CN115394002A - Data processing method and device - Google Patents

Data processing method and device Download PDF

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CN115394002A
CN115394002A CN202211024193.5A CN202211024193A CN115394002A CN 115394002 A CN115394002 A CN 115394002A CN 202211024193 A CN202211024193 A CN 202211024193A CN 115394002 A CN115394002 A CN 115394002A
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queuing
user
sequence
users
information
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周庆梅
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Bank of China Ltd
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    • G—PHYSICS
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    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/02—Banking, e.g. interest calculation or account maintenance
    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
    • G07C11/00—Arrangements, systems or apparatus for checking, e.g. the occurrence of a condition, not provided for elsewhere
    • G07C2011/04—Arrangements, systems or apparatus for checking, e.g. the occurrence of a condition, not provided for elsewhere related to queuing systems

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Abstract

The application discloses a data processing method and a data processing device, which can be applied to the field of artificial intelligence, the field of big data or the field of finance, and can firstly obtain a current queuing sequence, wherein the current queuing sequence comprises N queuing users who are queuing, a pending queuing sequence is obtained if the number of the queuing users in the current queuing sequence is changed, the pending queuing sequence comprises M queuing users, M is larger than N or smaller than N, the pending queuing sequence is further subjected to sequencing optimization according to queuing information of the M queuing users to obtain an optimized queuing sequence, and finally the user to be called is determined from the M queuing users according to the optimized queuing sequence. The sequencing optimization is carried out based on the queuing information of the M queuing users, so that the optimized queuing sequence is obtained based on global optimization processing, and then the user to be called is determined from the M queuing users according to the optimized queuing sequence, and the user to be called can be called when the number is called next time, thereby improving the processing efficiency of the service.

Description

Data processing method and device
Technical Field
The present application relates to the field of data processing technologies, and in particular, to a data processing method and apparatus.
Background
In daily life, a user queues up to handle business after handling business at a bank outlet and needing to take a number. Generally, when a user reaches a bank outlet, the user can reserve business for transaction and take a number, and the number taker prints a number taking receipt for the user and displays the number of people waiting in front, the business transacted by the user and other information.
In the related technology, the business service processing is directly provided for each queuing user according to the number taking sequence taken after the user arrives at the bank outlet, however, the processing mode is too rigid, the user experience is poor, and the business processing efficiency of the bank outlet is low. For example, when the transaction value is inconsistent with the waiting time, the user experience is poor, and accordingly, the satisfaction degree of the business service of the bank outlets is greatly reduced.
Disclosure of Invention
In order to solve the technical problem, the application provides a data processing method and device, which can perform global optimization processing of a number calling sequence according to queuing information of queuing users, so as to improve processing efficiency of related services and user experience.
The embodiment of the application discloses the following technical scheme:
in one aspect, an embodiment of the present application provides a data processing method, where the method includes:
acquiring a current queuing sequence; the current queuing sequence comprises N queuing users, wherein N is an integer greater than 1;
when the number of queuing users in the current queuing sequence is changed, determining the changed current queuing sequence as a pending queuing sequence; the pending queuing sequence comprises M queuing users, and M is greater than N or less than N; m is an integer greater than 1;
sequencing and optimizing the to-be-queued sequence according to the queuing information of the M queuing users to obtain an optimized queuing sequence;
and determining a user to be called from the M queuing users according to the optimized queuing sequence.
In a possible implementation manner, the performing order optimization on the to-be-queued sequence according to the queuing information of the M queued users to obtain an optimized queuing sequence includes:
for the M queuing users in the queue to be determined, determining optimized queuing information corresponding to each queuing user according to the initial queuing information of each queuing user, the service pre-estimation transaction duration information of each queuing user and the user information of each queuing user;
and according to the optimized queuing information, performing sequencing optimization on the M queuing users according to an optimized queuing sequence to obtain the optimized queuing sequence.
In a possible implementation manner, the optimizing queuing information includes predicting a queuing time, and the method further includes:
and displaying the estimated queuing time corresponding to the M queuing users.
In a possible implementation manner, the initial ranking information of each queued user is determined by the following method:
and generating the initial queuing information according to the number taking operation time of each queuing user on the initial number taking equipment.
