CN114331405B - A method, device, system and storage medium for processing transaction bill data - Google Patents
A method, device, system and storage medium for processing transaction bill data Download PDFInfo
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Abstract
The application provides a processing method, a device, a system and a storage medium of transaction bill data, wherein the processing method, the device, the system and the storage medium are used for obtaining a plurality of transaction bill data, each transaction bill data comprises a user identifier and a transaction object identifier, each transaction bill data is subjected to association clustering processing according to the user identifier and the transaction object identifier of each transaction bill data to obtain at least one transaction bill data set, and each transaction bill data of each transaction bill data set is respectively subjected to and accounts-giving processing according to each transaction bill data set. By using the method provided by the application, the operator can bill the bill of the user in real time, and the bill billing efficiency and accuracy are improved.
Description
Technical Field
The present application relates to transaction bill processing technologies, and in particular, to a method, apparatus, system, and storage medium for processing transaction bill data.
Background
With the popularization of computer technology and mobile networks, people live more conveniently, and especially the efficiency of processing massive data is improved. Meanwhile, as the living standard of people is continuously improved, the demands of people on the network are gradually increased, so that the number of mobile network users is greatly increased, and how to treat the charge of each month of the users becomes a problem that operators pay attention to at present.
In the prior art, the operations typically divide users in groups, then calculate the lease fees and billing for each user in a group-wise calculation dimension, and the billing calculation should be after the lease fees.
However, the existing network operator processing method cannot realize concurrent processing of the lease fees and the bills, that is, bill processing can only be performed after lease fees are processed, and it can be understood that bills of the same user are composed of lease fees of a plurality of groups, which easily results in relatively centralized bill processing, so that bill processing efficiency and accuracy are not high.
Disclosure of Invention
The application provides a transaction bill data processing method, device, system and storage medium, which are used for solving the problems of low bill processing efficiency and insufficient accuracy caused by mechanical grouping adopted by operators.
In a first aspect, the present application provides a method for processing transaction bill data, including:
Acquiring a plurality of transaction bill data, wherein each transaction bill data comprises a user identifier and a transaction object identifier;
Performing association clustering processing on each transaction bill data according to the user identification and the transaction object identification of each transaction bill data to obtain at least one transaction bill data set;
And respectively carrying out and issuing account processing on each transaction bill data of each transaction bill data set according to each transaction bill data set.
In a second aspect, the present application provides a transaction bill data processing apparatus, including:
The system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring a plurality of transaction bill data, wherein each transaction bill data comprises a user identifier and a transaction object identifier;
The association module is used for carrying out association clustering processing on each transaction bill data according to the user identification and the transaction object identification of each transaction bill data to obtain at least one transaction bill data set;
and the billing module is used for respectively carrying out billing processing on the transaction bill data of each transaction bill data set according to each transaction bill data set.
In a third aspect, the application provides a transaction bill data processing system, which comprises a transaction bill data processing device and an operator database;
The transaction bill data processing device is configured to obtain transaction bill data uploaded by the operator database, and process the obtained transaction bill data according to the transaction bill data processing method as set forth in any one of the preceding claims.
In a fourth aspect, the present application provides an electronic device comprising:
At least one processor, and
A memory;
the memory stores computer-executable instructions;
the at least one processor executing computer-executable instructions stored in the memory causes the at least one processor to perform a method as claimed in any one of the preceding claims.
In a fifth aspect, the present application provides a computer readable storage medium having stored therein computer executable instructions which, when executed by a processor, implement a method as claimed in any preceding claim.
In a sixth aspect, a computer program product comprising a computer program which, when executed by a processor, implements the method of any of the preceding claims.
The application provides a processing method, a device, a system and a storage medium of transaction bill data, wherein the processing method, the device, the system and the storage medium are used for obtaining a plurality of transaction bill data, each transaction bill data comprises a user identifier and a transaction object identifier, each transaction bill data is subjected to association clustering processing according to the user identifier and the transaction object identifier of each transaction bill data to obtain at least one transaction bill data set, and each transaction bill data of each transaction bill data set is respectively subjected to and accounts-giving processing according to each transaction bill data set. By using the method provided by the application, the operator can bill the bill of the user in real time, and the bill billing efficiency and accuracy are improved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application.
