CN110874789B - Data processing method and device and terminal - Google Patents
Data processing method and device and terminal Download PDFInfo
- Publication number
- CN110874789B CN110874789B CN201910910532.1A CN201910910532A CN110874789B CN 110874789 B CN110874789 B CN 110874789B CN 201910910532 A CN201910910532 A CN 201910910532A CN 110874789 B CN110874789 B CN 110874789B
- Authority
- CN
- China
- Prior art keywords
- data
- user account
- target
- processed
- expected
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- 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
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/12—Accounting
- G06Q40/125—Finance or payroll
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/903—Querying
- G06F16/90335—Query processing
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Accounting & Taxation (AREA)
- Finance (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Databases & Information Systems (AREA)
- General Physics & Mathematics (AREA)
- Development Economics (AREA)
- Technology Law (AREA)
- General Business, Economics & Management (AREA)
- Strategic Management (AREA)
- Marketing (AREA)
- Computational Linguistics (AREA)
- Economics (AREA)
- Data Mining & Analysis (AREA)
- General Engineering & Computer Science (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a data processing method, a device and a terminal, wherein the method comprises the following steps: responding to the data processing request, and acquiring target data of an object to be processed; acquiring a first user account and a second user account associated with an object to be processed; acquiring first expected data corresponding to a first user account and second expected data corresponding to a second user account in an object to be processed; if the first expected data and the second expected data are not consistent, selecting a reference object matched with the object to be processed from the historical processing objects; calculating recommended data of the object to be processed according to the reference object, the first expected data, the second expected data and the target data; and respectively sending the recommended data to a first terminal pointed by the first user account and a second terminal pointed by the second user account so as to confirm whether the recommended data is final data. The invention has the advantages of improving the data processing speed and simplifying the data processing flow.
Description
Technical Field
The present invention relates to data processing technologies, and in particular, to a data processing method, an apparatus, and a terminal.
Background
In daily transactions, when a settlement subject and a settlement object check accounts, if bill differences exist, the bill detail needs to be checked manually and repeatedly offline, difference points are confirmed, then bill modification is carried out, and the account checking process is initiated again, so that the operation is complex and slow.
Disclosure of Invention
In order to solve the above technical problem, a first aspect of the present invention provides a data processing method, where the data processing method includes:
responding to the data processing request, and acquiring target data of an object to be processed;
acquiring a first user account and a second user account associated with the object to be processed;
acquiring first expected data corresponding to the first user account and second expected data corresponding to a second user account in the object to be processed;
if the first expected data and the second expected data are not consistent, selecting a reference object matched with the object to be processed from historical processing objects;
calculating recommendation data of the object to be processed according to the reference object, the first expected data, the second expected data and the target data;
and respectively sending the recommended data to a first terminal pointed by the first user account and a second terminal pointed by the second user account so as to confirm whether the recommended data is final data.
Further, the data processing method further includes:
and if the first expected data and the second expected data are consistent, the first expected data or the second expected data serving as the final data are respectively sent to a first terminal pointed by the first user account and a second terminal pointed by the second user account.
Further, the selecting a reference object matched with the object to be processed from the history processing objects includes:
acquiring a set of related objects from a history processing object according to the object to be processed, wherein the related user account of the related object is the same as the first user account and the second user account;
selecting a target related object from the set of related objects, wherein the absolute value of the difference between target data of the target related object and target data of the object to be processed is smaller than the absolute value of the difference between target data of non-target related objects in the set of related objects and target data of the object to be processed;
and selecting the reference object according to the related data of the target related object and the related data of the object to be processed.
Further, the selecting the reference object according to the relevant data of the target relevant object and the relevant data of the object to be processed includes:
If only one target related object exists, taking the target related object as the reference object;
and if the target related objects are multiple, selecting the reference object according to the type of the object to be processed, the generating place of the object to be processed and/or the generating time of the object to be processed.
Further, the calculating the recommendation data of the object to be processed according to the reference object, the first expected data, the second expected data and the target data comprises:
respectively calculating a first deviation degree corresponding to the first user account and a second deviation degree corresponding to the second user account according to the reference object, wherein the deviation degrees refer to deviation degrees of historical expected data corresponding to the first user account or historical expected data corresponding to the second user account and historical final data of the reference object;
and calculating the recommended data of the object to be processed according to the first deviation degree, the second deviation degree, the first expected data, the second expected data and the target data.
Further, the calculating, according to the reference object, a first deviation degree corresponding to the first user account and a second deviation degree corresponding to the second user account includes:
And respectively calculating the first deviation degree and the second deviation degree according to the historical target data, the historical final data, the first historical expected data corresponding to the first user account and the second historical expected data corresponding to the second user account of the reference object.
