mode of dividing the historical service processing data according to whether the payment is a retry payment after the payment fails, whether the payment is at least one of a specific payment type and a payment amount; wherein the particular payment type comprises a credit card payment type.
Based on the same idea, the service processing method provided by the embodiment of the present application further provides a service processing method based on a payment service.
Fig. 2 is a payment process provided in the embodiment of the present application, which specifically includes the following steps:
s201: a payment request of a user is received.
S202: and determining historical payment data sets matched with the payment in each pre-divided historical payment data set, wherein each pre-divided historical payment data set is obtained by dividing each historical payment data of the user in advance according to different scene division modes.
S203: recommending at least one payment channel to the user according to the payment channel sequence corresponding to the matched historical payment data set, and processing the payment request based on the payment channel selected by the user from the at least one payment channel.
The execution main body of the payment method provided by the embodiment of the application can be a server.
By the method, the server can recommend the payment channel with the top sequence in the payment channel sequence to the user, the recommended payment channel has high possibility to accord with the preference of the user, and the resource waste of the server can be reduced.
Based on the same idea, the service processing method and the service processing method based on the payment service provided by the embodiment of the present application further provide a preprocessing method for historical service processing data, and through the preprocessing method, the server can determine what is needed in the service processing method: and sequencing business processing modes corresponding to the historical business processing data set, and credibility representation values of the scene division modes. It should be noted that the preprocessing method may be performed in advance before the business processing method can be executed, or may be performed during the business processing method.
Fig. 3 is a preprocessing process for historical service processing data according to an embodiment of the present application, which specifically includes the following steps:
s301: and acquiring each historical service processing data of the user.
S302: and according to different scene division modes, obtaining different historical service processing data sets by dividing the historical service processing data.
S303: and respectively determining the business processing mode sequence corresponding to each historical business processing data set.
S304: and determining credibility representation values of the scene division modes according to the determined service processing mode sequences.
The execution main body of the preprocessing method for the historical service processing data provided by the embodiment of the application can be a server.
By the method, the server can acquire data (service processing mode sequencing, credibility representation values of various scene division modes and the like) required in the service processing process in the figure 1, and further can solve the problems in the background technology based on the service processing process.
The specific implementation of the steps in fig. 3 has already been explained in detail in the description of the service processing procedure in fig. 1, and therefore, only a brief explanation is made here.
In this embodiment of the present application, for the step S303, the service processing manner ordering corresponding to the historical service processing data set may be determined according to the following method: determining the grade of each service processing mode according to the generation time of each historical service processing data in the historical service processing data set and each service processing mode contained in each historical service processing data; and determining the service processing mode sequence corresponding to the historical service processing data set according to the scores of the service processing modes.
In this embodiment of the application, for the step S304, the credibility representation value of the scene division manner may be determined according to the following method: acquiring a stored historical service processing request of the user and a processing result of the historical service processing request, and taking the processing result of the historical service processing request as a standard result; processing the historical service processing request according to the service processing mode sequence corresponding to each historical service processing data set divided by the scene division mode to obtain a processing result as a test result; comparing the standard result with the test result to obtain a comparison result; and determining the credibility representation value of the scene division mode according to the comparison result.
In practical application, the corresponding business model can be adopted to realize the preprocessing method for the historical business processing data provided by the application. In the following, a service model that can implement the preprocessing method in practical applications is still described by taking a payment service as an example. In this case, the service processing request may be a payment request, the historical service processing data may be historical payment data, and the service processing manner may be a payment channel.
Fig. 4 shows the modules (indicated by rectangular boxes), the connection relationship between the modules (indicated by arrow segments), and the data that can be output by the modules (indicated by rounded boxes) included in the business model.
It can be seen that fig. 4 includes 1 to N partitioning modules, 1 to N payment channel sorting modules, a scene partitioning mode credibility representation value determining module, and a scene partitioning mode optimizing module.
Each partitioning module may be for: according to one scenario division manner, at least one historical payment data set is divided from the historical payment data of the user (for convenience of description, in fig. 3, only one historical payment data set is shown and other historical payment data sets are not shown in each scenario division manner).
