CN113515575A - Associated data processing method and device, electronic equipment and storage medium - Google Patents
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Abstract
The embodiment of the application provides a method and a device for processing associated data, electronic equipment and a storage medium, wherein the method comprises the following steps: acquiring target associated data, wherein the target associated data comprises a target license plate number and a target fueling card account which have an association relation; acquiring candidate data, wherein the candidate data comprises associated data between license plate numbers and fuel card accounts which appear at different times and/or in different spaces; and determining the correctness of the target associated data according to the candidate data to obtain the correct target associated data. After the target associated data is acquired, the correctness of the target associated data is verified through the candidate data so as to acquire the correct target associated data, and the accuracy of the acquired target associated data can be effectively improved.
Description
Technical Field
The present application relates to the field of intelligent data analysis, and in particular, to a method and an apparatus for processing associated data, an electronic device, and a storage medium.
Background
With the rapid development of science and technology, the number of motor vehicles is also rapidly increased, and more people use the motor vehicles as transportation tools for daily trips. Gasoline stations can provide energy and power to motor vehicles, and the number of motor vehicles is increasing, so that the distribution of gasoline stations is more and more extensive.
The user can drive motor vehicles to a gas station, staff carries out refueling charging on the motor vehicles, the gas station can acquire information and payment information of the motor vehicles, the payment information can be associated with the motor vehicles, generally, license plate numbers and refueling card accounts are associated, and data support is provided for subsequent intellectualization of the gas station. However, a large number of motor vehicles are refueled in the gas station, a large number of license plate numbers and fueling card accounts can be obtained, and when the association relationship between the motor vehicles and payment information is established, the accuracy of the association relationship is difficult to ensure.
Disclosure of Invention
The embodiment of the application provides a method and a device for processing associated data, electronic equipment and a storage medium, which can effectively solve the problem that the association relation between a motor vehicle and payment information is not accurate enough.
According to a first aspect of embodiments of the present application, there is provided an associated data processing method, including: acquiring target associated data, wherein the target associated data comprises a target license plate number and a target fueling card account which have an association relation; acquiring candidate data, wherein the candidate data comprises associated data between license plate numbers and fuel card accounts which appear at different times and/or in different spaces; and determining the correctness of the target associated data according to the candidate data to obtain the correct target associated data.
According to a second aspect of embodiments of the present application, there is provided an associated data processing apparatus, the apparatus including: the first acquisition module is used for acquiring target associated data, wherein the target associated data comprises a target license plate number and a target fueling card account which have an association relation; the second acquisition module is used for acquiring candidate data, wherein the candidate data comprises the associated data of the license plate number and the fueling card account which appear at different time and/or in different space; and the determining module is used for determining the correctness of the target associated data according to the candidate data to obtain the correct target associated data.
According to a third aspect of embodiments of the present application, there is provided an electronic device comprising one or more processors; a memory; one or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the one or more processors, the one or more programs configured to perform the method as applied to an electronic device, as described above.
According to a fourth aspect of the embodiments of the present application, there is provided a computer-readable storage medium having a program code stored therein, wherein the method described above is performed when the program code runs.
By adopting the associated data processing method provided by the embodiment of the application, target associated data is obtained, wherein the target associated data comprises a target license plate number and a target fueling card account which have an associated relationship; acquiring candidate data, wherein the candidate data comprises associated data of license plate numbers and fueling card accounts which appear at different time and/or in different spaces; and determining the correctness of the target associated data according to the candidate data. After the target associated data is acquired, the correctness of the target associated data is verified through the candidate data so as to acquire the correct target associated data, and the accuracy of the acquired target associated data can be effectively improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
fig. 1 is a flowchart of an associated data processing method according to an embodiment of the present application;
FIG. 2 is a flow chart of a method for processing associated data according to another embodiment of the present application;
FIG. 3 is a flow chart of a method for processing associated data according to yet another embodiment of the present application;
FIG. 4 is a flow chart of a part of the steps of the associated data processing method provided on the basis of the embodiment provided in FIG. 3;
FIG. 5 is a functional block diagram of an associated data processing apparatus according to an embodiment of the present application;
fig. 6 is a block diagram of an electronic device for executing an associated data processing method according to an embodiment of the present application.