Further, the calculating the recommendation data of the object to be processed according to the first deviation degree, the second deviation degree, the first expected data, the second expected data and the target data includes:
determining a reference deviation degree according to the first deviation degree and the second deviation degree;
determining reference expected data according to the reference deviation degree, the first expected data and the second expected data;
and calculating the recommendation data according to the reference deviation degree, the reference expected data and the target data.
Further, the calculating the recommendation data according to the reference deviation degree, the reference expected data and the target data comprises:
calculating a deviation value according to the reference deviation degree and the reference expected data;
comparing the size of the reference expected data and the target data;
if the reference expected data is larger than the target data, taking the sum of the reference expected data and the deviation value as the recommended data;
And if the reference expected data is smaller than the target data, taking the difference between the reference expected data and the deviation value as the recommended data.
In a second aspect, the present invention also provides a data processing apparatus, including:
the target data acquisition module is used for responding to the data processing request and acquiring target data of the object to be processed;
the user account acquisition module is used for acquiring a first user account and a second user account which are associated with the object to be processed;
an expected data acquisition module, configured to acquire first expected data corresponding to the first user account and second expected data corresponding to a second user account in the object to be processed;
a reference object selection module, configured to select, if the first expected data and the second expected data are inconsistent, a reference object that matches the object to be processed from among historical processing objects;
the recommended data calculation module is used for calculating recommended data of the object to be processed according to the reference object, the first expected data, the second expected data and the target data;
and the sending module is used for respectively sending the recommended data to a first terminal pointed by the first user account and a second terminal pointed by the second user account so as to confirm whether the recommended data is final data.
In a third aspect, the present invention also provides a data processing terminal, including a processor and a memory, where the memory stores at least one instruction, at least one program, a code set, or a set of instructions, and the at least one instruction, the at least one program, the code set, or the set of instructions is loaded and executed by the processor to implement the data processing method according to any one of the above.
By adopting the technical scheme, the invention has the following beneficial effects: the target data to be processed of the object to be processed can be re-determined according to the data information of the historical processing object, so that the data processing speed is increased, and the data confirmation process is simplified.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic flow chart of a data processing method according to an embodiment of the present invention;
Fig. 2 is a flowchart illustrating an implementation method of step S400 according to an embodiment of the present invention;
fig. 3 is a flowchart illustrating an implementation method of step S430 according to an embodiment of the present invention;
fig. 4 is a flowchart illustrating an implementation method of step S500 according to an embodiment of the present invention;
fig. 5 is a flowchart illustrating an implementation method of step S520 according to an embodiment of the present invention;
fig. 6 is a schematic flowchart of an implementation method of step S523 according to an embodiment of the present invention;
FIG. 7 is a schematic diagram of a data processing system in accordance with the present invention;
FIG. 8 is a flowchart illustrating a data processing method for an application scenario provided by the present invention;
FIG. 9 is a flowchart illustrating a data processing method for an application scenario provided by the present invention;
fig. 10 is a schematic structural diagram of a data processing apparatus according to the present invention.
1-a first terminal; 2-a second terminal; 3-a server; 4-a data processing device; 401-target data acquisition module; 402-a user account acquisition module; 403-expected data acquisition module; 404-a reference object selection module; 405-a recommendation data calculation module; 406-a sending module.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or server that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Referring to fig. 1, fig. 1 is a flow chart of a data processing method according to an embodiment of the present invention, and the present specification provides the operation steps of the method according to the embodiment or the flow chart, but may include more or less operation steps based on conventional or non-inventive labor. The order of steps recited in the embodiments is merely one manner of performing the steps in a multitude of orders and does not represent the only order of execution. In practice, the system or server product may be implemented in a sequential or parallel manner (e.g., parallel processor or multi-threaded environment) according to the embodiments or methods shown in the figures. Specifically, as shown in fig. 1, the method may include:
S100: and responding to the data processing request, and acquiring target data of the object to be processed.
In this embodiment of the present specification, the data processing request may be submitted by a terminal, or may be sent by a processor during a processing procedure. The target data may be initial data generated by processing by the processing system or may be data obtained from an external data source.
In practical applications, when the data processing request is submitted by a terminal, a user at the terminal side can submit the data processing request through the terminal. The terminal side user can also submit the expected data of the terminal side user when submitting the data processing request. And when the target data is initial data generated by processing of the processing system, the initial data is data obtained by processing according to a preset processing method of the object to be processed.
S200: and acquiring a first user account and a second user account associated with the object to be processed.