Each payment channel ranking module may be operable to: and determining the payment channel ordering of the corresponding historical payment data set.
The scene partitioning mode credibility representation value determining module may be configured to: and determining credibility characteristic values of various scene division modes.
The scene division mode optimizing module may be configured to: and determining a preferred scene division mode according to the credibility characteristic values of various scene division modes, wherein the preferred scene division mode is more suitable for users compared with other scene division modes. Generally, the scene division mode optimization module may use the scene division mode with the largest credibility representation value as the optimal scene division mode.
After determining the preferred scene division mode, the scene division mode preference module may acquire the payment channel ranking corresponding to the preferred scene division mode, and is used to recommend the payment channel to the user.
In practical applications, the business model in fig. 4 may be trained every day, so as to possibly improve the accuracy of recommending a payment channel for a user.
To further help understanding the scene division manner, the following examples illustrate the scene division manner that may be used in practical applications, as shown in table 1 below:
Figure BDA0000760972450000151
Figure BDA0000760972450000161
TABLE 1
It can be seen that a total of 3 scene partitioning modes are shown in table 1.
The "secondary payment data" in table 1 may refer to: for a certain transaction, the user may have failed payment for the first time, and then a second payment (i.e. a re-payment) may be made, and assuming that the second payment is successful, the subsequently generated payment data may be referred to as: secondary payment data.
Then, for "whether only secondary payment data is used" in table 1, if so, each secondary payment data may be divided from each historical payment data of the user to form a historical payment data set, and if not, each historical payment data of the user may form a historical payment data set.
The "whether to distinguish the credit payment scenario" in table 1 may refer to: whether the collection is divided from each historical payment data of the user according to the payment channel contained in each historical payment data (whether the payment channel is paid by a credit card or not). If the payment channel is selected, the historical payment data paid by the credit card through the included payment channel can be used as one divided historical payment data set, and the historical payment data paid by the credit card through the included payment channel can be used as the other divided historical payment data set.
In practical applications, the credit payment scenario may be differentiated in another way. Specifically, the historical payment data may be divided based on the business scenario to which the historical payment data belongs, and if the user has paid by using a credit card in a certain business scenario, the historical payment data belonging to the business scenario may be divided into payment data sets in which the corresponding scenario is "pay by using a credit card", so that the processing speed of the server may be increased. The business scenario to which the historical payment data belongs can be generally determined according to a business number contained in the historical payment data.
The "whether to differentiate the size of the payment amount" in table 1 may mean: whether to divide the set from each historical payment data according to the payment amount contained in each historical payment data of the user. If the selection is yes, a discrimination point for discriminating the size of the payment amount may also be specified. For example, the division point designated in the first scene division manner in table 1 is 100 bins.
In practical applications, according to the 1 st division manner, 4 sets of historical payment data corresponding to the 1 st division manner may be divided; similarly, according to the 2 nd division, it may be possible to divide 2 sets of historical payment data corresponding to the 2 nd division; according to the nth division, it may be possible to divide 1 set of historical payment data corresponding to the 2 nd division.
In the embodiment of the application, if the server does not store the historical service processing data of the user, or if the server does not perform service interaction with the user for a long period of time, the accuracy rate of subsequently recommending the service processing mode may be reduced due to insufficient quantity of the historical service processing data. In this case, the method provided by the present application may not be adopted, but the service processing method may be randomly recommended to the user, so that the processing load of the server may be reduced. Further, the server may start to execute the method provided by the present application after acquiring the historical service processing data of the set number of users.
Fig. 5 is a method for deciding whether to execute the service processing procedure in practical application according to the embodiment of the present application. The execution subject of the decision method may be a server, and the decision method may specifically include the following steps:
s501: and acquiring historical service processing data of a user with the generation time within a set date range.
In practical applications, the set date range may be within about 1 month, or within about half a year, or within about one year, etc.
S502: and judging whether the quantity of the acquired historical service processing data is not less than a preset threshold value, if so, executing step S503, otherwise, executing step S504.