Detailed Description
With the rapid development of science and technology, the number of motor vehicles is also rapidly increased, and more people use the motor vehicles as transportation tools for daily trips. Gasoline stations can provide energy and power to motor vehicles, and the number of motor vehicles is increasing, so that the distribution of gasoline stations is more and more extensive. When a user drives a vehicle to a gas station to refuel, the gas station can acquire a large amount of vehicle information and payment information, and can correlate the vehicle information and the payment information to provide data support for intellectualization of the gas station. Generally, a gas station can associate a license plate number with a gasoline card account to provide data support for an intelligent gas station, however, when a plurality of vehicles exist in the gas station, the obtained associated data may have errors and is not accurate enough.
The inventor finds in research that if the associated data occurs again at a different time or in a different space, it can be determined that the associated data is correct. If the associated data is erroneous, the probability of its reoccurrence is extremely low. For example, when the license plate jing a00001 and the fueling card 010001 are associated at the fueling station a, the fueling station a may have the license plate jing B00002, the license plate jing C00003, and the like, and whether the association is correct or not cannot be confirmed. However, when the license plate jing a00001 and the fuel card 010001 are associated again or more times at different times of the fuel station B, C, D or the fuel station a, the license plate jing B00002, jing C00003, and the like are present on site, and the possibility of the fuel cards 020002, 030003, and the like is close to 0. Therefore, whether the associated data is correct or not can be confirmed through the multiple occurrences of the associated data in different time and/or different space, and the accuracy of the associated data can be effectively improved.
Therefore, the embodiment of the application provides a method for processing associated data, which includes acquiring target associated data, wherein the target associated data includes a target license plate number and a target fueling card account which have an association relationship; acquiring candidate data, wherein the candidate data is associated data appearing in historical time; and determining the correctness of the target associated data according to the candidate data. After the target associated data is acquired, the correctness of the target associated data is verified through the candidate data, and the accuracy of the acquired target associated data can be effectively improved.
The scheme in the embodiment of the present application may be implemented by using various computer languages, for example, object-oriented programming language Java and transliterated scripting language JavaScript, Python, and the like.
In order to make the technical solutions and advantages of the embodiments of the present application more apparent, the following further detailed description of the exemplary embodiments of the present application with reference to the accompanying drawings makes it clear that the described embodiments are only a part of the embodiments of the present application, and are not exhaustive of all embodiments. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
Referring to fig. 1, an embodiment of the present application provides a method for processing associated data, which may specifically include the following steps.
Target associated data is obtained, and the target associated data is defined as a target license plate number and a target fueling card account which have an association relation. A large number of vehicles needing to be refueled appear in the gas station every day, and the gas station can be provided with an image acquisition device for acquiring video information. The video information can be identified and analyzed through an artificial intelligence deep learning technology, the license plate number of the refueled vehicle is associated with the refueled card account, and therefore the target associated data can be obtained. The target association data can be an association relation which is established for the first time at the gas station.
And step 120, acquiring candidate data, wherein the candidate data comprises the associated data of the license plate number and the fueling card account which appear at different time and/or in different space.
The candidate data are related data which appear at different time and/or different space, and the related data comprise license plate numbers and fuel card accounts with the related relation.
In some embodiments, a candidate may refer to associated data that occurred within a historical time. For example, the current date is 3 months and 1 day, the historical time is all the time before 3 months and 1 day, and the candidate data is all the relevant data which appear before 3 months and 1 day.
In some embodiments, the candidate data may refer to related data that appears in different spaces, for example, there are a gas station a and a gas station B, where the target related data is acquired by the gas station a, and then the related data acquired by the gas station B is the candidate data.