In actual application, a first user and a second user generate transactions or other behaviors online or offline, and the first user and the second user can respectively use corresponding user accounts to perform online processing. Thus, the object to be processed can be associated with at least two account numbers.
S300: and acquiring first expected data corresponding to the first user account and second expected data corresponding to a second user account in the object to be processed.
In practical applications, the first expected data may be expected data submitted by a first user via a first user account, and the second expected data may be expected data submitted by a second user via a second user account.
In this embodiment, the first expected data may be expected data obtained by the first user according to the target data, and the second expected data may be expected data obtained by the second user according to the target data.
S400: and if the first expected data and the second expected data are not consistent, selecting a reference object matched with the object to be processed from the objects to be processed in history.
It is understood that the history processing object refers to a processing object that has been completed before the to-be-processed object occurs.
In practical application, there may be a plurality of history processing objects, and during subsequent processing, the history processing objects may be selected, and a reference object matched with the object to be processed is selected, so as to improve processing efficiency and reliability of a processing result.
It should be noted that the number of the reference objects may be one or multiple. When only one object is needed, the reference object is the object with the highest matching rate with the object to be processed; when there are a plurality of them, the comprehensive consideration can be made by a plurality of objects.
In some possible embodiments, as shown in fig. 2, the step S400 may include
S410: and acquiring a set of related objects from the history processing objects according to the objects to be processed, wherein the related user accounts of the related objects are the same as the first user account and the second user account.
It can be understood that each history processing object is associated with a corresponding user account, and when the associated account in the history processing object is the same as the associated account of the object to be processed, that is, when the associated accounts in the history processing object are the first user account and the second user account, respectively, the history processing object is an object associated with the object to be processed.
In practical application, there may be a plurality of related objects, so the set of related objects may be obtained from the history processing object. It should be noted that there may be a plurality of related objects or only one related object in the set of related objects.
S420: and selecting a target related object from the set of related objects, wherein the absolute value of the difference between the target data of the target related object and the target data of the object to be processed is smaller than the absolute value of the difference between the target data of the non-target related object in the set of related objects and the target data of the object to be processed.
In actual application, if there are multiple related objects in the set of related objects, a target related object may be selected from the set of related objects. It will be appreciated that the selection criteria for the target related object may be adaptively modified depending on the particular implementation scenario.
In one usage scenario, the selection may be made according to the target data of each related object and the target data of the object to be processed. Specifically, the selection may be performed according to a difference between target data of each related object and target data of the object to be processed. Preferably, the related object with the smallest difference value with the target data of the object to be processed may be selected as the target related object.
In another usage scenario, the selection may also be made according to other non-target data associated with the object to be processed. For example, in this scenario, the target data is money data, and the other non-target data may be time, place, weather, and other data information. In summary, according to a specific usage scenario, the corresponding data information may be selected to select the target related object from the set of related objects.
S430: and selecting the reference object according to the related data of the target related object and the related data of the object to be processed.
In some possible embodiments, as shown in fig. 3, the step S430 may include
S431: and if only one target related object exists, taking the target related object as the reference object.
S432: and if the target related objects are multiple, selecting the reference object according to the type of the object to be processed, the generating place of the object to be processed and/or the generating time of the object to be processed.
It is to be understood that when selecting the target related object from the set of related objects, there may be a plurality of target related objects or only one target related object after selection according to the corresponding selection criteria. When there are a plurality of the target related objects, the object with the highest degree of correlation with the object to be processed may be further selected according to other conditions.
For example, in the process of selecting the target related object from the set of related objects, the target related object is limited and selected by target data; if there is only one target related object, the target related object can be used as the reference object; if there are a plurality of target related objects, the target related objects may be selected according to other non-target data of the object to be processed, where the non-target data may be a type, a place of occurrence, a time of occurrence, and the like of the object to be processed.
The above contents provide a way of selecting a reference object matched with the object to be processed, which may be selected according to target data and other non-target data information of the object to be processed, and may be sequentially used as a limit according to importance degrees of the target data and the non-target data, so as to gradually select the reference object with the highest correlation with the object to be processed.
In other possible embodiments, when the reference object matched with the object to be processed is selected from the history processing objects in S400, the reference object may be further selected according to a matching rate:
acquiring a set of related objects from the history processing objects;
respectively calculating the matching rate between each related object in the related object set and the object to be processed;
and selecting the related object with the highest matching rate as the reference object.
Further, the matching rate may be calculated by target data and non-target data in the object to be processed and corresponding target data and non-target data in the related object. The calculation process may be calculation according to the weight of each data or may be averaging, and the specific use of the calculation method may be selected by those skilled in the art according to the requirements of a specific scenario.