S503: and recommending a service processing mode to the user by executing the service processing process provided by the application.
S504: and recommending the service processing mode to the user by adopting other recommending methods.
Based on the same idea, the service processing method based on the payment service, and the preprocessing method for processing data of the historical service provided in the embodiments of the present application also provide a corresponding service processing device, a corresponding service processing device based on the payment service, and a corresponding preprocessing device for processing data of the historical service, as shown in fig. 6, 7, and 8.
Fig. 6 is a schematic structural diagram of a service processing apparatus provided in an embodiment of the present application, which specifically includes:
a receiving module 601, configured to receive a service processing request of a user;
a determining module 602, configured to determine, in pre-divided historical service processing data sets, a historical service processing data set matched with the service processing request, where the pre-divided historical service processing data sets are obtained by dividing, according to different scene division manners, the historical service processing data of the user in advance;
and the processing module 603 is configured to process the service processing request according to the service processing mode sequence corresponding to the matched historical service processing data set.
The determining module 602 is specifically configured to: according to the credibility representation value of each scene division mode, determining a historical service processing data set matched with the service processing request from each historical service processing data set corresponding to the scene division mode with the largest credibility representation value; the credibility representation value of the scene division mode is determined according to each historical service processing data set corresponding to the scene division mode.
The determining module 602 is further configured to determine a credibility characteristic value of the scene partitioning manner according to the following method: acquiring a stored historical service processing request of the user and a processing result of the historical service processing request, and taking the processing result of the historical service processing request as a standard result; processing the historical service processing request according to the service processing mode sequence corresponding to each historical service processing data set divided by the scene division mode to obtain a processing result as a test result; comparing the standard result with the test result to obtain a comparison result; and determining the credibility representation value of the scene division mode according to the comparison result.
The determining module 602 is further configured to determine a service processing manner ordering corresponding to the historical service processing data set according to the following method: determining the grade of each service processing mode according to the generation time of each historical service processing data in the historical service processing data set and each service processing mode contained in each historical service processing data; and determining the service processing mode sequence corresponding to the historical service processing data set according to the scores of the service processing modes.
The processing module 603 is specifically configured to: in each service processing mode, selecting at least one service processing mode according to the sequence from front to back of the service processing mode sequence, and recommending the service processing mode to the user; and processing the service processing request based on the service processing mode selected by the user from the recommended service processing modes.
The scene division mode specifically includes: and dividing the historical service processing data according to at least one of the number of times of retry processing, the processing type and the size of the service parameter.
The apparatus shown in fig. 6 may be located on a server.
Fig. 7 is a schematic structural diagram of a service processing apparatus based on payment service according to an embodiment of the present application, which specifically includes:
a receiving module 701, configured to receive a payment request of a user;
a determining module 702, configured to determine, in each pre-divided historical payment data set, a historical payment data set that matches the payment, where each pre-divided historical payment data set is obtained by dividing, according to different scene division manners, each historical payment data set of the user in advance;
the processing module 703 is configured to recommend at least one payment channel to the user according to the payment channel ranking corresponding to the matched historical payment data set, and process the payment request based on a payment channel selected by the user from the at least one payment channel.
The apparatus shown in fig. 7 may be located on a server.
Fig. 8 is a schematic structural diagram of a preprocessing device for processing historical service data according to an embodiment of the present application, which specifically includes:
an obtaining module 801, configured to obtain historical service processing data of a user;
a dividing module 802, configured to divide the historical service processing data into different historical service processing data sets according to different scene division manners;
a first determining module 803, configured to respectively determine a service processing manner ranking corresponding to each historical service processing data set;
a second determining module 804, configured to determine a credibility representation value of each scene partitioning manner according to the determined ranking of each service processing manner.
The first determining module 803 is specifically configured to determine the service processing manner ordering corresponding to the historical service processing data set according to the following method: determining the grade of each service processing mode according to the generation time of each historical service processing data in the historical service processing data set and each service processing mode contained in each historical service processing data; and determining the service processing mode sequence corresponding to the historical service processing data set according to the scores of the service processing modes.