The candidate data may be stored at a specified location, and the candidate data may be acquired by accessing the specified location.
And step 130, determining the correctness of the target associated data according to the candidate data to obtain correct target associated data.
When the target associated data is acquired, the target associated data may be incorrect due to the numerous vehicles present in the gas station, and thus, the correctness of the target associated data needs to be determined. For example, a vehicle with the license plate number a and a vehicle with the license plate number B simultaneously appear in the gas station, the fueling card account corresponding to the vehicle with the license plate number a should be a, the fueling card account corresponding to the vehicle with the license plate number B should be B, and the acquired target related data indicates that the license plate number a and the fueling card account B have a correlation relationship.
The candidate data comprises the associated data which appear at different time and/or different space, if the target associated data appears in the candidate data, the target associated data is indicated to reappear at different time and/or different space. Since the probability that the target license plate number and the target fueling card account are associated again in different time and/or different space is extremely low, the correctness of the target associated data can be determined through the candidate data. By confirming the correctness of the target associated data, correct target associated data can be obtained.
In different spaces, the image acquisition devices used may have different ways of establishing the association relationship between the license plate number and the fueling card account, and thus the obtained association data may also be different. If the target associated data reappears in different spaces, the association relationship can still be established when the target license plate number and the target fueling card account are in different association modes or different image acquisition devices, and the accuracy of the target associated data can be further improved. For example, the image capture device used by the gas station a and the way of establishing the association relationship are different from those of the gas station B, the target association data is obtained for the first time at the gas station a, and when the target association data is obtained again at the gas station B, the target association data obtained at the gas station a is used as one of the candidate data, and the target association data can be determined to be correct through the candidate data.
In a specific implementation process, the target associated data may also refer to a license plate number and a fueling card account for which an association relationship is established for the first time, and after the target associated data is obtained, the target associated data may be judged to be correct through the candidate data.
Specifically, whether a target fueling card account exists in the candidate data or not may be judged; if the target fueling card account exists, the correctness of the target associated data can be continuously determined according to the target fueling card account and the candidate data.
If the target associated data is determined to be correct, the target associated data can be stored in a preset database for subsequent use.
If the target associated data is determined to be incorrect, which indicates that errors may occur when the license plate number and the fueling card account are associated, the target associated data can be corrected by using temporary data.
The temporary data includes currently acquired unconfirmed associated data, i.e., when the gas station associates the license plate number with the fueling card account, multiple vehicles and multiple fueling card accounts may be present at the same time, so that multiple associated data may be available. Among these pieces of related data, related data whose correctness is being confirmed is target related data, and related data whose correctness cannot be confirmed is the temporary data. For example, the gas station simultaneously obtains the associated data 3, the associated data 4 and the associated data 5, and the correctness of the associated data 3 is being confirmed, then the associated data 3 is the target associated data, and the correctness of the associated data 4 and the associated data 5 which cannot be confirmed is the associated data 4 and the associated data 5, then the associated data 4 and the associated data 5 are temporary data.
The temporary data may also be stored at a specified location, and the temporary data may be acquired by accessing the specified location.
In some embodiments, the temporary data may be converted into the candidate data. Specifically, the temporary data may be converted into the candidate data at preset time intervals. The preset time interval may be set as needed without particular limitation, and may be, for example, one hour, one day, or the like. Assuming that the preset time interval is 1 day, and the current date is 3 months and 1 days, the associated data acquired before 3 months and 1 days is candidate data, and the unconfirmed associated data acquired on 3 months and 1 days is temporary data.
When the obtained license plate numbers and the oiling card account information are associated by the gas station, omission may occur, and no associated license plate numbers appear, so that the license plate numbers can be obtained, and the license plate numbers are associated with the target oiling card account one by one to obtain first associated data. And when the first associated data has correct associated data, correcting the target associated data. If the first associated data does not have correct associated data, the target associated data may be corrected according to the temporary data and the candidate data.