S500: and calculating recommendation data of the object to be processed according to the reference object, the first expected data, the second expected data and the target data.
In some possible embodiments, as shown in fig. 4, the step S500 includes
S510: and respectively calculating a first deviation degree corresponding to the first user account and a second deviation degree corresponding to the second user account according to the reference object, wherein the deviation degrees refer to the deviation degrees of the historical expected data corresponding to the first user account or the historical expected data corresponding to the second user account and the historical final data of the reference object.
In some possible embodiments, the step S510 includes:
and respectively calculating the first deviation degree and the second deviation degree according to the historical target data, the historical final data, the first historical expected data corresponding to the first user account and the second historical expected data corresponding to the second user account of the reference object.
S520: and calculating the recommended data of the object to be processed according to the first deviation degree, the second deviation degree, the first expected data, the second expected data and the target data.
In some possible embodiments, as shown in fig. 5, the step S520 includes
S521: and determining a reference deviation degree according to the first deviation degree and the second deviation degree.
S522: determining reference expected data according to the reference deviation degree, the first expected data and the second expected data.
In some possible embodiments, the reference expected amount is an expected amount of the user corresponding to the reference deviation.
S523: and calculating the recommendation data according to the reference deviation degree, the reference expected data and the target data.
In some possible embodiments, as shown in fig. 6, the step S523 includes
S5231: calculating a deviation value according to the reference deviation degree and the reference expected data;
s5232: comparing the size of the reference expected data and the target data;
s5233: if the reference expected data is larger than the target data, taking the sum of the reference expected data and the deviation value as the recommended data;
s5234: and if the reference expected data is smaller than the target data, taking the difference between the reference expected data and the deviation value as the recommended data.
S600: and respectively sending the recommended data to a first terminal pointed by the first user account and a second terminal pointed by the second user account so as to confirm whether the recommended data is final data.
It will be appreciated that the first user may log in to the first user account on the first terminal to receive the recommendation data and decide whether to confirm the recommendation data as final data. And the second user can log in the second user account on the second terminal to receive the recommendation data and decide whether to confirm the recommendation data as final data.
In some possible embodiments, the data processing method further includes
S700: and if the first expected data and the second expected data are consistent, respectively sending the first expected data or the second expected data as the final data to a first terminal pointed by the first user account and a second terminal pointed by the second user account.
Referring to fig. 7, fig. 7 is a schematic diagram of a system according to an embodiment of the present invention, and as shown in fig. 7, the system may include at least a first terminal 1, a second terminal 2, and a server 3.
Specifically, the first terminal 1 may include a smart phone, a tablet computer, a notebook computer, a digital assistant, a smart wearable device, a vehicle-mounted terminal, and other types of physical devices, and may also include software running in the physical devices, such as an application program.
Specifically, the second terminal 2 may include a smart phone, a tablet computer, a notebook computer, a digital assistant, a smart wearable device, a vehicle-mounted terminal, and other types of physical devices, and may also include software running in the physical devices, such as an application program.
Specifically, the server 3 may include a server operating independently, or a distributed server, or a server cluster composed of a plurality of servers. The server 3 may comprise a network communication unit, a processor and a memory, etc. Specifically, the control server 3 may provide background services for the first terminal 1 and the second terminal 2.
The following describes a data processing method of the present invention based on the above system, and the method may include:
s1: and the first terminal and/or the second terminal sends a data processing request to the server.
In practical application, after generating target data of an object to be processed, a server sends the target data to the first terminal and the second terminal. A first user corresponding to the first terminal may have a data processing requirement for the target data, or a second user corresponding to the second terminal may have a data processing requirement for the target data, or both the first user and the second user may have a data processing requirement for the target data.
When any one or two of the two parties have doubt on the target data and have a data processing requirement, a data processing request can be sent to the server through the corresponding terminal.
In some possible embodiments, when the first user sends a data processing request to the server through the first terminal, the first user may also send own expected data of the target data, that is, the first expected data. Accordingly, the second user may also send its own expected data for the target data, i.e., second expected data.
S2: the server responds to the data processing request and acquires target data of an object to be processed; acquiring a first user account and a second user account associated with the object to be processed; acquiring first expected data corresponding to the first user account and second expected data corresponding to a second user account in the object to be processed; if the first expected data and the second expected data are not consistent, selecting a reference object matched with the object to be processed from historical processing objects; calculating recommendation data of the object to be processed according to the reference object, the first expected data, the second expected data and the target data; and respectively sending the recommendation data to a first terminal pointed to by the first user account and a second terminal pointed to by the second user account.
S3: and the first terminal and the second terminal respectively accept the recommended data, and a first user corresponding to the first terminal and a second user corresponding to the second terminal respectively confirm whether the recommended data is used as final data or not.