FIG. 1 is a schematic diagram of a network architecture on which the present application is based;
FIG. 2 is a flow chart of a method for processing transaction bill data according to the present application;
FIG. 3 is a schematic diagram of a transaction bill data processing device according to the present application;
FIG. 4 is a schematic diagram of another transaction bill data processing device according to the present application;
FIG. 5 is a schematic diagram of a transaction bill data processing system according to the present application;
fig. 6 is a schematic diagram of a hardware structure of an electronic device provided by the present application.
Specific embodiments of the present application have been shown by way of the above drawings and will be described in more detail below. The drawings and the written description are not intended to limit the scope of the inventive concepts in any way, but rather to illustrate the inventive concepts to those skilled in the art by reference to the specific embodiments.
Detailed Description
Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples do not represent all implementations consistent with the application. Rather, they are merely examples of apparatus and methods consistent with aspects of the application as detailed in the accompanying claims.
Along with the popularization of computer technology and mobile networks, the method is greatly convenient for people to live in aspects, particularly, the method is convenient for people to work, and the complicated processing process is simplified. Meanwhile, as the living standard of people is continuously improved, the demands of people on the network are gradually increased, so that the number of mobile network users is greatly increased, and how to treat the charge of each month of the users becomes a hot spot of current research in the field.
In the prior art, the operations typically divide users in groups, then calculate the lease fees and billing for each user in a group-wise calculation dimension, and the billing calculation should be after the lease fees. It can be understood that the operator groups all users of a local area network or a local network, i.e. the user identification performs a modular processing on a certain calibration value and divides the same modular value into groups, then calculates the lease fees of each group, and calculates the total bill of each user after the lease fees of all groups are calculated.
However, in the method provided by the prior art, because the mobile network mechanically groups the users according to the user identification, the association relationship between the ordered sales items of the users, namely, the relationship between ordered package services is not considered, and because the bill of the users is composed of at least one package service, the bill is processed after the lease processing. Therefore, the operators cannot process the lease fees and the bills simultaneously, so that the operators can process the lease fees and the bills in a centralized manner, the processing efficiency is low, and meanwhile, the accuracy is not high enough.
Aiming at the technical problems, the application considers the association relationship between users, such as that the package A is ordered by the user 1, the package B is ordered by the user 1, and the association relationship between the package A and the package B can be established due to the user relationship, and also considers the association relationship between package services, such as that the user 2 orders the package C and the package D, and when the user 1 also orders the package D, the association relationship between the user 1 and the user 2 can be established due to the package D. The users are grouped according to the association relation between the users and the services, so that the situation that different services ordered by the same user are in cross-group is avoided, the concurrent processing of lease fees and bills can be realized, and the processing efficiency and accuracy are improved.
The application particularly provides a processing method of transaction bill data, which comprises the steps of obtaining a plurality of transaction bill data, wherein each transaction bill data comprises a user identifier and a transaction object identifier, carrying out association clustering processing on each transaction bill data according to the user identifier and the transaction object identifier of each transaction bill data to obtain at least one transaction bill data set, and carrying out and issuing account processing on each transaction bill data of each transaction bill data set aiming at each transaction bill data set. By using the method provided by the application, the operator can bill the bill of the user in real time, and the bill billing efficiency and accuracy are improved.
The following describes embodiments of the present application and how the technical solutions of the present application solve the above technical problems in detail with specific embodiments. The following embodiments may be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments. Embodiments of the present application will be described below with reference to the accompanying drawings.
Referring to fig. 1, fig. 1 is a schematic diagram of a network architecture according to the present application, and as shown in fig. 1, the network architecture includes a server 1 and a terminal 2.
The server 1 is specifically disposed in a mobile network management platform server cluster, and the processing device of the transaction bill data provided by the application can be integrated or installed therein.
The terminal 2 may be a hardware device such as a user mobile phone or a tablet, and may upload personal information to the server 1, and when the terminal 2 subscribes to a package service, the terminal may upload a subscription bill record to the server 1 for use by a processing device of transaction bill data, and complete the payment processing, and meanwhile, based on a network communication technology, the terminal 2 may receive payment information processed by the server 1.