The second determining module 804 is specifically configured to determine the credibility characteristic value of the scene partitioning manner according to the following method: acquiring a stored historical service processing request of the user and a processing result of the historical service processing request, and taking the processing result of the historical service processing request as a standard result; processing the historical service processing request according to the service processing mode sequence corresponding to each historical service processing data set divided by the scene division mode to obtain a processing result as a test result; comparing the standard result with the test result to obtain a comparison result; and determining the credibility representation value of the scene division mode according to the comparison result.
The apparatus shown in fig. 8 may be located on a server.
The embodiment of the application provides a service processing method and a device, wherein the method comprises the following steps: receiving a service processing request of a user; determining historical service processing data sets matched with the service processing requests in each pre-divided historical service processing data set, wherein each pre-divided historical service processing data set is obtained by dividing each historical service processing data of the user in advance according to different scene dividing modes; and processing the service processing request according to the service processing mode sequence corresponding to the matched historical service processing data set. By the method, the scenes to which the historical service processing data belong, which are divided based on different scene division modes, can be different, wherein the scene to which the set matched with the service processing request belongs is higher in matching degree with the scene to which the service processing request belongs, so that the service processing modes corresponding to the matched set are sorted, and the service processing modes with the front sequence in the service processing mode sorting are probably also the service processing modes with the higher preference degree aiming at the service processing request by the user, so that the server can recommend the service processing modes with the front sequence to the user.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims (18)

1. A method for processing a service, comprising:
receiving a service processing request of a user;
determining a historical service processing data set matched with the service processing request according to the credibility representation value of each scene division mode in each pre-divided historical service processing data set, wherein each pre-divided historical service processing data set is obtained by dividing each historical service processing data of the user according to different scene division modes in advance, the historical service processing data set matched with the service processing request is determined by a server after the scene division mode is determined, and the scene division mode specifically comprises the following steps: a mode of dividing the historical service processing data according to at least one of the number of times of retry processing, the processing type and the size of the service parameter;
and processing the service processing request according to the service processing mode sequence corresponding to the matched historical service processing data set.
2. The method of claim 1, wherein determining a set of historical business process data that matches the business process request comprises:
according to the credibility representation value of each scene division mode, determining a historical service processing data set matched with the service processing request from each historical service processing data set corresponding to the scene division mode with the largest credibility representation value;
the credibility representation value of the scene division mode is determined according to each historical service processing data set corresponding to the scene division mode.
3. The method of claim 2, wherein the confidence measure of the scene partitioning is determined as follows:
acquiring a stored historical service processing request of the user and a processing result of the historical service processing request, and taking the processing result of the historical service processing request as a standard result;
processing the historical service processing request according to the service processing mode sequence corresponding to each historical service processing data set divided by the scene division mode to obtain a processing result as a test result;
comparing the standard result with the test result to obtain a comparison result;
and determining the credibility representation value of the scene division mode according to the comparison result.
4. The method of claim 1, wherein the service processing mode ordering corresponding to the historical service processing data set is determined according to the following method:
determining the grade of each service processing mode according to the generation time of each historical service processing data in the historical service processing data set and each service processing mode contained in each historical service processing data;
and determining the service processing mode sequence corresponding to the historical service processing data set according to the scores of the service processing modes.
5. The method according to claim 1, wherein processing the service processing request according to the service processing manner ranking corresponding to the matched historical service processing data set specifically comprises:
in each service processing mode, selecting at least one service processing mode according to the sequence from front to back of the service processing mode sequence, and recommending the service processing mode to the user;
and processing the service processing request based on the service processing mode selected by the user from the recommended service processing modes.