It can be understood that, if both the first user and the second user confirm that the recommended data is the final data, the processing of the object to be processed is completed, and the recommended data is the final data. If one or both of the first user and the second user has doubt that the recommended data needs to be processed again, the first user and/or the second user can send a data processing request to the server again, and the server performs calculation processing again according to the historical processing object until the first user and the second user confirm the target data of the object to be processed.
The data processing method provided in the embodiments of the present specification is described below with reference to specific implementation scenarios. In practical implementation, it can be implemented in the following scenario: in daily transactions, when a settlement subject and a settlement object perform reconciliation (such as reconciliation of a payee and a payer), if a bill difference exists, the bill detail needs to be checked manually and repeatedly offline, a difference point is confirmed, then bill modification is performed, and a reconciliation process is initiated again, which is tedious and slow. When the data processing method is implemented in this scenario, as shown in fig. 8, the method includes:
S100': and responding to the data processing request, and acquiring the target amount of the bill to be processed.
It is understood that the target amount refers to a bill settlement amount initially generated by the bill to be processed.
S200': and acquiring a first user account and a second user account associated with the bill to be processed.
It will be appreciated that the first user account may be an account of a payee, and the second user account may be an account of a payer.
S300': and acquiring a first expected amount corresponding to the first user account and a second expected amount corresponding to the second user account in the bill to be processed.
It is to be understood that the first expected amount may be an amount of settlement of the bill to be processed considered by the first user, and the second expected amount may be an amount of settlement of the bill to be processed considered by the second user.
S400': and if the first expected amount is inconsistent with the second expected amount, selecting a reference bill matched with the bill to be processed from the historical processed bills.
In some possible embodiments, the step S400' may include
S410': and acquiring a set of related bills from the historical processed bills according to the bills to be processed, wherein the related user account of the related bills is the same as the first user account and the second user account.
And S420': and selecting a target related bill from the set of related bills, wherein the absolute value of the difference between the target amount of the target related bill and the target amount of the bill to be processed is smaller than the absolute value of the difference between the target amount of the non-target related bill in the set of related bills and the target amount of the bill to be processed.
S430': and selecting the reference bill according to the relevant data of the target relevant bill and the relevant data of the bill to be processed.
It is understood that the related data may be data other than the target amount involved in the pending bill, and may be data of the type, the place of occurrence, the time of occurrence, and the like of the bill.
In some possible embodiments, the step S430' may include
S431': and if only one target related bill exists, taking the target related bill as the reference bill.
S432': and if the target related bills are multiple, selecting the reference bill according to the type of the bill to be processed, the generation place of the bill to be processed and/or the generation time of the bill to be processed.
S500': calculating a recommended amount of the bill to be processed according to the reference bill, the first expected amount, the second expected amount and the target amount.
In some possible embodiments, the step S500' includes
S510': and respectively calculating a first deviation degree corresponding to the first user account and a second deviation degree corresponding to the second user account according to the reference bill, wherein the deviation degrees refer to the deviation degrees of the historical expected amount corresponding to the first user account or the historical expected amount corresponding to the second user account and the historical final amount of the reference bill.
In some possible embodiments, the step S510' includes:
and respectively calculating the first deviation degree and the second deviation degree according to the historical target amount, the historical final amount, the first historical expected amount corresponding to the first user account and the second historical expected amount corresponding to the second user account of the reference bill.
S520': and calculating the recommended amount of the bill to be processed according to the first deviation degree, the second deviation degree, the first expected amount, the second expected amount and the target amount.
In some possible embodiments, the step S520' includes
S521': and determining a reference deviation degree according to the first deviation degree and the second deviation degree.
S522': determining a reference expected amount according to the reference deviation degree, the first expected amount and the second expected amount.
In some possible embodiments, the reference expected amount is an expected amount of the user corresponding to the reference deviation.
S523': and calculating the recommended amount according to the reference deviation degree, the reference expected amount and the target amount.
In some possible embodiments, the step S523' includes
S5231': calculating a deviation value according to the reference deviation degree and the reference expected amount;
s5232': comparing the reference expected amount to the target amount;
s5233': if the reference expected amount is larger than the target amount, taking the sum of the reference expected amount and the deviation value as the recommended amount;
s5234': and if the reference expected amount is smaller than the target amount, taking the difference between the reference expected amount and the deviation value as the recommended amount.