Example 1
Fig. 2 is a flow chart of a method for processing transaction bill data according to the present application, as shown in fig. 2, the method includes:
Step 201, obtaining a plurality of transaction bill data, wherein each transaction bill data comprises a user identifier and a transaction object identifier;
step 202, performing association clustering processing on each transaction bill data according to the user identification and the transaction object identification of each transaction bill data to obtain at least one transaction bill data set;
Step 203, for each transaction bill data set, respectively performing and issuing account processing on each transaction bill data of each transaction bill data set.
It should be noted that, the execution main body of the transaction bill data processing method provided by the present application is the processing device, and as mentioned above, the processing device may be specifically installed or carried in the server 1.
The server 1 stores a large amount of transaction bill data, namely, the terminal uploads the self information and bill information of ordered packages to the server 1 and stores the data in an operator database in the server 1, and the processing device executes the transaction bill data according to the processing method of the transaction bill data after acquiring the data and completes the accounting processing.
Specifically, in step 201, the processing device obtains transaction billing data of each user from an operator database in a server. The transaction bill data comprises a user identifier and a transaction object identifier.
The transaction bill consists of user personal information and transaction information of a user ordering package, the user identifier refers to a unique identifier which can be used as a user identity, the transaction object identifier refers to a unique identifier for package service, and the two identifiers are preset with a certain mode and rule, such as marking a new user accessing the network and a new formulated package according to letter mode and sequence rule.
Further, the transaction bill data are all in the form of data forms, as shown in table 1, and table 1 shows an example of the obtained bill data.
As can be seen from the observation table 1, the transaction bill mainly comprises a transaction object identifier, a user identifier, a transaction object preference rule and a value-added fee, wherein the transaction object preference rule corresponds to the transaction object identifier one by one.
TABLE 1
The added value cost refers to the use cost beyond the specification of the transaction object.
After the processing device obtains the transaction bill data, step 202 is executed, in which each transaction bill data is subjected to association clustering processing according to the user identifier and the transaction object identifier in each transaction bill data, so as to obtain at least one transaction bill data set. The association clustering processing specifically refers to storing transaction bills with association relations together.
The processing device firstly carries out rough association clustering once according to the transaction object identification, namely, the transaction object identification is divided into the same group according to the transaction object identification, then carries out association clustering again according to the user identification, namely, on the basis of the association clustering according to the transaction object identification, then carries out association on transaction bills of different groups according to the user identification, namely, different groups can be combined through the user identification, and at least one transaction bill data set can be obtained through the two association clustering.
Further, the processing device firstly performs a first association clustering on transaction bill data with the same transaction object identification according to the transaction object identification in the transaction bill data, divides the obtained suggested bill data into groups according to the transaction object identification field so that the transaction bill data with the same transaction object identification are divided into the same candidate data set, and then performs a second association clustering on each candidate data set after the division based on the first association clustering according to the user identification field in the transaction bill data, namely, combines groups which have the same user identification and are positioned in different groups so that the candidate data sets with the same user identification are divided into the same transaction bill data set.
That is, step 202 includes performing a first associative clustering process on each transaction bill data based on the transaction object identifications in each transaction bill data such that transaction bill data having the same transaction object identification are partitioned into the same candidate data set.
And carrying out second association clustering processing on each candidate data set according to the user identification in each transaction bill data, so that the candidate data sets with the same user identification are divided into the same transaction bill data set.
As for the above example table 1, the processing device executes step 202 to perform first association clustering according to the transaction object identifiers in table 1, where the obtained results are shown in table 2.
TABLE 2
The group identifier in table 2 indicates a group number, that is, each group number obtained by performing a first association clustering according to the transaction object.
It can be understood that the transaction bill data corresponding to the transaction object identifier a is divided into the group with the group identifier 1 after the first association clustering, and the transaction bill data corresponding to the transaction object identifier B corresponds to the group identifier 2, the transaction bill data corresponding to the transaction object identifier C corresponds to the group identifier 3, and the transaction bill data corresponding to the transaction object identifier D corresponds to the group identifier 4.
In correspondence thereto, groups 1,2, 3, 4 are candidate data sets with the same transaction object identification, respectively.
Then, a second association clustering is performed on the user identification fields in the candidate set, and the obtained results are shown in table 3.