6. A service processing method based on payment service is characterized by comprising the following steps:
receiving a payment request of a user;
determining a historical payment data set matched with payment according to the credibility characteristic value of each scene division mode in each pre-divided historical payment data set, wherein each pre-divided historical payment data set is obtained by dividing each historical payment data set of the user according to different scene division modes in advance, the determining of the historical payment data set matched with the payment is that a server determines a set matched with the payment request of the user in each set corresponding to the scene division modes after determining the scene division modes, and the scene division modes specifically comprise: a mode of dividing the historical service processing data according to at least one of the number of times of retry processing, the processing type and the size of the service parameter;
recommending at least one payment channel to the user according to the payment channel sequence corresponding to the matched historical payment data set, and processing the payment request based on the payment channel selected by the user from the at least one payment channel.
7. A preprocessing method for historical service processing data is characterized by comprising the following steps:
acquiring historical service processing data of a user;
according to different scene division modes, different historical service processing data sets are obtained by dividing the historical service processing data, and the scene division mode specifically comprises the following steps: a mode of dividing the historical service processing data according to at least one of the number of times of retry processing, the processing type and the size of the service parameter;
respectively determining the business processing mode sequence corresponding to each historical business processing data set;
and determining credibility representation values of the scene division modes according to the determined service processing mode sequences.
8. The method of claim 7, wherein the service processing mode ordering corresponding to the historical service processing data set is determined according to the following method:
determining the grade of each service processing mode according to the generation time of each historical service processing data in the historical service processing data set and each service processing mode contained in each historical service processing data;
and determining the service processing mode sequence corresponding to the historical service processing data set according to the scores of the service processing modes.
9. The method of claim 7, wherein the confidence measure of the scene partitioning is determined as follows:
acquiring a stored historical service processing request of the user and a processing result of the historical service processing request, and taking the processing result of the historical service processing request as a standard result;
processing the historical service processing request according to the service processing mode sequence corresponding to each historical service processing data set divided by the scene division mode to obtain a processing result as a test result;
comparing the standard result with the test result to obtain a comparison result;
and determining the credibility representation value of the scene division mode according to the comparison result.
10. A traffic processing apparatus, comprising:
the receiving module is used for receiving a service processing request of a user;
a determining module, configured to determine, in each pre-divided historical service processing data set, a historical service processing data set matched with the service processing request according to a credibility characterizing value of each scene division manner, where each pre-divided historical service processing data set is obtained by dividing, in advance, each historical service processing data of the user according to different scene division manners, and the determining of the historical service processing data set matched with the service processing request is performed by a server, after determining the scene division manner, in each set corresponding to the scene division manner, a set matched with the service processing request of the user is determined, where the scene division manner specifically includes: a mode of dividing the historical service processing data according to at least one of the number of times of retry processing, the processing type and the size of the service parameter;
and the processing module is used for sequencing according to the service processing modes corresponding to the matched historical service processing data set and processing the service processing request.
11. The apparatus of claim 10, wherein the determination module is specifically configured to: according to the credibility representation value of each scene division mode, determining a historical service processing data set matched with the service processing request from each historical service processing data set corresponding to the scene division mode with the largest credibility representation value; the credibility representation value of the scene division mode is determined according to each historical service processing data set corresponding to the scene division mode.
12. The apparatus of claim 11, wherein the determining module is further configured to determine the credibility representation value of the scene partitioning manner according to the following method: acquiring a stored historical service processing request of the user and a processing result of the historical service processing request, and taking the processing result of the historical service processing request as a standard result; processing the historical service processing request according to the service processing mode sequence corresponding to each historical service processing data set divided by the scene division mode to obtain a processing result as a test result; comparing the standard result with the test result to obtain a comparison result; and determining the credibility representation value of the scene division mode according to the comparison result.
13. The apparatus of claim 10, wherein the determining module is further configured to determine the business process mode ranking corresponding to the historical business process data set according to the following method: determining the grade of each service processing mode according to the generation time of each historical service processing data in the historical service processing data set and each service processing mode contained in each historical service processing data; and determining the service processing mode sequence corresponding to the historical service processing data set according to the scores of the service processing modes.
14. The apparatus of claim 10, wherein the processing module is specifically configured to: in each service processing mode, selecting at least one service processing mode according to the sequence from front to back of the service processing mode sequence, and recommending the service processing mode to the user; and processing the service processing request based on the service processing mode selected by the user from the recommended service processing modes.