For the above process, assuming that the first user is the payee, the first user account is the payee account; if the second user is a payer, the account of the second user is the account of the payer;
for pending bills: the target amount is c and the first expected amount is a 1 The second expected amount is b 1 ；
For reference bills: the historical target amount is W, the historical final amount is Z, and the first historical expected amount is Q n The second historical expected amount is q n ；
Then, the degree of deviation of the payee is | Q n -Z/| W-Z |; the degree of deviation of the payer is | q n -Z|/|W-Z|；
If the degree of deviation of the payee is less than the degree of deviation of the payer, | Q n -Z/| W-Z | as a reference deviation; deviation value of | Q n -Z|/|W-Z|*|c-a 1 L, |; the reference expected amount is the first expected amount a 1 ；
If the reference expected amount a 1 If the sum is larger than the target sum W, the recommended sum is a 1 +|Q n -Z|/|W-Z|*|c-a 1 |；
If the reference expected amount a 1 If the sum is less than the target sum W, the recommended sum is a 1 -|Q n -Z|/|W-Z|*|c-a 1 |。
When calculating the deviation degree, if the payee and the payer submit historical expected amounts more than once, the average values of the historical expected amounts can be respectively taken as the deviation degree.
S600': and respectively sending the recommended amount to a first terminal pointed by the first user account and a second terminal pointed by the second user account so as to confirm whether the recommended amount is the final amount.
In some possible embodiments, the data processing method further includes
S700': and if the first expected amount is consistent with the second expected amount, sending the first expected amount or the second expected amount as the final amount to a first terminal pointed by the first user account and a second terminal pointed by the second user account respectively.
It is to be understood that, if both the payee and the payer confirm that the recommended amount is the final amount, the pending bill processing is completed, and the recommended amount is the final amount. If either or both of the payee and the payer are doubtful that the recommended amount is still to be processed, the payee and/or the payer may request again until the payee and/or the payer confirm the target amount of the bill to be processed.
Through the data processing method, when the user checks accounts, bills can be generated and difference feedback can be online, and online communication cost is reduced. The difference processing is realized by automatically checking the difference situation and updating the bill by the system, so that the labor checking cost is reduced. Both sides of the transaction can see respective bills on line, feed back differences on line, automatically update bills, confirm on line, realize the whole flow process of account checking on line, and greatly reduce the time and cost of account checking.
Introducing a data processing method of the present invention based on the above system and combining the above listed implementation scenarios, fig. 9 is a schematic flow chart of a data processing method provided in an embodiment of the present invention, where the method includes:
S1': and the first terminal and/or the second terminal sends a re-account checking request to the server.
S2': the server readjusts the bill in response to the reconciled account request.
The readjusting the bill comprises:
acquiring a target amount of an object to be processed;
acquiring a first user account and a second user account associated with the object to be processed; acquiring a first expected amount corresponding to the first user account and a second expected amount corresponding to a second user account in the bill to be processed;
if the first expected amount is inconsistent with the second expected amount, selecting a reference bill matched with the bill to be processed from historical processed bills;
calculating a recommended amount of the bill to be processed according to the reference bill, the first expected amount, the second expected amount and the target amount;
and respectively sending the recommended amount to a first terminal pointed by the first user account and a second terminal pointed by the second user account so as to confirm whether the recommended amount is the final amount.
S3': and the first terminal and the second terminal respectively accept the recommended sum, and a first user corresponding to the first terminal and a second user corresponding to the second terminal respectively confirm whether the recommended sum is the final sum or not.
Before the step S1', the method further includes: the system generates bills according to the bill data and sends the bills to the first terminal and the second terminal respectively.
An embodiment of the present invention further provides a data processing apparatus, and as shown in fig. 10, the data processing apparatus 4 includes:
a target data obtaining module 401, configured to obtain target data of an object to be processed in response to a data processing request;
a user account acquisition module 402, configured to acquire a first user account and a second user account associated with the object to be processed;
an expected data obtaining module 403, configured to obtain first expected data corresponding to the first user account and second expected data corresponding to a second user account in the object to be processed;
a reference object selecting module 404, configured to select, if the first expected data and the second expected data are inconsistent, a reference object that matches the object to be processed from among historical processing objects;
a recommended data calculating module 405, configured to calculate recommended data of the object to be processed according to the reference object, the first expected data, the second expected data, and the target data;
a sending module 406, configured to send the recommended data to a first terminal pointed to by the first user account and a second terminal pointed to by the second user account, respectively, so as to determine whether the recommended data is final data.
An embodiment of the present invention further provides a server for data processing, where the server includes a processor and a memory, where the memory stores at least one instruction, at least one program, a code set, or an instruction set, and the at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by the processor to implement any one of the above data processing methods.
The embodiment of the invention also provides a data processing terminal,
the terminal comprises a processor and a memory, wherein at least one instruction, at least one program, a code set or an instruction set is stored in the memory, and the at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by the processor to realize the data processing method of any one of the above.