In a possible implementation manner, the service pre-estimated transaction duration information of each queued user is determined by the following method:
acquiring a target service type input by each queuing user through the initial number taking equipment;
acquiring a mapping relation between a pre-configured service type and service pre-estimation handling time;
and determining the service pre-estimation transaction duration corresponding to the target service type as the service pre-estimation transaction duration information of each queuing user according to the mapping relation.
In a possible implementation manner, the performing order optimization on the to-be-queued sequence according to the queuing information of the M queued users to obtain an optimized queuing sequence includes:
and sequencing and optimizing the to-be-queued sequence according to the queuing information of the M queuing users by using a pre-trained intelligent sequencing model to obtain the optimized queuing sequence.
In a possible implementation manner, the determining a user to be called from the M queued users according to the optimized queuing sequence includes:
and determining the queuing user ranked at the first position in the optimized queuing sequence as the user to be called.
In one possible implementation, the method further includes:
and calling the user to be called when the next number calling is carried out.
On the other hand, an embodiment of the present application provides a data processing apparatus, where the apparatus includes an obtaining unit, a determining unit, and an optimizing unit:
the acquiring unit is used for acquiring the current queuing sequence; the current queuing sequence comprises N queuing users, wherein N is an integer greater than 1;
the determining unit is used for determining the changed current queuing sequence as a pending queuing sequence when the number of queuing users in the current queuing sequence is changed; the pending queuing sequence comprises M queuing users, and M is greater than N or smaller than N; m is an integer greater than 1;
the optimizing unit is used for carrying out sequencing optimization on the queuing sequences to be determined according to the queuing information of the M queuing users to obtain optimized queuing sequences;
and the determining unit is also used for determining a user to be called from the M queued users according to the optimized queuing sequence.
In a possible implementation manner, the optimization unit is further configured to:
for the M queuing users in the queue to be determined, determining optimized queuing information corresponding to each queuing user according to the initial queuing information of each queuing user, the service pre-estimation transaction duration information of each queuing user and the user information of each queuing user;
and according to the optimized queuing information, performing sequencing optimization on the M queuing users according to an optimized queuing sequence to obtain the optimized queuing sequence.
In a possible implementation manner, the optimizing the queuing information includes estimating a queuing time, and the apparatus further includes a display unit:
and the display unit is used for displaying the estimated queuing time corresponding to the M queuing users.
In a possible implementation manner, the initial ranking information of each queued user is determined by the following method:
and generating the initial queuing information according to the number taking operation time of each queuing user on the initial number taking equipment.
In a possible implementation manner, the service pre-estimated transaction duration information of each queued user is determined by the following method:
acquiring a target service type input by each queuing user through the initial number taking equipment;
acquiring a mapping relation between a pre-configured service type and service pre-estimation handling time;
and determining the service pre-estimation transaction duration corresponding to the target service type as the service pre-estimation transaction duration information of each queuing user according to the mapping relation.
In a possible implementation manner, the optimization unit is further configured to:
and sequencing and optimizing the to-be-queued sequence according to the queuing information of the M queuing users by using a pre-trained intelligent sequencing model to obtain the optimized queuing sequence.
In a possible implementation manner, the determining unit is further configured to:
and determining the queuing user ranked at the first position in the optimized queuing sequence as the user to be called.
In one possible implementation, the apparatus further includes a calling unit:
and the calling unit is used for calling the user to be called when the next number calling is carried out.
According to the technical scheme, the current queuing sequence can be obtained at first, the current queuing sequence comprises N queuing users which are queuing, if the number of the queuing users in the current queuing sequence is changed, the changed queuing sequence is determined to be a queuing sequence to be determined, the queuing sequence to be determined comprises M queuing users, wherein M is larger than N or smaller than N, the queuing sequence to be determined is further subjected to sequencing optimization according to the queuing information of the M queuing users to obtain an optimized queuing sequence, and finally the user to be called is determined from the M queuing users according to the optimized queuing sequence. It can be seen that, for a queuing scene, when the number of queuing users in the current queuing sequence changes, the queuing sequence to be scheduled can be sequenced and optimized according to the queuing information of the M queuing users to obtain an optimized queuing sequence, because the sequencing optimization is performed based on the queuing information of the M queuing users, the optimized queuing sequence is obtained based on global optimization processing, and then the user to be called is determined from the M queuing users according to the optimized queuing sequence, and the user to be called can be called when calling the number next time. Compared with the mode that the number is sequentially called according to the initial queuing sequence in the related technology, the method and the device can perform global optimization processing of the queuing sequence according to the queuing information of the queuing users, and further improve the processing efficiency of related services and user experience.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a flowchart of a data processing method according to an embodiment of the present application;
fig. 2 is a structural diagram of a data processing apparatus according to an embodiment of the present application.
Detailed Description
In order to make those skilled in the art better understand the technical solutions of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
In daily life, a user queues up to handle business after handling business at a bank outlet and needing to take a number. Generally, when a user reaches a bank outlet, the user can reserve business for transaction and take a number, and the number taker prints a number taking receipt for the user and displays the number of people waiting in front, the business transacted by the user and other information.
In the related technology, the business service processing is directly provided for each queuing user according to the number taking sequence taken by the user after the user arrives at the banking outlet, however, the processing mode is too rigid, the user experience is poor, and the business processing efficiency of the banking outlet is low. For example, when the transaction value is inconsistent with the waiting time, the user experience is poor, and accordingly, the satisfaction degree of the business service of the bank outlets is greatly reduced.
In order to solve the technical problem, the application provides a data processing method and device, which can perform global optimization processing of a number calling sequence according to queuing information of queuing users, so as to improve processing efficiency of related services and user experience.
The data processing method provided by the embodiment of the application can be implemented by computer equipment, the computer equipment can be terminal equipment or a server, wherein the server can be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, and a cloud server providing cloud computing service. The terminal devices include, but are not limited to, mobile phones, computers, intelligent voice interaction devices, intelligent household appliances, vehicle-mounted terminals, and the like. The terminal device and the server may be directly or indirectly connected through wired or wireless communication, which is not limited in this application.
It should be noted that the data processing method and apparatus provided by the present application can be used in the field of artificial intelligence, the field of big data, or the field of finance. The foregoing is merely an example, and does not limit the application field of the data processing method and apparatus provided in the present application.
The following examples are intended to illustrate in particular:
fig. 1 is a flowchart of a data processing method provided in an embodiment of the present application, and in the embodiment, a terminal device is taken as an example of the foregoing computer device, and the method includes S101 to S104:
s101: and acquiring the current queuing sequence.
S102: and when the number of queuing users in the current queuing sequence is changed, determining the changed current queuing sequence as a pending queuing sequence.
For a number taking queuing scenario, such as a typical number taking queuing scenario in which a number is taken and queued when a bank outlet handles a service, and a service is handled after waiting for a number to be called, a current queuing sequence may be first obtained, where the current queuing sequence includes N queued users, and N is an integer greater than 1. That is, there are currently N queued users in queue.
And further, if the number of queuing users in the current queuing sequence is changed, determining the changed current queuing sequence as a pending queuing sequence, wherein the pending queuing sequence comprises M queuing users, M is greater than N or smaller than N, and M is an integer greater than 1. For example, when a new queuing user is added, the number of queuing users in the current queuing sequence will change.
S103: and performing sequencing optimization on the queuing sequence to be scheduled according to the queuing information of the M queuing users to obtain an optimized queuing sequence.
Because the services to be handled by each queuing user may be different and correspondingly, the time spent for handling different services is different, in order to avoid poor user experience caused by the fact that the value of the services to be handled is not consistent with the waiting time, the queuing sequence to be handled can be sequenced and optimized according to the queuing information of the M queuing users, and then an optimized queuing sequence is obtained, so that a bank outlet can call the number according to the optimized queuing sequence when the number is called in the service processing. The queuing information is used for representing the queuing conditions related to the queuing users, and then the queuing information of the M queuing users is used for carrying out sequencing optimization processing, so that the optimized queuing sequence is obtained based on global optimization processing and has the global optimal characteristic, finally, the problem of poor user experience caused by the fact that the service value to be handled is not consistent with the waiting time can be avoided by calling according to the optimized queuing sequence, and the service processing efficiency can be improved.