As shown in Table 3, since the group 1 and the group 3 have the same user identification 1, the group 1 and the group 3 are combined to obtain a new group identification as the group 1, and since the group 1 and the group 4 have the same user identification 4, the group 4 and the new group 1 are combined and the group identification is 1, and the user identifications in the group 2 are inconsistent with the user identifications in other groups, the group 2 still remains unchanged and is not combined with other groups. This results in the transaction bill data set.
TABLE 3 Table 3
In a practical scenario, since the user uses the package service, that is, the transaction object, there is a case that the package service does not need to additionally order other packages, which changes the transaction bill data, the association clustering process is performed on the transaction bill data in real time, and the transaction bill data set needs to be updated in real time.
After acquiring the transaction bill data set, the processing device executes step 203 to perform the posting process. I.e. each transaction bill data set is respectively subjected to and billed for each transaction bill data of each transaction bill data set.
Specifically, the processing device performs accounting processing on the transaction bill data in each transaction bill data set, namely, accounts are counted according to the user identification, and the ordered transaction objects, the transaction object preferential rules and the added value fees are subjected to accounting processing. The billing processing comprises a lease fee processing and a billing processing which are sequentially executed.
The lease fee processing refers to calculating the sum of the expense and the added expense of the transaction object, and the bill processing refers to performing preferential processing according to preferential rules after the lease fee is calculated.
If the transaction object A, B, C, D is checked out, the corresponding fees are assumed to be X1, X2, X3 and X4, and the corresponding preferential rules are that the transaction object is checked out by 8, the Y-limit is reduced by 5 yuan, the Y1-limit is reduced by 10 yuan, all the transaction objects are assumed to meet the preferential rule, and the result of checking out each transaction bill data is shown in table 4.
TABLE 4 Table 4
After the processing device finishes the account-out processing, the bill information is stored in the server, and then the bill is issued to the relevant terminal equipment based on the network communication technology.
Compared with the prior art, as shown in table 5, the transaction bill data is divided into groups according to the prior art, namely, the 2 is subjected to modulo processing according to the user grouping identification, and the bill data corresponding to the same remainder after modulo processing is divided into the same group.
The prior art divides the transaction bill into 2 groups, and because the association relation between users and ordered transaction objects is not considered, the lease fees of the transaction bill data in each group can only be calculated, and the bill processing is carried out, so that the problem that the bill processing is wrong due to inaccurate lease fee calculation can be avoided, the bill output efficiency is low, the condition that the bill output is inaccurate can be caused if the missing condition occurs, the transaction bill data in the group 0 in table 5 is observed, other transaction objects are not ordered, and the bill processing can be carried out after the lease fees are calculated by other groups.
Therefore, the method provided by the application can realize real-time account-out processing, and can also enable lease fees and bills to be processed concurrently, thereby improving the account-out efficiency and the account-out accuracy.
The application provides a processing method of transaction bill data, which comprises the steps of obtaining a plurality of transaction bill data, wherein each transaction bill data comprises a user identifier and a transaction object identifier, carrying out association clustering processing on each transaction bill data according to the user identifier and the transaction object identifier of each transaction bill data to obtain at least one transaction bill data set, and carrying out and issuing account processing on each transaction bill data of each transaction bill data set aiming at each transaction bill data set. By using the method provided by the application, the operator can bill the bill of the user in real time, and the bill billing efficiency and accuracy are improved.
TABLE 5
Example two
Fig. 3 is a schematic structural diagram of a transaction bill data processing device according to the present application, corresponding to the transaction bill data processing method of the present application. For convenience of explanation, only parts relevant to the present application are shown.
Referring to fig. 3, the transaction bill data processing apparatus 300 includes:
An obtaining module 10, configured to obtain a plurality of transaction bill data, where each transaction bill data includes a user identifier and a transaction object identifier;
The association module 20 is configured to perform association clustering processing on each transaction bill data according to the user identifier and the transaction object identifier of each transaction bill data, so as to obtain at least one transaction bill data set;
The billing module 30 is configured to perform and bill the transaction bill data of each transaction bill data set separately for each transaction bill data set.
The association module 20 is specifically configured to:
Performing first association clustering processing on each transaction bill data according to the transaction object identifiers in each transaction bill data so that the transaction bill data with the same transaction object identifier are divided into the same candidate data set;
And carrying out second association clustering processing on each candidate data set according to the user identification in each transaction bill data, so that the candidate data sets with the same user identification are divided into the same transaction bill data set.