15. A transaction processing apparatus based on payment transaction, comprising:
the receiving module is used for receiving a payment request of a user;
a determining module, configured to determine, in each pre-divided historical payment data set, a historical payment data set that matches payment according to a credibility characterizing value of each scene division manner, where each pre-divided historical payment data set is obtained by dividing, in advance, each historical payment data of the user according to different scene division manners, and the determining of the historical service processing data set that matches the service processing request is performed by the server, and after the scene division manner is determined, a set that matches the service processing request of the user is determined in each set corresponding to the scene division manner, where the scene division manner specifically includes: a mode of dividing the historical service processing data according to at least one of the number of times of retry processing, the processing type and the size of the service parameter;
and the processing module is used for recommending at least one payment channel to the user according to the payment channel sequence corresponding to the matched historical payment data set, and processing the payment request based on the payment channel selected by the user from the at least one payment channel.
16. A preprocessing apparatus for processing data of a historical service, comprising:
the acquisition module is used for acquiring each historical service processing data of the user;
the dividing module is used for dividing the historical service processing data according to different scene dividing modes to obtain different historical service processing data sets, and the scene dividing modes specifically include: a mode of dividing the historical service processing data according to at least one of the number of times of retry processing, the processing type and the size of the service parameter;
the first determining module is used for respectively determining the business processing mode sequence corresponding to each historical business processing data set;
and the second determining module is used for determining the credibility representation value of each scene division mode according to the determined service processing mode sequencing.
17. The apparatus of claim 16, wherein the first determining module is specifically configured to determine the service processing manner ordering corresponding to the historical service processing data set according to the following method: determining the grade of each service processing mode according to the generation time of each historical service processing data in the historical service processing data set and each service processing mode contained in each historical service processing data; and determining the service processing mode sequence corresponding to the historical service processing data set according to the scores of the service processing modes.
18. The apparatus according to claim 16, wherein the second determining module is specifically configured to determine the credibility representation value of the scene partitioning manner according to the following method: acquiring a stored historical service processing request of the user and a processing result of the historical service processing request, and taking the processing result of the historical service processing request as a standard result; processing the historical service processing request according to the service processing mode sequence corresponding to each historical service processing data set divided by the scene division mode to obtain a processing result as a test result; comparing the standard result with the test result to obtain a comparison result; and determining the credibility representation value of the scene division mode according to the comparison result.
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Families Citing this family (20)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
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CN110175113B (en) * 2019-04-18 2023-07-14 创新先进技术有限公司 Service scene determination method and device
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US11282052B2 (en) 2019-05-06 2022-03-22 Advanced New Technologies Co., Ltd. Payment channel recommendation
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CN112801670B (en) * 2021-04-07 2021-07-23 支付宝(杭州)信息技术有限公司 Risk assessment method and device for payment operation
CN113052682A (en) * 2021-04-30 2021-06-29 中国银行股份有限公司 Account recommendation method and device
CN114038128B (en) * 2021-10-20 2023-06-27 浪潮金融信息技术有限公司 Energy-saving control method, system and medium applied to self-service terminal
CN115795342B (en) * 2022-11-15 2024-02-06 支付宝(杭州)信息技术有限公司 Method and device for classifying business scenes, storage medium and electronic equipment
CN117113929B (en) * 2023-09-08 2024-06-21 中电金信数字科技集团有限公司 Method and device for splitting field data, electronic equipment and storage medium

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8352323B2 (en) * 2007-11-30 2013-01-08 Blaze Mobile, Inc. Conducting an online payment transaction using an NFC enabled mobile communication device
CN102314649A (en) * 2011-07-27 2012-01-11 杭州斯凯网络科技有限公司 Payment method based on user and payment page
CN104182869A (en) * 2013-05-22 2014-12-03 深圳市腾讯计算机系统有限公司 Service processing method, device and system
CN104281940B (en) * 2013-07-12 2019-12-10 阿里巴巴集团控股有限公司 Method and apparatus for providing data processing mode list through communication network

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