In one possible implementation, S103 may include the following steps:
for M queuing users in a queue to be determined, determining optimized queuing information corresponding to each queuing user according to the initial queuing information of each queuing user, the service pre-estimated transaction duration information of each queuing user and the user information of each queuing user;
and according to the optimized queuing information, performing sequencing optimization on the M queuing users according to the optimized queuing sequence to obtain an optimized queuing sequence.
Therefore, the queuing information of each queuing user can comprise three dimensions of initial queuing information, service pre-estimation transaction duration information and user information.
First, information for the first dimension, i.e. initial ranking information for each queued user, may be determined as follows: and generating initial queuing information according to the number taking operation time of each queuing user on the initial number taking equipment. That is, the initial queuing information is generated according to the time for taking the number on the initial number taking device after the queuing user reaches the bank outlet, specifically, the initial queuing information can be generated according to the time for taking the number, and correspondingly, the initial queuing information of the M queuing users can reflect the sequence of the number taking operation of the M queuing users on the initial number taking device.
Secondly, for the information of the second dimension, that is, the service estimated transaction duration information of each queuing user, the information is used to represent the estimated transaction duration of the service to be transacted by each queuing user, and specifically, the service estimated transaction duration information of each queuing user is determined in the following manner:
acquiring a target service type input by each queuing user through initial number taking equipment;
acquiring a mapping relation between a pre-configured service type and service pre-estimation handling time;
and determining the service pre-estimation transaction duration corresponding to the target service type as the service pre-estimation transaction duration information of each queuing user according to the mapping relation.
Specifically, when the queuing user performs number taking operation through the initial number taking device, the number taking operation needs to input a target service type needing to be handled by the queuing user, and further obtains a mapping relation between a service type configured in advance and service estimated handling time, so that the service estimated handling time corresponding to the target service type is determined as the service estimated handling time information of the queuing user according to the mapping relation. The mapping relationship may be calibrated according to historical data, for example, data such as historical transaction time, historical transaction duration, queuing waiting duration of a user, service satisfaction of the user, and the like of each type of service of a bank outlet may be collected as a calibration data set, and then the service pre-estimation transaction duration corresponding to each type of service is calibrated according to the calibration data set, so as to obtain the mapping relationship. It can be understood that the initial network model can be further subjected to model training by using the calibration data set to obtain a service duration estimation model, and then the service estimation transaction duration information of each queuing user is output by using the target service type of each queuing user through the service duration estimation model.
Finally, the information for the third dimension, i.e. the user information, is used to represent the user characteristic information of the queued users, for example, the user information may include the user characteristic information of the age, the gender, and the like of the user.
Furthermore, the optimized queuing information of each queuing user can be determined according to the three-dimensional information of the initial queuing information, the service pre-estimated transaction duration information and the user information of each queuing user, and then the M queuing users can be sequenced and optimized according to the optimized queuing information and the optimized queuing sequence according to the optimized queuing information to obtain the optimized queuing sequence. The optimized queuing information is used for representing the queuing information optimized according to the information of three dimensions, and then sequencing optimization is carried out according to the optimized queuing sequence, namely, the queuing sequences of the M queuing users are reordered according to the optimized queuing information, so that an optimized queuing sequence is obtained.
Because M queuing users are queuing, in order to facilitate each queuing user to know queuing time in real time and improve user experience, in a possible implementation manner, the optimized queuing information can comprise estimated queuing time which is used for representing a result of estimating the time for which the queuing user still needs to queue, the result can be determined according to the queuing sequence of each queuing user in the optimized queuing sequence and the service estimated transaction time information of the queuing user arranged before the queuing user, and correspondingly, the estimated queuing time corresponding to the M queuing users can also be displayed.
The mode of how to display the estimated queuing time can be set according to the actual situation, and the method is not limited in this application. For example, the estimated queuing time corresponding to the M queuing users can be displayed through a display screen of a bank outlet hall, the estimated queuing time of each queuing user can be sent to the terminal equipment of each queuing user through short messages and the like, and the estimated queuing time is pushed to each queuing user based on the estimated queuing time.
In one possible implementation, the optimized queuing sequence may also be determined by:
and sequencing and optimizing the queue-waiting sequence according to the queuing information of the M queuing users by using a pre-trained intelligent sequencing model to obtain an optimized queue-waiting sequence.
The intelligent sequencing model can perform sequencing optimization on the queuing sequence to be sequenced according to the queuing information of M queuing users in the queuing sequence to be sequenced, and output an optimized queuing sequence. It should be noted that the intelligent ranking model may be obtained by performing model training on the initial ranking model, and specifically, data such as actual waiting time for business transaction, actual waiting time, and user satisfaction of a bank outlet may be collected as a training data set, model training is performed on the initial ranking model, actual waiting time, user satisfaction, and the like corresponding to the output optimized queuing sequence are collected as an adjustment training data set, and the initial ranking model is continuously trained according to the adjustment training data set to obtain the intelligent ranking model.
In one possible implementation, the sum of the user satisfaction of the M queued users is maximized under the optimized queuing sequence. Namely, the number is called according to the optimized queuing sequence, and the business is transacted for M queuing users, so that the sum of the user satisfaction degrees of the M queuing users is the maximum.
S104: and determining the number-to-be-called user from the M queuing users according to the optimized queuing sequence.
After the optimized queuing sequence is determined, the number-to-be-called user can be determined from the M queuing users according to the optimized queuing sequence.
It should be noted that, the number of the number to be called may be selected and set according to actual situations, and the present application is not limited to this. For example, the number of the users to be called can be set according to the number of service handling windows of the bank outlets. To facilitate understanding, the embodiments of the present application provide the following examples:
in a possible implementation manner, the queuing user ranked first in the optimized queuing sequence is determined as the user to be called, and then when the next number calling is performed, the user to be called can be called, so that the service can be handled for the user to be called.
According to the technical scheme, the current queuing sequence can be obtained at first, the current queuing sequence comprises N queuing users which are queuing, if the number of the queuing users in the current queuing sequence is changed, the changed queuing sequence is determined to be a queuing sequence to be determined, the queuing sequence to be determined comprises M queuing users, wherein M is larger than N or smaller than N, the queuing sequence to be determined is further subjected to sequencing optimization according to the queuing information of the M queuing users to obtain an optimized queuing sequence, and finally the user to be called is determined from the M queuing users according to the optimized queuing sequence. It can be seen that, for a queuing scene, when the number of queuing users in the current queuing sequence changes, the queuing sequence to be scheduled can be sequenced and optimized according to the queuing information of the M queuing users to obtain an optimized queuing sequence, because the sequencing optimization is performed based on the queuing information of the M queuing users, the optimized queuing sequence is obtained based on global optimization processing, and then the user to be called is determined from the M queuing users according to the optimized queuing sequence, and the user to be called can be called when calling the number next time. Compared with the mode that the number is sequentially called according to the initial queuing sequence in the related technology, the method and the device can perform global optimization processing of the queuing sequence according to the queuing information of the queuing users, and further improve the processing efficiency of related services and user experience.
Fig. 2 is a structural diagram of a data processing apparatus according to an embodiment of the present application, where the apparatus includes an obtaining unit 201, a determining unit 202, and an optimizing unit 203:
the acquiring unit 201 is configured to acquire a current queuing sequence; the current queuing sequence comprises N queuing users, wherein N is an integer greater than 1;
the determining unit 202 is configured to determine, when the number of queuing users in the current queuing sequence changes, the changed current queuing sequence as a pending queuing sequence; the pending queuing sequence comprises M queuing users, and M is greater than N or smaller than N; m is an integer greater than 1;
the optimizing unit 203 is configured to perform sequencing optimization on the to-be-queued sequence according to the queuing information of the M queued users, so as to obtain an optimized queuing sequence;
the determining unit 202 is further configured to determine a user to be called from the M queued users according to the optimized queuing sequence.
In a possible implementation manner, the optimization unit is further configured to:
for the M queuing users in the queue to be determined, determining optimized queuing information corresponding to each queuing user according to the initial queuing information of each queuing user, the service pre-estimation transaction duration information of each queuing user and the user information of each queuing user;
and according to the optimized queuing information, performing sequencing optimization on the M queuing users according to an optimized queuing sequence to obtain the optimized queuing sequence.
In a possible implementation manner, the optimizing the queuing information includes estimating a queuing time, and the apparatus further includes a display unit:
and the display unit is used for displaying the estimated queuing time corresponding to the M queuing users.
In a possible implementation manner, the initial ranking information of each queued user is determined by the following method:
and generating the initial queuing information according to the number taking operation time of each queuing user on the initial number taking equipment.
In a possible implementation manner, the service estimated transaction duration information of each queuing user is determined by the following manner:
acquiring a target service type input by each queuing user through the initial number taking equipment;
acquiring a mapping relation between a pre-configured service type and service pre-estimation handling time;
and determining the service pre-estimation transaction duration corresponding to the target service type as the service pre-estimation transaction duration information of each queuing user according to the mapping relation.
In a possible implementation manner, the optimization unit is further configured to:
and sequencing and optimizing the pending queuing sequence according to the queuing information of the M queuing users through a pre-trained intelligent sequencing model to obtain the optimized queuing sequence.
In a possible implementation manner, the determining unit is further configured to:
and determining the queuing user ranked at the first position in the optimized queuing sequence as the user to be called.
In one possible implementation, the apparatus further includes a calling unit:
and the calling unit is used for calling the user to be called when the next number calling is carried out.
According to the technical scheme, the current queuing sequence can be obtained at first, the current queuing sequence comprises N queuing users which are queuing, if the number of the queuing users in the current queuing sequence is changed, the changed queuing sequence is determined to be a queuing sequence to be determined, the queuing sequence to be determined comprises M queuing users, wherein M is larger than N or smaller than N, the queuing sequence to be determined is further subjected to sequencing optimization according to the queuing information of the M queuing users to obtain an optimized queuing sequence, and finally the user to be called is determined from the M queuing users according to the optimized queuing sequence. It can be seen that, for a queuing scene, when the number of queuing users in the current queuing sequence changes, the queuing sequence to be scheduled can be sequenced and optimized according to the queuing information of the M queuing users to obtain an optimized queuing sequence, because the sequencing optimization is performed based on the queuing information of the M queuing users, the optimized queuing sequence is obtained based on global optimization processing, and then the user to be called is determined from the M queuing users according to the optimized queuing sequence, and the user to be called can be called when calling the number next time. Compared with the mode that the number is sequentially called according to the initial queuing sequence in the related technology, the method and the device can perform global optimization processing of the queuing sequence according to the queuing information of the queuing users, and further improve the processing efficiency of related services and user experience.
For the device embodiment, since it basically corresponds to the method embodiment, reference may be made to the partial description of the method embodiment for relevant points. The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement without inventive effort.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrases "comprising one of 8230; \8230;" 8230; "does not exclude the presence of additional like elements in a process, method, article, or apparatus that comprises the element.
The data processing method and apparatus provided in the embodiments of the present application are described in detail above, and specific examples are applied herein to explain the principles and embodiments of the present application, and the description of the embodiments is only used to help understanding the method of the present application. Also, the method according to the present application may vary in the embodiments and the application range for a person skilled in the art.
In view of the foregoing, it is not intended that the present disclosure be limited to the specific embodiments disclosed, and that any modifications or alterations that may occur to those skilled in the art and which are within the scope of the disclosure are intended to be covered by the appended claims. Moreover, the present application can be further combined to provide more implementations on the basis of the implementations provided by the above aspects.

Claims (10)

1. A method of data processing, the method comprising:
acquiring a current queuing sequence; the current queuing sequence comprises N queuing users, wherein N is an integer greater than 1;
when the number of queuing users in the current queuing sequence is changed, determining the changed current queuing sequence as a pending queuing sequence; the pending queuing sequence comprises M queuing users, and M is greater than N or smaller than N; m is an integer greater than 1;
sequencing and optimizing the queue to be determined according to the queuing information of the M queuing users to obtain an optimized queuing sequence;
and determining the number-to-be-called user from the M queuing users according to the optimized queuing sequence.
2. The method according to claim 1, wherein the performing order optimization on the pending queuing sequence according to the queuing information of the M queued users to obtain an optimized queuing sequence comprises:
for the M queuing users in the queue to be determined, determining optimized queuing information corresponding to each queuing user according to the initial queuing information of each queuing user, the service pre-estimation transaction duration information of each queuing user and the user information of each queuing user;
and according to the optimized queuing information, performing sequencing optimization on the M queuing users according to an optimized queuing sequence to obtain the optimized queuing sequence.
3. The method of claim 2, wherein optimizing queuing information includes estimating a queuing duration, the method further comprising:
and displaying the estimated queuing time corresponding to the M queuing users.
4. The method of claim 2, wherein the initial ranking information for each queued user is determined by:
and generating the initial queuing information according to the number taking operation time of each queuing user on the initial number taking equipment.
5. The method of claim 4, wherein the pre-estimated transaction duration information for each queued user is determined by:
acquiring a target service type input by each queuing user through the initial number taking equipment;
acquiring a mapping relation between a pre-configured service type and service pre-estimation handling time;
and determining the service pre-estimation transaction duration corresponding to the target service type as the service pre-estimation transaction duration information of each queuing user according to the mapping relation.
6. The method according to any one of claims 1 to 5, wherein the sorting optimization of the pending queuing sequences according to the queuing information of the M queuing users to obtain an optimized queuing sequence comprises:
and sequencing and optimizing the pending queuing sequence according to the queuing information of the M queuing users through a pre-trained intelligent sequencing model to obtain the optimized queuing sequence.
7. The method according to any one of claims 1-5, wherein said determining a number-to-call user from said M queued users according to said optimized queuing sequence comprises:
and determining the queuing user ranked at the first position in the optimized queuing sequence as the user to be called.
8. The method of claim 7, further comprising:
and calling the user to be called when the next number calling is carried out.
9. A data processing apparatus, characterized in that the apparatus comprises an acquisition unit, a determination unit and an optimization unit:
the acquiring unit is used for acquiring the current queuing sequence; the current queuing sequence comprises N queuing users, wherein N is an integer greater than 1;
the determining unit is used for determining the changed current queuing sequence as a pending queuing sequence when the number of queuing users in the current queuing sequence is changed; the pending queuing sequence comprises M queuing users, and M is greater than N or smaller than N; m is an integer greater than 1;
the optimizing unit is used for carrying out sequencing optimization on the queuing sequences to be determined according to the queuing information of the M queuing users to obtain optimized queuing sequences;
and the determining unit is also used for determining a user to be called from the M queued users according to the optimized queuing sequence.
10. The apparatus of claim 9, wherein the optimization unit is further configured to:
for the M queuing users in the queue to be determined, determining optimized queuing information corresponding to each queuing user according to the initial queuing information of each queuing user, the service pre-estimation transaction duration information of each queuing user and the user information of each queuing user;
and according to the optimized queuing information, performing sequencing optimization on the M queuing users according to an optimized queuing sequence to obtain the optimized queuing sequence.
CN202211024193.5A 2022-08-24 2022-08-24 Data processing method and device Pending CN115394002A (en)

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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102779367A (en) * 2012-07-13 2012-11-14 南京信息工程大学 Scheduling method of queuing processing system and queuing machine for prediction of service processing time
CN108537941A (en) * 2018-03-30 2018-09-14 深圳市零度智控科技有限公司 Bank queuing management method and system, server and storage medium
CN109657980A (en) * 2018-12-20 2019-04-19 中国银行股份有限公司 A kind of site custom queueing dispatching method and system
CN112734185A (en) * 2020-12-30 2021-04-30 中国人寿保险股份有限公司上海数据中心 Intelligent queuing scheduling method
CN114120516A (en) * 2021-11-26 2022-03-01 中国农业银行股份有限公司重庆市分行 Business hall number calling sequence optimization method

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102779367A (en) * 2012-07-13 2012-11-14 南京信息工程大学 Scheduling method of queuing processing system and queuing machine for prediction of service processing time
CN108537941A (en) * 2018-03-30 2018-09-14 深圳市零度智控科技有限公司 Bank queuing management method and system, server and storage medium
CN109657980A (en) * 2018-12-20 2019-04-19 中国银行股份有限公司 A kind of site custom queueing dispatching method and system
CN112734185A (en) * 2020-12-30 2021-04-30 中国人寿保险股份有限公司上海数据中心 Intelligent queuing scheduling method
CN114120516A (en) * 2021-11-26 2022-03-01 中国农业银行股份有限公司重庆市分行 Business hall number calling sequence optimization method

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