The associated data processing method provided by the embodiment of the application obtains target associated data, wherein the target associated data comprises a target license plate number and a target fueling card account which have an association relation; acquiring candidate data, wherein the candidate data comprises associated data of license plate numbers and fueling card accounts which appear at different time and/or in different spaces; and determining the correctness of the target associated data according to the candidate data. After the target associated data is acquired, the correctness of the target associated data is verified through the candidate data so as to acquire the correct target associated data, and the accuracy of the acquired target associated data can be effectively improved.
Referring to fig. 2, another embodiment of the present application provides a method for processing associated data, which focuses on describing the process of confirming the correctness of the target associated data based on the foregoing embodiment.
Step 210 and step 220 can refer to the corresponding parts of the previous embodiments, and are not described herein again.
After the target associated data is obtained, a target license plate number and the target fueling card account can be obtained, and after the target fueling card account is obtained, whether the target fueling card account exists in the candidate data or not can be judged.
In some embodiments, the candidate data may be stored in a preset database, and the target fueling card account is used as a retrieval condition to search in the preset database. If the target fueling card account is found in the preset database, executing step 250; if the target fueling card account is not found in the preset database, go to step 240.
And 240, processing the target associated data according to the target license plate number.
In general, the target fueling card account is determined according to payment information, and omission does not occur, so that if the target fueling card account does not exist in the candidate data, which indicates that no associated data corresponding to the target fueling card account has occurred before, the target associated data is further processed according to the target license plate number.
Specifically, it may be determined whether the target license plate number exists in the candidate data; if the target license plate number exists in the candidate data, storing the target associated data as temporary data; and if the target license plate number does not exist in the candidate data, storing the target associated data as the candidate data.
When the candidate data does not have the target license plate number, the correctness of the target associated data cannot be continuously confirmed, and therefore the target associated data can be stored as the candidate data. And when the candidate data has the target license plate number, indicating that the association may have errors, and storing the target association data as temporary data for subsequent use.
And step 250, determining the correctness of the target associated data according to the target times of the target associated data appearing in the candidate data.
When the target fueling card account exists in the candidate data, the target associated data may be correct, indicating that the target fueling card has a previously associated license plate number. And defining the times of occurrence of the target associated data in the candidate data, so that the correctness of the target associated data can be determined according to the target times.
Specifically, the number of times of occurrence of the target associated data in the candidate data may be obtained as a target number of times; judging whether the target times are greater than or equal to preset times; if the target times are larger than or equal to the preset times, determining that the target associated data are correct; and if the target times are less than the preset times, determining that the target associated data are incorrect.
In some embodiments, the occurrence frequency of each piece of associated data may be correspondingly recorded in the candidate data, so that when the target associated data is found in the candidate data, the corresponding target frequency may be obtained.
It is understood that the preset number of times may be set as needed, and is not particularly limited herein. In the embodiment of the present application, the preset number of times may be set to 1, that is, as long as the target related data exists in the candidate data, the target related data may be considered to be correct.
The principle is that when the license plate number of the vehicle appearing in a gas station is associated with a fueling card account, the license plate number of the vehicle appearing in another gas station is also associated with the fueling card account. Assuming that there is a gas station X, and a gas station Y, where the gas station X associates the license plate number A with the fueling card account a, the gas station X may also have the license plate number B, and the license plate number C, and it cannot be determined whether the association between the license plate number A and the fueling card account a is correct.
The possibility of the license plate number B being close to 0 also appears at the gas station Y when the gas station Y associates the license plate number a with the fueling card account a, or the possibility of the license plate number C being close to 0 also appears at the gas station X when the gas station X associates the license plate number a with the fueling card account a again at another time at the gas station X. Therefore, if the associated data of the license plate number A and the fueling card account a appears again or the appearing frequency is greater than the preset frequency, the associated data can be confirmed to be correct. I.e. multiple occurrences of the associated data in different times and spaces, may be considered correct. Due to the fact that the probability of the license plate number A, the license plate number B, the license plate number C and the oiling card account a appearing for many times is extremely low at different times or in different spaces, the correctness of the target associated data is confirmed in the mode, and the accuracy of the obtained conclusion is high.
According to the associated data processing method provided by the embodiment of the application, after target associated data and candidate data are obtained, a target oiling card account in the target associated data can be extracted, and whether the target oiling card account exists in the candidate data or not is judged; if the target fueling card account does not exist, processing the target associated data according to the target license plate number; and if the target fueling card account exists, determining the correctness of the target associated data according to the target times of the target associated data appearing in the candidate data. By comparing the target times with the preset times, the correctness of the target associated data is verified, and the accuracy of the obtained target associated data can be effectively improved.
Referring to fig. 3, a related data processing method is provided in another embodiment of the present application, and a process of correcting target related data is mainly described on the basis of the foregoing embodiment.
And step 320, acquiring candidate data, wherein the candidate data comprises the related data of the license plate number and the fueling card account which appear at different time and/or in different space.
And 330, determining the correctness of the target associated data according to the candidate data to obtain correct target associated data.
The corresponding parts of the foregoing embodiments can be referred to in steps 310 to 330, which are not described herein again.
Upon determining that the target association data is incorrect, an unassociated license plate number may be obtained. It will be appreciated that there may be multiple vehicles present in a gas station at the same time, and that some license plates may not be associated with a fuel card account when associating the license plate number with the fuel card account. The license plate number of the part which is not related to the oiling card account can be stored in a certain fixed position, and the unassociated license plate number can be obtained by accessing the fixed position.
And 350, associating the unassociated license plate number with the target fueling card account to obtain first associated data.
When the unassociated license plate number is obtained, the unassociated license plate number can be associated with the target fueling card account one by one to obtain first associated data. For example, if there are 3 unassociated license plate numbers, namely, license plate a, license plate B and license plate C, the license plate a is associated with the target fueling card account to obtain first associated data, the license plate B is associated with the target fueling card account to obtain second first associated data, and the license plate C is associated with the target fueling card account to obtain third first associated data.
Defining the first times as the times of the first associated data appearing in the candidate data, after the first associated data is obtained, searching the first associated data in the candidate data, and obtaining the corresponding times as the first times. Judging whether the first time is greater than or equal to a preset time; if the first number is greater than or equal to the preset number, go to step 370; if the first time is less than the preset time, go to step 380. The preset times can be set according to actual needs, and are not specifically limited herein.
In some embodiments, when the preset number of times is set to 1, determining whether the first associated data exists in the candidate data; if the first association data exists, go to step 370; if the first association data does not exist, go to step 380.
In other embodiments, when the preset number is set to a value greater than 1, it may be determined whether the first associated data exists in the candidate data; if the first associated data exists, acquiring a first frequency of the first associated data appearing in the candidate data, and then judging whether the first frequency is greater than or equal to the preset frequency; if the first number is greater than or equal to the preset number, go to step 370; if the first time is less than the preset time, go to step 380.
If the number of times that the first associated data appears in the candidate data is greater than or equal to the preset number of times, the first associated data can be considered to be correct, and therefore the target associated data can be corrected into the first associated data. The target fueling card account is associated with the unassociated license plate number, association rate can be improved, if the first associated data are determined to be correct, the target associated data are corrected according to the correct first associated data, and accuracy of the target associated data is improved.
If the number of times that the first associated data appears in the candidate data is less than the preset number of times, the obtained first associated data is considered to be incorrect, and the target associated data can be continuously corrected according to temporary data. Specifically, referring to fig. 4, the process may further include the following steps.
And 381, extracting the license plate number in the temporary data.
In the temporary data, the currently acquired unconfirmed associated data is obtained, that is, the associated data in the temporary data and the target associated data are obtained in the same time period, and at this time, the target associated data is incorrect, which indicates that the license plate number associated with the target fueling card account may be wrongly associated as other associated data. Thus, the license plate number in the temporary data can be extracted, and an attempt is continuously made to find a target license plate number that is correctly associated with the target fueling card account.
After the license plate number is extracted, the extracted license plate number can be associated with a target fueling card account one by one to obtain second associated data. For example, the extracted license plate number includes a license plate D and a license plate E, so that the target fueling card account can be associated with the license plate D and the license plate E respectively to obtain two second associated data.
The second frequency is the frequency of the second associated data appearing in the candidate data, after the second associated data is obtained, the second associated data can be searched in the candidate data, and the corresponding frequency is obtained as the second frequency. Judging whether the second time is greater than or equal to a preset time; if the second number is greater than or equal to the preset number, go to step 384; if the second number is less than the preset number, execute step 385. The preset times can be set according to actual needs, and are not specifically limited herein. When the predetermined number of times is set to 1 or a value greater than 1, the corresponding determination process is similar to that in the step 360, and may be referred to each other.
If the number of times that the second associated data appears in the candidate data is greater than or equal to the preset number of times, the second associated data can be considered to be correct, and therefore the target associated data can be corrected into the second associated data. And correcting the target associated data according to the correct second associated data, so that the accuracy of the target associated data is improved.
If the number of times that the second associated data appears in the candidate data is less than the preset number of times, it indicates that the second associated data is incorrect, it indicates that the target associated data has not appeared before, and it may be associated data appearing for the first time, and the target associated data may be stored as temporary data for subsequent use. The temporary data may be converted into the candidate data at preset time intervals for subsequent use.
According to the associated data processing method provided by the embodiment of the application, the unassociated license plate number is associated with the target fueling card account to obtain first associated data; verifying the correctness of the first associated data according to the candidate data, and correcting the target associated data when the first associated data is correct; and when the first associated data is incorrect, matching the license plate number in the temporary data with the target fueling card account to obtain second associated data, and when the second associated data is correct, correcting the target associated data. The target fueling card is matched with the license plate numbers which are not related and the license plate numbers in the temporary data for multiple times to obtain the first related data or the second related data, so that the association rate of the related license plate numbers and the fueling card account can be improved, and when the first related data or the second related data are correct, the target related data are corrected based on the correct first related data or the correct second related data, so that the accuracy of the target related data is ensured.
Referring to fig. 5, an associated data processing apparatus 400, which can be applied to an electronic device, is provided in an embodiment of the present application, where the associated data processing apparatus 400 includes a first obtaining module 410, a second obtaining module 420, and a determining module 430. The first obtaining module 410 is configured to obtain target associated data, where the target associated data includes a target license plate number and a target fueling card account having an association relationship; the second obtaining module 420 is configured to obtain candidate data, where the candidate data includes associated data of license plate numbers and fueling card accounts that appear at different times and/or in different spaces; the determining module 430 is configured to determine correctness of the target related data according to the candidate data, so as to obtain correct target related data.
Further, the associated data processing apparatus 400 further includes a correcting module, configured to correct the target associated data according to temporary data when it is determined that the target associated data is incorrect, where the temporary data includes currently acquired unconfirmed associated data.
Further, the correction module is also used for acquiring unassociated license plate numbers; associating the unassociated license plate number with the target fueling card account to obtain first associated data; judging whether the first time of the first associated data in the candidate data is greater than or equal to a preset time or not; if the first time is greater than or equal to the preset times, correcting the target associated data into the first associated data; and if the first time is less than the preset times, correcting the target associated data according to the temporary data and the candidate data.
Further, the correction module is also used for extracting the license plate number in the temporary data; associating the extracted license plate number with the target fueling card account to obtain second associated data; judging whether the second times of the second associated data in the candidate data are greater than or equal to a preset number of times; if the second time is greater than or equal to the preset times, correcting the target associated data into second associated data; and if the second time is less than the preset times, storing the target associated data as temporary data.
Further, the determining module 430 is further configured to determine whether the target fueling card account exists in the candidate data; if the target oiling card account exists in the candidate data, determining the correctness of the target associated data according to the target times of the target associated data appearing in the candidate data; and if the target fueling card account does not exist in the candidate data, processing the target associated data according to the target license plate number.
Further, the determining module 430 is further configured to obtain, in the candidate data, the number of times that the target associated data appears is the target number of times; judging whether the target times are greater than or equal to preset times; if the target times are larger than or equal to the preset times, determining that the target associated data are correct; and if the target times are less than the preset times, determining that the target associated data are incorrect.
Further, the determining module 430 is further configured to determine whether the target license plate number exists in the candidate data; if the target license plate number exists in the candidate data, storing the target associated data as temporary data; and if the target license plate number does not exist in the candidate data, storing the target associated data as the candidate data.
Further, the associated data processing apparatus 400 further includes a conversion module, configured to convert the temporary data into the candidate data according to a preset time interval.
The associated data processing device provided by the embodiment of the application acquires target associated data, wherein the target associated data comprises a target license plate number and a target fueling card account which have an association relationship; acquiring candidate data, wherein the candidate data comprises associated data of license plate numbers and fueling card accounts which appear at different time and/or in different spaces; and determining the correctness of the target associated data according to the candidate data. After the target associated data is acquired, the correctness of the target associated data is verified through the candidate data so as to acquire the correct target associated data, and the accuracy of the acquired target associated data can be effectively improved.
It should be noted that, as will be clear to those skilled in the art, for convenience and brevity of description, the specific working process of the above-described apparatus may refer to the corresponding process in the foregoing method embodiment, and is not described herein again.
Referring to fig. 6, an embodiment of the present application provides a block diagram of an electronic device 500, where the electronic device 500 includes a processor 510, a memory 520, and one or more applications, where the one or more applications are stored in the memory 520 and configured to be executed by the one or more processors 510, and the one or more programs are configured to perform the above-mentioned method for associated data processing.
The electronic device 500 may be a terminal device capable of running an application, such as a smart phone or a tablet computer, or may be a server. The electronic device 500 in the present application may include one or more of the following components: a processor 510, a memory 520, and one or more applications, wherein the one or more applications may be stored in the memory 520 and configured to be executed by the one or more processors 510, the one or more programs configured to perform a method as described in the aforementioned method embodiments.
Processor 510 may include one or more processing cores. The processor 510 interfaces with various components throughout the electronic device 500 using various interfaces and circuitry to perform various functions of the electronic device 500 and process data by executing or executing instructions, programs, code sets, or instruction sets stored in the memory 520 and invoking data stored in the memory 520. Alternatively, the processor 510 may be implemented in hardware using at least one of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), and Programmable Logic Array (PLA). The processor 510 may integrate one or more of a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), a modem, and the like. Wherein, the CPU mainly processes an operating system, a user interface, an application program and the like; the GPU is used for rendering and drawing display content; the modem is used to handle wireless communications. It is understood that the modem may not be integrated into the processor 510, but may be implemented by a communication chip.
The Memory 520 may include a Random Access Memory (RAM) or a Read-Only Memory (Read-Only Memory). The memory 520 may be used to store instructions, programs, code sets, or instruction sets. The memory 520 may include a stored program area and a stored data area, wherein the stored program area may store instructions for implementing an operating system, instructions for implementing at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing various method embodiments described below, and the like. The data storage area may also store data created during use by the electronic device 500 (e.g., phone books, audio-visual data, chat log data), and so forth.
The electronic equipment provided by the embodiment of the application acquires target associated data, wherein the target associated data comprises a target license plate number and a target oiling card account which have an association relationship; acquiring candidate data, wherein the candidate data comprises associated data of license plate numbers and fueling card accounts which appear at different time and/or in different spaces; and determining the correctness of the target associated data according to the candidate data. After the target associated data is acquired, the correctness of the target associated data is verified through the candidate data so as to acquire the correct target associated data, and the accuracy of the acquired target associated data can be effectively improved.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While the preferred embodiments of the present application have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all alterations and modifications as fall within the scope of the application.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the spirit and scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include such modifications and variations as well.
Claims (11)
1. A method of associative data processing, the method comprising:
acquiring target associated data, wherein the target associated data comprises a target license plate number and a target fueling card account which have an association relation;
acquiring candidate data, wherein the candidate data comprises associated data between license plate numbers and fuel card accounts which appear at different times and/or in different spaces;
and determining the correctness of the target associated data according to the candidate data to obtain the correct target associated data.
2. The method of claim 1, further comprising:
and when the target associated data is determined to be incorrect, correcting the target associated data according to temporary data, wherein the temporary data comprises the currently acquired unconfirmed associated data.
3. The method of claim 2, wherein modifying the target associated data based on the temporal data comprises:
obtaining an unassociated license plate number;
associating the unassociated license plate number with the target fueling card account to obtain first associated data;
judging whether the first time of the first associated data in the candidate data is greater than or equal to a preset time or not;
if the first time is greater than or equal to the preset times, correcting the target associated data into the first associated data;
and if the first time is less than the preset times, correcting the target associated data according to the temporary data and the candidate data.
4. The method of claim 3, wherein said modifying said target-associated data based on said temporal data and said candidate data comprises:
extracting the license plate number in the temporary data;
associating the extracted license plate number with the target fueling card account to obtain second associated data;
judging whether the second times of the second associated data in the candidate data are greater than or equal to a preset number of times;
if the second time is greater than or equal to the preset times, correcting the target associated data into second associated data;
and if the second time is less than the preset times, storing the target associated data as temporary data.
5. The method of claim 1, wherein the determining the correctness of the target associated data according to the candidate data comprises:
judging whether the target fueling card account exists in the candidate data or not;
if the target oiling card account exists in the candidate data, determining the correctness of the target associated data according to the target times of the target associated data appearing in the candidate data;
and if the target fueling card account does not exist in the candidate data, processing the target associated data according to the target license plate number.
6. The method of claim 5, wherein determining the correctness of the target associated data according to the target times of the target associated data appearing in the candidate data comprises:
acquiring the frequency of the target associated data in the candidate data as the target frequency;
judging whether the target times are greater than or equal to preset times;
if the target times are larger than or equal to the preset times, determining that the target associated data are correct;
and if the target times are less than the preset times, determining that the target associated data are incorrect.
7. The method of claim 5, wherein the processing the target associated data according to the target license plate number comprises:
judging whether the target license plate number exists in the candidate data or not;
if the target license plate number exists in the candidate data, storing the target associated data as temporary data;
and if the target license plate number does not exist in the candidate data, storing the target associated data as the candidate data.
8. The method of any one of claims 2, 3, 4, or 7, further comprising:
and converting the temporary data into the candidate data according to a preset time interval.
9. An associated data processing apparatus, characterized in that the apparatus comprises:
the first acquisition module is used for acquiring target associated data, wherein the target associated data comprises a target license plate number and a target fueling card account which have an association relation;
the second acquisition module is used for acquiring candidate data, wherein the candidate data comprises the associated data of the license plate number and the fueling card account which appear at different time and/or in different space;
and the determining module is used for determining the correctness of the target associated data according to the candidate data to obtain the correct target associated data.
10. An electronic device, characterized in that the electronic device comprises:
one or more processors;
a memory electrically connected with the one or more processors;
one or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the one or more processors, the one or more applications configured to perform the method of any of claims 1-8.
11. A computer-readable storage medium, having stored thereon program code that can be invoked by a processor to perform the method according to any one of claims 1 to 8.
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