The accounting module 30 is specifically configured to:
Concurrently executing a billing process on transaction bill data in each transaction bill data set;
the billing processing comprises a lease fee processing and a billing processing which are sequentially executed.
The implementation principle of the transaction bill data processing device provided by the application is similar to that of any embodiment, and is not described herein.
The application provides a processing device of transaction bill data, which is characterized by acquiring a plurality of transaction bill data, wherein each transaction bill data comprises a user identifier and a transaction object identifier, performing association clustering processing on each transaction bill data according to the user identifier and the transaction object identifier of each transaction bill data to obtain at least one transaction bill data set, and respectively performing and issuing account processing on each transaction bill data of each transaction bill data set aiming at each transaction bill data set. By using the method provided by the application, the operator can bill the bill of the user in real time, and the bill billing efficiency and accuracy are improved.
Example III
Fig. 4 is a schematic structural diagram of another processing device for transaction bill data according to the present application. For convenience of explanation, only parts relevant to the present application are shown.
Referring to fig. 3, the processing apparatus 400 includes:
an obtaining module 410, configured to obtain a plurality of transaction bill data, where each transaction bill data includes a user identifier and a transaction object identifier;
the association module 420 is configured to perform association clustering processing on each transaction bill data according to the user identifier and the transaction object identifier of each transaction bill data, so as to obtain at least one transaction bill data set;
The billing module 430 is configured to perform and bill the transaction bill data of each transaction bill data set for each transaction bill data set.
Optionally, the association module 420 includes:
A first association unit 421, configured to perform a first association clustering process on each transaction bill data according to the transaction object identifiers in each transaction bill data, so that the transaction bill data with the same transaction object identifier are divided into the same candidate data set;
and a second association unit 422, configured to perform a second association clustering process on each candidate data set according to the user identifier in each transaction bill data, so that candidate data sets with the same user identifier are divided into the same transaction bill data set.
Optionally, the accounting module 430 includes:
And a concurrency processing unit 431, configured to concurrency execute a billing process on the transaction bill data in each transaction bill data set, where the billing process includes a lease fee process and a bill process that are executed sequentially.
It will be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working process of the processing apparatus may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.
The application provides a processing device of transaction bill data, which is characterized by acquiring a plurality of transaction bill data, wherein each transaction bill data comprises a user identifier and a transaction object identifier, performing association clustering processing on each transaction bill data according to the user identifier and the transaction object identifier of each transaction bill data to obtain at least one transaction bill data set, and respectively performing and issuing account processing on each transaction bill data of each transaction bill data set aiming at each transaction bill data set. By using the method provided by the application, the operator can bill the bill of the user in real time, and the bill billing efficiency and accuracy are improved.
Example IV
Fig. 5 is a schematic diagram of a transaction bill data processing system according to the present application. For convenience of explanation, only parts relevant to the present application are shown.
As shown in fig. 5, the processing system 500 includes:
A processing device 510 and an operator database 520 for the transaction bill data;
The processing device of the transaction bill data is configured to obtain the transaction bill data uploaded by the operator database, and process the obtained transaction bill data according to the processing method of the transaction bill data in any embodiment.
Example five
Fig. 6 is a schematic diagram of a hardware structure of the electronic device according to the present application, and for convenience of explanation, only a portion relevant to the present application is shown.
Referring to fig. 6, a schematic structural diagram of an electronic device 1000 suitable for implementing embodiments of the present application is shown, where the electronic device 1000 may be a terminal device. Among them, the terminal device may include, but is not limited to, a mobile terminal such as a mobile phone, a notebook computer, a digital broadcast receiver, a Personal Digital Assistant (PDA) or the like, a tablet computer (Portable Android Device) or the like, a Portable Multimedia Player (PMP) or the like, a vehicle-mounted device (e.g., a vehicle-mounted navigation terminal) or the like, and a fixed terminal such as a digital TV or a desktop computer or the like. The electronic device shown in fig. 6 is only an example and should not be construed as limiting the functionality and scope of use of the embodiments of the application.