It should be noted that: the precedence order of the above embodiments of the present invention is only for description, and does not represent the merits of the embodiments. And specific embodiments thereof have been described above. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, as for the apparatus, system and server embodiments, since they are substantially similar to the method embodiments, the description is relatively simple, and reference may be made to some descriptions of the method embodiments for relevant points.
It will be understood by those skilled in the art that all or part of the steps for implementing the above embodiments may be implemented by hardware, or may be implemented by a program instructing relevant hardware, where the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (9)
1. A data processing method, characterized in that the data processing method comprises:
responding to the data processing request, and acquiring target data of an object to be processed;
Acquiring a first user account and a second user account associated with the object to be processed;
acquiring first expected data corresponding to the first user account and second expected data corresponding to a second user account in the object to be processed;
if the first expected data and the second expected data are inconsistent, acquiring a set of related objects from a history processing object according to the object to be processed, wherein the related user account of the related objects is the same as the first user account and the second user account; selecting a target related object from the set of related objects, wherein the absolute value of the difference between target data of the target related object and target data of the object to be processed is smaller than the absolute value of the difference between target data of non-target related objects in the set of related objects and target data of the object to be processed; selecting a reference object according to the related data of the target related object and the related data of the object to be processed;
calculating recommendation data of the object to be processed according to the reference object, the first expected data, the second expected data and the target data;
and respectively sending the recommended data to a first terminal pointed by the first user account and a second terminal pointed by the second user account so as to confirm whether the recommended data is final data.
2. The data processing method of claim 1, further comprising:
and if the first expected data and the second expected data are consistent, respectively sending the first expected data or the second expected data as the final data to a first terminal pointed by the first user account and a second terminal pointed by the second user account.
3. The data processing method according to claim 1, wherein said selecting the reference object according to the related data of the target related object and the related data of the object to be processed comprises:
if only one target related object exists, taking the target related object as the reference object;
and if the target related objects are multiple, selecting the reference object according to the type of the object to be processed, the generating place of the object to be processed and/or the generating time of the object to be processed.
4. The data processing method of claim 1, wherein the calculating the recommendation data for the object to be processed according to the reference object, the first expectation data, the second expectation data, and the target data comprises:
Respectively calculating a first deviation degree corresponding to the first user account and a second deviation degree corresponding to the second user account according to the reference object, wherein the deviation degrees refer to the deviation degrees of historical expected data corresponding to the first user account or historical expected data corresponding to the second user account and historical final data of the reference object;
and calculating recommended data of the object to be processed according to the first deviation degree, the second deviation degree, the first expected data, the second expected data and the target data.
5. The data processing method according to claim 4, wherein the calculating, according to the reference object, a first deviation degree corresponding to the first user account and a second deviation degree corresponding to the second user account respectively comprises:
and respectively calculating the first deviation degree and the second deviation degree according to the historical target data, the historical final data, the first historical expected data corresponding to the first user account and the second historical expected data corresponding to the second user account of the reference object.
6. The data processing method according to claim 4, wherein the calculating the recommended data of the object to be processed based on the first degree of deviation, the second degree of deviation, the first expected data, the second expected data, and the target data comprises:
Determining a reference deviation degree according to the first deviation degree and the second deviation degree;
determining reference expected data according to the reference deviation degree, the first expected data and the second expected data;
and calculating the recommendation data according to the reference deviation degree, the reference expected data and the target data.
7. The data processing method of claim 6, wherein the calculating the recommendation data from the reference deviation metric, the reference expected data, and the target data comprises:
calculating a deviation value according to the reference deviation degree and the reference expected data;
comparing the size of the reference expected data and the target data;
if the reference expected data is larger than the target data, taking the sum of the reference expected data and the deviation value as the recommended data;
and if the reference expected data is smaller than the target data, taking the difference between the reference expected data and the deviation value as the recommended data.
8. A data processing apparatus, characterized in that the data processing apparatus comprises:
the target data acquisition module is used for responding to the data processing request and acquiring target data of the object to be processed;
The user account acquisition module is used for acquiring a first user account and a second user account which are associated with the object to be processed;
an expected data acquisition module, configured to acquire first expected data corresponding to the first user account and second expected data corresponding to a second user account in the object to be processed;
a reference object selection module, configured to, if the first expected data is inconsistent with the second expected data, obtain a set of related objects from a history processing object according to the object to be processed, where a related user account of the related object is the same as both the first user account and the second user account; selecting a target related object from the set of related objects, wherein the absolute value of the difference between target data of the target related object and target data of the object to be processed is smaller than the absolute value of the difference between target data of non-target related objects in the set of related objects and target data of the object to be processed; selecting the reference object according to the related data of the target related object and the related data of the object to be processed;
the recommended data calculation module is used for calculating recommended data of the object to be processed according to the reference object, the first expected data, the second expected data and the target data;
And the sending module is used for respectively sending the recommended data to a first terminal pointed by the first user account and a second terminal pointed by the second user account so as to confirm whether the recommended data is final data.