As shown in fig. 6, the electronic apparatus 1000 may include an output device (e.g., a central processor, a graphics processor, etc.) 1007 that may perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 1002 or a program loaded from a storage device 1008 into a random access Memory (Random Access Memory RAM) 1003. In the RAM 1003, various programs and data necessary for the operation of the electronic apparatus 1000 are also stored. The processing device 1001, the ROM 1002, and the RAM 1003 are connected to each other by a bus 1004. An input/output (I/O) interface 1005 is also connected to bus 1004.
In general, devices may be connected to I/O interface 1005 including input devices 1006 such as a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc., output devices 1007 including, for example, a Liquid CRYSTAL DISPLAY (LCD), speakers, vibrator, etc., storage devices 1008 including, for example, magnetic tape, hard disk, etc., and communication devices 1009. The communication means 1009 may allow the electronic device 1000 to communicate wirelessly or by wire with other devices to exchange data. While fig. 6 shows an electronic device 1000 having various means, it is to be understood that not all of the illustrated means are required to be implemented or provided. More or fewer devices may be implemented or provided instead.
In particular, according to embodiments of the present application, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, embodiments of the present application include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method shown in the flowcharts. In such an embodiment, the computer program may be downloaded and installed from a network via the communication device 1009, or installed from the storage device 1008, or installed from the ROM 1002. When being executed by the processing means 1001, performs the above-described functions defined in the method of the embodiment of the present application.
The computer readable medium of the present application may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of a computer-readable storage medium may include, but are not limited to, an electrical connection having one or more wires, a portable computer diskette, 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 disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present application, however, the computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to electrical wiring, fiber optic cable, RF (radio frequency), and the like, or any suitable combination of the foregoing.
The computer readable medium may be included in the electronic device or may exist alone without being incorporated into the electronic device.
The computer-readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to perform the methods shown in the above-described embodiments.
The present application provides a computer program product in which computer program code for performing the operations of the present disclosure can be written in one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or media library. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a local area network (Local Area Network, LAN for short) or a wide area network (Wide Area Network, WAN for short), or may be connected to an external computer (e.g., through the internet using an internet service provider).
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units involved in the embodiments of the present application may be implemented in software or in hardware. The name of the unit does not in any way constitute a limitation of the unit itself, for example the first acquisition unit may also be described as "unit acquiring at least two internet protocol addresses".
The functions described above herein may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic that may be used include Field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems-on-a-chip (SOCs), complex Programmable Logic Devices (CPLDs), and the like.
In the context of the present application, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, 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 disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
Other embodiments of the application will be apparent to those skilled in the art from consideration of the specification and practice of the application disclosed herein. The embodiments of the present application are intended to cover any variations, uses, or adaptations of the application following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the application pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the application being indicated by the following claims.
It is to be understood that the application is not limited to the precise arrangements and instrumentalities shown in the drawings, which have been described above, and that various modifications and changes may be effected without departing from the scope thereof. The scope of the application is limited only by the appended claims.
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| JP2017107496A (en) * | 2015-12-11 | 2017-06-15 | Kddi株式会社 | Display control device, display control method, and display control program |
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| US10679196B2 (en) * | 2007-09-28 | 2020-06-09 | The Western Union Company | Bill payment aggregation service |
| US9576318B2 (en) * | 2012-09-25 | 2017-02-21 | Mx Technologies, Inc. | Automatic payment and deposit migration |
| JP6073171B2 (en) * | 2013-03-29 | 2017-02-01 | 株式会社 日立マネジメントパートナー | Claim deposit matching device, bill deposit matching method and bill deposit matching program |
| US10192206B2 (en) * | 2016-07-26 | 2019-01-29 | Intuit Inc. | Method and system for integrating discrete invoices into a personal financial management and bill payment system and then aggregating discrete invoices having the same payor user and the same payee business into a single payment due item for processing |
| CN110879816A (en) * | 2019-10-30 | 2020-03-13 | 支付宝(杭州)信息技术有限公司 | Associated account identification method and device and electronic equipment |
| EP3869372B1 (en) * | 2020-02-19 | 2024-11-13 | Mastercard International Incorporated | A method of sending data |
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| JP2017107496A (en) * | 2015-12-11 | 2017-06-15 | Kddi株式会社 | Display control device, display control method, and display control program |
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