9. A terminal for data processing,
the terminal comprises a processor and a memory, in which at least one instruction, at least one program, a set of codes, or a set of instructions is stored, which is loaded and executed by the processor to implement the data processing method according to any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910910532.1A CN110874789B (en) | 2019-09-25 | 2019-09-25 | Data processing method and device and terminal |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910910532.1A CN110874789B (en) | 2019-09-25 | 2019-09-25 | Data processing method and device and terminal |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110874789A CN110874789A (en) | 2020-03-10 |
| CN110874789B true CN110874789B (en) | 2022-07-29 |
Family
ID=69717824
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910910532.1A Active CN110874789B (en) | 2019-09-25 | 2019-09-25 | Data processing method and device and terminal |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110874789B (en) |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106156305A (en) * | 2016-06-30 | 2016-11-23 | 北京奇虎科技有限公司 | Represent the method and device of propelling data |
| CN106250314A (en) * | 2016-08-04 | 2016-12-21 | 合网络技术（北京）有限公司 | A kind of test data capture method and system |
| CN110020176A (en) * | 2017-12-29 | 2019-07-16 | 中国移动通信集团公司 | A kind of resource recommendation method, electronic equipment and computer readable storage medium |
| CN110223137A (en) * | 2019-05-22 | 2019-09-10 | 平安科技（深圳）有限公司 | Product mix recommended method, device, computer equipment and storage medium |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10692014B2 (en) * | 2016-06-27 | 2020-06-23 | Microsoft Technology Licensing, Llc | Active user message diet |
-
2019
- 2019-09-25 CN CN201910910532.1A patent/CN110874789B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106156305A (en) * | 2016-06-30 | 2016-11-23 | 北京奇虎科技有限公司 | Represent the method and device of propelling data |
| CN106250314A (en) * | 2016-08-04 | 2016-12-21 | 合网络技术（北京）有限公司 | A kind of test data capture method and system |
| CN110020176A (en) * | 2017-12-29 | 2019-07-16 | 中国移动通信集团公司 | A kind of resource recommendation method, electronic equipment and computer readable storage medium |
| CN110223137A (en) * | 2019-05-22 | 2019-09-10 | 平安科技（深圳）有限公司 | Product mix recommended method, device, computer equipment and storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110874789A (en) | 2020-03-10 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US20190019186A1 (en) | Systems and methods for automated decentralized multilateral transaction processing | |
| US8713445B2 (en) | Systems and methods for generating customized user interfaces | |
| CN111932238B (en) | Payment account recommendation method and device and electronic equipment | |
| CN107133788A (en) | A kind of reimbursement processing method and processing device | |
| CN106875167B (en) | Detection method and device for fund transaction path in electronic payment process | |
| CN112907344A (en) | Accounting data processing method and device, electronic equipment and storage medium | |
| CN104574182A (en) | Bank reconciliation account configuration method and device | |
| CN110874789B (en) | Data processing method and device and terminal | |
| WO2017106225A1 (en) | A method and system of processing a transaction on a server | |
| US10929237B2 (en) | Error handling tool | |
| CN110009483A (en) | A kind of data processing method and device based on temporal information | |
| CN110990007A (en) | Bank software function interface generation method and device | |
| JP2001306873A (en) | Electronic transaction system | |
| CN114255127A (en) | Accounting consistency processing method and device for distributed system | |
| CN112950355B (en) | Transaction data processing method and device | |
| US20230342753A2 (en) | Systems and methods for event-driven dispute processing using distributed ledger | |
| KR101891734B1 (en) | Notary service providing system for account transfer | |
| CN111754348A (en) | Scene combined transaction method and device | |
| US20240169336A1 (en) | Systems and methods for dynamically switching payment mechanisms for outgoing payments | |
| US20240185192A1 (en) | Recursive distributed ledger for cryptocurrency | |
| US20230131294A1 (en) | Executable code blocks based on captured user interactions | |
| CN111882118B (en) | Decision making system and method | |
| US20240202792A1 (en) | System and method for decentralized marketplaces | |
| CN116523633A (en) | Cross-currency exchange method and device | |
| CN112464272A (en) | Data transfer method, system, terminal, server and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |