Business prompt information generation method and device and electronic equipment

Abstract

The invention discloses a service prompt information generation method and device and electronic equipment. The method comprises the following steps: in response to a number taking instruction submitted by a target user at a first branch, determining waiting time required by the target user to handle business at the first branch, and obtaining first waiting time; determining predicted human traffic of M second websites in a target time period to obtain M traffic predicted values; obtaining waiting duration required by the target user to handle the service at each second branch, obtaining M second waiting duration, and determining M predicted waiting duration for the target user to go to each second branch to handle the service according to the M second waiting duration, the M traffic predicted values and the M target distances; and generating service prompt information sent to the target user according to the M predicted waiting durations and the first waiting duration. Through the method and the device, the problem of relatively low user business handling efficiency due to user shunting in a single network point through manual operation or a self-service machine in related technologies is solved.

Description

Technical Field

[0001] The present application relates to the field of big data, and in particular, to a method, device and electronic device for generating business prompt information. Background Art

[0002] With the rapid economic development and the increasing popularity of financial services, the user base of banks and other outlets is growing larger and larger. Due to the limited number of employees and counters in online stores, users often have to wait in line when handling business, especially during peak business hours. Long waiting times can easily lead to a poor user experience.

[0003] Therefore, it is very important to reduce the waiting time for users to handle business at outlets. Relevant technologies achieve user diversion by adopting service diversion or process diversion within a single outlet, but this method mainly relies on manual or self-service machines. When manpower or equipment are occupied, the business processing efficiency is still very low.

[0004] Currently, no effective solution has been proposed to address the problem of low efficiency in user business processing due to manual or self-service machine-based user diversion within a single branch in related technologies. Summary of the invention

[0005] The main purpose of the present application is to provide a method, device and electronic device for generating business prompt information to solve the problem of low efficiency of user business handling in the related art of performing user diversion within a single outlet through manual or self-service machines.

[0006] In order to achieve the above-mentioned purpose, according to one aspect of the present application, a method for generating service prompt information is provided. The method includes: responding to a number-taking instruction submitted by a target user at a first outlet, and determining the waiting time required for the target user to handle the service at the first outlet, and obtaining a first waiting time; determining the predicted flow of people at M second outlets within a target time period, and obtaining M flow prediction values, wherein the target time period is taken as the starting time by the target time, the target time is the time when the target user submits the number-taking instruction, and M is a positive integer; obtaining the waiting time required for the target user to handle the service at each second outlet, and obtaining M second waiting times, and determining the predicted waiting time for the target user to go to each second outlet to handle the service based on the M second waiting times, the M flow prediction values, and the M target distances, and obtaining M predicted waiting times; generating service prompt information sent to the target user based on the M predicted waiting times and the first waiting time.

[0007] Optionally, determining the waiting time required for the target user to handle a business at the first outlet, and obtaining the first waiting time includes: obtaining the user type of the historical user before the target user in the first outlet, and obtaining N first user types, where N is a positive integer; obtaining the business that each historical user needs to handle, and obtaining N first businesses, and determining the business handling time for each user based on the user type and the first business of each user, and obtaining N business handling times; adding the N business handling times to obtain the first waiting time.

[0008] Optionally, determining the predicted pedestrian flow of M second outlets within the target time period to obtain M traffic prediction values ​​includes: for each second outlet, obtaining environmental information and multiple historical pedestrian flows of the second outlet within the target time period, wherein the environmental information of the time period in which each historical pedestrian flow is located is the same as the environmental information of the second outlet; inputting the multiple historical pedestrian flows and environmental information into a traffic prediction model to obtain an initial prediction value for the second outlet; judging whether there is activity information for the second outlet within the target time period; if there is activity information, changing the initial prediction value according to the activity information to obtain the traffic prediction value for the second outlet; if there is no activity information, determining the initial prediction value as the traffic prediction value for the second outlet.

[0009] Optionally, the predicted waiting time for the target user to go to each second outlet to handle business is determined based on M second waiting times, M traffic prediction values ​​and M target distances, and the M predicted waiting times include: for each second outlet, calculating the time required for the target user to reach the second outlet according to the target distance to obtain a first time; calculating the new number of people at the second outlet according to the traffic prediction value and the first time; calculating the new waiting time based on the new number of people, and determining the predicted waiting time for the second outlet based on the new waiting time, the second waiting time and the first time.

[0010] Optionally, generating business prompt information to be sent to the target user based on M predicted waiting times and the first waiting time includes: determining whether there is a target waiting time that is less than the first waiting time among the M predicted waiting times; if there is at least one target waiting time, determining the second outlet to which the smallest target waiting time belongs as the target outlet, and generating first business prompt information based on the outlet information of the target outlet, wherein the first business prompt information is used to prompt the target user to go to the second outlet to handle business; if there is no target waiting time, obtaining a candidate waiting time with the smallest difference from the first waiting time; determining whether the difference between the candidate waiting time and the first waiting time is less than a target threshold; if the difference is less than or equal to the target threshold, determining the second outlet to which the candidate waiting time belongs as the target outlet, and generating first business prompt information based on the outlet information of the target outlet; if the difference is greater than the target threshold, generating business promotion information based on the business information in the first outlet, and generating second business prompt information based on the business promotion information, wherein the second business prompt information is used to promote business to the target user.

[0011] Optionally, after obtaining the first waiting time, the method also includes: determining whether the first waiting time is less than the preset waiting time; if the first waiting time is less than the preset waiting time, generating business promotion information based on the business information in the first outlet, and generating second business prompt information based on the business promotion information.

[0012] Optionally, after responding to the number-taking instruction submitted by the target user at the first outlet, the method also includes: obtaining the number of times the target user receives the first business prompt information within a historical time period to obtain a first number; determining the number of times the target user goes to each second outlet to handle business within the historical time period to obtain a second number; determining the promotion success rate of the target user based on the first number and the second number; when the promotion success rate is less than a preset success rate, generating business promotion information based on the business information in the first outlet, and generating second business prompt information based on the business promotion information.

[0013] In order to achieve the above-mentioned purpose, according to another aspect of the present application, a device for generating service prompt information is provided. The device includes: a first determination unit, which is used to respond to the number-taking instruction submitted by the target user at the first outlet, and determine the waiting time required for the target user to handle the service at the first outlet, and obtain the first waiting time; a second determination unit, which is used to determine the predicted flow of people at M second outlets in the target time period, and obtain M flow prediction values, wherein the target time period is taken as the starting time by the target time, the target time is the time when the target user submits the number-taking instruction, and M is a positive integer; a first acquisition unit, which is used to obtain the waiting time required for the target user to handle the service at each second outlet, and obtain M second waiting times, and determine the predicted waiting time for the target user to go to each second outlet to handle the service according to the M second waiting times, the M flow prediction values ​​and the M target distances, and obtain M predicted waiting times; a first generation unit, which is used to generate service prompt information sent to the target user according to the M predicted waiting times and the first waiting time.

[0014] In an embodiment of the present application, a method is adopted in which a target user responds to a number-taking instruction submitted by a first outlet, and the waiting time required for the target user to handle business at the first outlet is determined to obtain a first waiting time; the predicted flow of people at M second outlets within a target time period is determined to obtain M flow prediction values, wherein the target time period is started at a target time, the target time is the time when the target user submits a number-taking instruction, and M is a positive integer; the waiting time required for the target user to handle business at each second outlet is obtained to obtain M second waiting times, and the predicted waiting time for the target user to go to each second outlet to handle business is determined based on the M second waiting times, the M flow prediction values, and the M target distances to obtain M predicted waiting times; a signal to the target user is generated based on the M predicted waiting times and the first waiting time. The method of sending business reminder information to the target user is to determine the first waiting time of the target user at the first outlet according to the user type and the business type handled by the historical user, and at the same time use the prediction model to determine the predicted flow of people in multiple second outlets, and then calculate the second waiting time for handling business at each second outlet, and determine the predicted waiting time for each second outlet according to the second waiting time and the target distance from the target user to the second outlet, and finally generate the business reminder information sent to the target user by comparing the multiple predicted waiting times with the first waiting time, thereby solving the problem of low user business handling efficiency in a single outlet through manual or self-service machines in the related technology, thereby achieving the technical effect of improving user business handling efficiency and reducing user waiting time for business handling. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0016] Figure 1 A hardware structure block diagram of a computer terminal for implementing a method for generating business prompt information is shown;

[0017] Figure 2 is a flowchart of a method for generating business prompt information provided in Example 1 of the present application;

[0018] Figure 3 is a schematic diagram of a device for generating business prompt information provided in Example 2 of the present application;

[0019] Figure 4 It is a structural block diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0020] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0021] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0022] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0023] It should be noted that the method, device and electronic device for generating the business prompt information determined in the present disclosure can be used in field A, and can also be used in any field other than field A. The application field of the method, device and electronic device for generating the business prompt information determined in the present disclosure is not limited.

[0024] It should be noted that the collected information, user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) used in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of relevant data are in compliance with the relevant laws, regulations and standards of the relevant regions, necessary confidentiality measures are taken, and public order and good customs are not violated. Corresponding operation entrances are provided for users to choose to authorize use or refuse use. If the user chooses to refuse, the expert decision-making process is entered. For example, an interface is set between this system and relevant users or institutions. Before obtaining relevant information, it is necessary to send an acquisition request to the aforementioned user or institution through the interface, and obtain relevant information after receiving the consent information fed back by the aforementioned user or institution.

[0025] The embodiments or examples of the present disclosure are not exhaustive, but are only illustrative of some embodiments or examples, and are not intended to be specific limitations on the scope of protection of the present disclosure. In the absence of contradiction, each step in a certain embodiment or example can be implemented as an independent example, and the steps can be combined arbitrarily. For example, the scheme after removing some steps in a certain embodiment or example can also be implemented as an independent example, and the order of the steps in a certain embodiment or example can be arbitrarily exchanged. In addition, the optional methods or optional examples in a certain embodiment or example can be combined arbitrarily; in addition, the various embodiments or examples can be combined arbitrarily, for example, some or all steps of different embodiments or examples can be combined arbitrarily, and a certain embodiment or example can be combined arbitrarily with the optional methods or optional examples of other embodiments or examples.

[0026] For the convenience of description, some nouns or terms involved in the embodiments of the present application are explained below:

[0027] XGBoost: XGBoost (eXtreme Gradient Boosting, distributed gradient boosting library) is a gradient boosting tree model in ensemble learning. It can handle large-scale data sets and high-dimensional features, and has good generalization ability.

[0028] LSTM: LSTM (Long Short-Term Memory) is a long short-term memory neural network model used to process sequence data and time series data. LSTM is a special type of recurrent neural network that can better handle long-term dependencies and memory information.

[0029] Example 1

[0030] According to an embodiment of the present application, an embodiment of a method for generating business prompt information is also provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0031] The method embodiment provided in the first embodiment of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Figure 1 The hardware structure block diagram of a computer terminal for implementing a method for generating service prompt information is shown. Figure 1 As shown, the computer terminal 10 (or mobile device) may include one or more (102a, 102b, ..., 102n are used to illustrate) processors 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory 104 for storing data, and a transmission device 106 for communication functions. In addition, it may also include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of the BUS bus), a network interface, a power supply and / or a camera. It can be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the above electronic device. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations are shown.

[0032] It should be noted that the one or more processors 102 and / or other data processing circuits described above may generally be referred to herein as "data processing circuits". The data processing circuits may be embodied in whole or in part as software, hardware, firmware, or any other combination thereof. In addition, the data processing circuit may be a single independent processing module, or may be incorporated in whole or in part into any of the other components in the computer terminal 10 (or mobile device). As described in the embodiments of the present application, the data processing circuit acts as a processor control (e.g., selection of a variable resistor terminal path connected to an interface).

[0033] The memory 104 can be used to store software programs and modules of application software, such as program instructions / data storage devices corresponding to the method for generating business prompt information in the embodiment of the present application. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, that is, the method for generating business prompt information described above is realized. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the computer terminal 10 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0034] The transmission device 106 is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of the computer terminal 10. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0035] The display may be, for example, a touch screen liquid crystal display (LCD) that enables a user to interact with a user interface of the computer terminal 10 (or mobile device).

[0036] Under the above operating environment, this application provides Figure 2 The method for generating business prompt information shown. Figure 2 This is a flowchart of a method for generating business prompt information provided in Example 1 of the present application.

[0037] Step S101, responding to a number taking instruction submitted by a target user at a first outlet, and determining a waiting time required for the target user to handle a service at the first outlet, thereby obtaining a first waiting time.

[0038] Specifically, the executing entity of this embodiment can be a business processing system. During the process of generating business prompt information in the system, it will first receive the number-taking instruction submitted by the target user at the first branch and respond. The number-taking instruction can be the number-taking instruction submitted by the system after the target user arrives at the first branch, thereby completing the number-taking.

[0039] Optionally, after responding to the number-taking instruction submitted by the target user at the first outlet, the system's real-time data can be used to obtain user information and corresponding business information, such as user type, business type, etc., who submitted the number-taking instruction before the target user. The time required for each user before the target user to handle the business can be determined based on the user information and business information. The waiting time for the target user to handle the business at the first outlet is determined by adding the business handling time of each user before the target user, thereby obtaining the first waiting time.

[0040] For example, suppose user C handles business at Bank Z, and there are two users who handle business before user C. The first one is a young user who handles a deposit. The system estimates that the processing time for this user is 5 minutes based on the recorded historical information. The second one is an elderly user who handles a loan. The estimated processing time is 20 minutes. Therefore, the waiting time for user C to handle business at Bank Z is 25 minutes. In the case where the user waits for a long time, the system predicts the waiting time of other bank branches for the user and pushes reminder information to the user.

[0041] Step S102, determining the predicted flow of people at M second outlets within a target time period, and obtaining M flow prediction values, wherein the target time period is started at a target time, the target time is the time when the target user submits a number-taking instruction, and M is a positive integer.

[0042] Specifically, after determining the first waiting time required for the target user to handle business at the first outlet, the waiting time for the target user to handle business at multiple second outlets can be predicted. First, the flow of people at multiple second outlets within the target time period can be predicted, where the second outlet refers to multiple outlets that are of the same type as the first outlet and are within a certain range of distance from the first outlet. The target time period refers to a period of time that starts at the target moment when the target user submits a number-taking instruction and extends backward, which can be half an hour or an hour, etc.

[0043] It should be noted that the flow of people at multiple second outlets within the target time period can be predicted by a flow prediction model. This can be done by obtaining historical flow data and environmental information such as special days and weather at each second outlet within the target time period, where the environmental information corresponding to the historical flow data is the same as the current environmental information of the second outlet. For example, the target user submitted a number-taking instruction at Bank Z at 10:00 a.m. on September 30. Assuming that the 30th of each month is payday and there are three second outlets near Bank Z, the flow of people at each second outlet in the time period of 10:00-10:30 can be predicted. Therefore, the historical flow of people and environmental information of each second outlet on historical paydays can be obtained and input into the flow prediction model to obtain the flow prediction value of each second outlet.

[0044] Step S103, obtain the waiting time required for the target user to handle business at each second outlet, obtain M second waiting times, and determine the predicted waiting time for the target user to go to each second outlet to handle business based on the M second waiting times, M traffic prediction values ​​and M target distances, and obtain M predicted waiting times.

[0045] Specifically, after obtaining the traffic forecast value of each second outlet, the system's real-time data can be used to obtain the user information and corresponding business information of each second outlet that handles the business before the target user submits the number-taking instruction, such as user type, type of business handled, etc., and based on the user information and business information, determine the time required for each user before the target user to handle the business, and determine the waiting time required for the target user to handle the business at each second outlet by adding them up, and obtain multiple second waiting times.

[0046] It should be noted that after obtaining multiple second waiting times, the distance between the target user and each second outlet can be obtained to obtain multiple target distances. The system can estimate the time required for the target user to reach each second outlet based on each target distance. By combining the traffic prediction value of each second outlet and the time required for the target user to reach each second outlet, the number of newly added users at each second outlet in the process of the target user going to the second outlet can be calculated, and the newly added waiting time can be determined.

[0047] It should be noted that after obtaining the newly added waiting time of the target user at each second outlet, the newly added waiting time of each second outlet can be combined with the first waiting time and second waiting time obtained above to comprehensively determine the predicted waiting time for the target user to go to each second outlet to handle business, and finally obtain multiple predicted waiting times.

[0048] Step S104: generating service prompt information to be sent to the target user according to the M predicted waiting times and the first waiting time.

[0049] Specifically, after obtaining the predicted waiting time for the target user to go to each second outlet to handle business, business reminder information sent to the target user can be generated based on multiple predicted waiting times and the first waiting time. By comparing the first waiting time with multiple predicted waiting times, if there is a situation where the predicted waiting time is less than the first waiting time, or the predicted waiting time is slightly different from the first waiting time, business reminder information for going to the second outlet with the minimum predicted waiting time can be sent to the user. The business reminder information may include the first waiting time for the target user to handle business at the first outlet, the minimum predicted waiting time for the target user to go to the second outlet to handle business, and transportation methods and route recommendations to the second outlet with the minimum predicted waiting time.

[0050] It should be noted that when the predicted waiting time is greater than the first waiting time and the difference between the two is quite large, it can be considered that the target user is more suitable for handling business at the current first outlet. Therefore, the system can push business reminder information of the first outlet to the target user. The business reminder information may include the first waiting time for the target user to handle business at the first outlet, as well as promotional information of other businesses of the first outlet, etc., and finally complete the sending of the business reminder information.

[0051] The method for generating business prompt information provided in the embodiment of the present application adopts the method of responding to the number-taking instruction submitted by the target user at the first outlet, and determining the waiting time required for the target user to handle the business at the first outlet to obtain the first waiting time; determining the predicted flow of people at M second outlets within the target time period to obtain M flow prediction values, wherein the target time period is started at the target time, the target time is the time when the target user submits the number-taking instruction, and M is a positive integer; obtaining the waiting time required for the target user to handle the business at each second outlet to obtain M second waiting times, and determining the predicted waiting time for the target user to go to each second outlet to handle the business based on the M second waiting times, the M flow prediction values ​​and the M target distances to obtain M predicted waiting times; and determining the predicted waiting time based on the M predicted waiting times and the first waiting time. The method of generating business reminder information to be sent to the target user determines the first waiting time of the target user at the first outlet according to the user type and the business type handled by the historical user, and uses the prediction model to determine the predicted flow of people in multiple second outlets, and then calculates the second waiting time for handling business at each second outlet, and determines the predicted waiting time for each second outlet according to the second waiting time and the target distance from the target user to the second outlet, and finally generates the business reminder information to be sent to the target user by comparing the multiple predicted waiting times with the first waiting time, thereby solving the problem of low user business handling efficiency in a single outlet through manual or self-service machines in the related technology, thereby achieving the technical effect of improving user business handling efficiency and reducing user waiting time for business handling.

[0052] Optionally, in the method for generating business prompt information provided in the embodiment of the present application, determining the waiting time required for the target user to handle business at the first outlet, and obtaining the first waiting time includes: obtaining the user type of the historical user before the target user in the first outlet, and obtaining N first user types, where N is a positive integer; obtaining the business that each historical user needs to handle, and obtaining N first businesses, and determining the business handling time for each user based on the user type and the first business of each user, and obtaining N business handling times; adding the N business handling times to obtain the first waiting time.

[0053] It should be noted that in the process of generating business prompt information, the waiting time required for the target user to handle business at the first outlet can be determined first. The system's real-time data can be used to determine the historical users who are waiting to handle business before the target user in the first outlet, and the user type of each historical user can be obtained to obtain multiple first user types, among which the user type can be classified according to age, gender, etc.

[0054] Optionally, after obtaining the first user types of multiple historical users, the business types of the services that each historical user needs to handle can be obtained, such as deposits, withdrawals, credit card applications and other different types of services, to obtain multiple first services. For each historical user, based on the first user type and the first service, the time required for each historical user to handle the service can be determined, and multiple service processing times can be obtained. By adding up the multiple service processing times, the time required for the target user to wait for the service at the first outlet can be finally obtained, that is, the first waiting time.

[0055] For example, suppose user C handles business at Bank Z, and there are three users who handle business before user C. The first two are young users who handle deposit business and loan business respectively. The system estimates that the processing time for these two users is 5 minutes and 10 minutes respectively based on the recorded historical information. The third is an elderly user who handles loan business, and the estimated processing time is 20 minutes. Therefore, the waiting time for user C to handle business at Bank Z is 35 minutes, and the first waiting time for the target user at the first branch is obtained.

[0056] This embodiment determines the first waiting time for the target user to handle the service at the first outlet by acquiring the user type and service type of the historical user, thereby ensuring the accuracy of the estimation of the first waiting time.

[0057] Optionally, in the method for generating business prompt information provided in the embodiment of the present application, the predicted flow of people at M second outlets within the target time period is determined to obtain M flow prediction values, including: for each second outlet, obtaining environmental information and multiple historical flow rates of people at the second outlet within the target time period, wherein the environmental information of the time period in which each historical flow rate is located is the same as the environmental information of the second outlet; inputting multiple historical flow rates and environmental information into a flow prediction model to obtain an initial prediction value for the second outlet; judging whether there is activity information at the second outlet within the target time period; if there is activity information, changing the initial prediction value according to the activity information to obtain the flow prediction value for the second outlet; if there is no activity information, determining the initial prediction value as the flow prediction value for the second outlet.

[0058] It should be noted that after obtaining the first waiting time required for the target user to handle business at the first outlet, the flow of people at multiple second outlets within the target time period can be predicted. First, the environmental information of each second outlet within the target time period can be obtained, such as weather conditions, holidays, etc. At the same time, the historical flow of people at each second outlet within the target time period is collected. The environmental information of each time period in which the historical flow of people is located is the same as the environmental information of the current second outlet. The target time period starts at the target moment when the target user submits the number-taking instruction, and extends backward for a period of time, which can be half an hour or an hour, etc.

[0059] Optionally, after obtaining multiple historical traffic flows and environmental information of each second outlet, the multiple historical traffic flow data and corresponding environmental information can be input into the traffic prediction model, and the model can be used to calculate the initial predicted value of the traffic flow of each second outlet, wherein the traffic prediction model can use a distributed LSTM neural network model built by pre-trained XGBoost and LSTM.

[0060] Optionally, after obtaining the initial predicted value of the flow of people at each second outlet, it can be determined whether there is any activity information at the second outlet during the target time period, that is, whether the second outlet has held special activities such as discounts and promotions. If there is activity information, the initial predicted value can be changed according to the activity information. For example, the initial predicted value of the flow of people can be processed according to the scale of the activity to obtain the flow prediction value of the second outlet. If there is no activity information, the initial predicted value will ultimately be determined as the flow prediction value of the second outlet.

[0061] This embodiment predicts the initial predicted value of the flow of people at the second outlet within the target time period through a flow prediction model, and adjusts and changes the initial predicted value according to whether there is activity information at the second outlet, and finally obtains the flow prediction value of the second outlet, thereby ensuring the accuracy of predicting the flow of people at the second outlet.

[0062] Optionally, in the method for generating business prompt information provided in the embodiment of the present application, the predicted waiting time for the target user to go to each second outlet to handle business is determined based on M second waiting times, M traffic prediction values, and M target distances, and the M predicted waiting times are obtained, including: for each second outlet, calculating the time required for the target user to reach the second outlet according to the target distance to obtain the first time; calculating the new number of people at the second outlet according to the traffic prediction value and the first time; calculating the new waiting time based on the new number of people, and determining the predicted waiting time for the second outlet based on the new waiting time, the second waiting time, and the first time.

[0063] It should be noted that after obtaining the traffic prediction value of the second outlet, the predicted waiting time for the target user to go to each second outlet to handle business can be determined based on multiple traffic prediction values, the second waiting time and the target distance. Among them, the second waiting time can be obtained by obtaining historical users who have been waiting for business handling at each second outlet before the target user, and determining the time required for each historical user to handle business at the second outlet based on the user type of each historical user and the type of business to be handled, thereby obtaining the waiting time required for the target user to handle business at each second outlet, that is, the second waiting time.

[0064] Optionally, after obtaining the second waiting time, the distance between the target user and each second outlet can be obtained to obtain multiple target distances. The system can estimate the time required for the target user to reach each second outlet based on each target distance, that is, the first time. According to the traffic prediction value and the first time, the additional number of target users in the process of going to the second outlet can be calculated. For example, the target user submits a number-taking instruction at the first outlet A at 2:00 p.m., and it is assumed that the traffic prediction value of the second outlet B from 2:00 p.m. to 2:30 p.m. is 4 people according to the model prediction, and the first time required for the target user to go to the second outlet B is 15 minutes. The calculation shows that the additional number of target users in the process of going to the second outlet is 2 people.

[0065] Optionally, after obtaining the number of new people at each second outlet, the new waiting time of the target user at each second outlet can be calculated based on the number of new people and the average business processing time at each second outlet. The new waiting time, the second waiting time and the first time are comprehensively considered to determine the predicted waiting time of the target user at each second outlet. The second waiting time and the new waiting time can be added together. When the added result is greater than the first time, the added result of the second waiting time and the new waiting time is determined as the predicted waiting time. When the added result is less than the first time, the first time is finally determined as the predicted waiting time.

[0066] This embodiment comprehensively considers the newly added waiting time, the second waiting time and the first waiting time to determine the predicted waiting time of the target user at each second network point, thereby ensuring the accuracy of estimating the predicted waiting time at each second network point.

[0067] Optionally, in the method for generating business prompt information provided in the embodiment of the present application, generating business prompt information to be sent to the target user based on M predicted waiting times and the first waiting time includes: determining whether there is a target waiting time less than the first waiting time among the M predicted waiting times; if there is at least one target waiting time, determining the second outlet to which the smallest target waiting time belongs as the target outlet, and generating the first business prompt information based on the outlet information of the target outlet, wherein the first business prompt information is used to prompt the target user to go to the second outlet to handle the business; if there is no target waiting time, obtaining a candidate waiting time with the smallest difference from the first waiting time; determining whether the difference between the candidate waiting time and the first waiting time is less than a target threshold; if the difference is less than or equal to the target threshold, determining the second outlet to which the candidate waiting time belongs as the target outlet, and generating the first business prompt information based on the outlet information of the target outlet; if the difference is greater than the target threshold, generating business promotion information based on the business information in the first outlet, and generating the second business prompt information based on the business promotion information, wherein the second business prompt information is used to promote the business to the target user.

[0068] It should be noted that after obtaining the predicted waiting time of the target user at each second outlet, the target outlet can be determined according to different situations by comparing the aforementioned first waiting time with each predicted waiting time, that is, the outlet where the target user is recommended to handle business, and corresponding business prompt information can be generated.

[0069] Specifically, in the process of determining the target outlet, it is first possible to determine whether there is a target waiting time that is less than the first waiting time among multiple predicted waiting times. If there is at least one target waiting time, that is, there is a predicted waiting time that is less than the first waiting time, the second outlet corresponding to the smallest target waiting time can be selected as the target outlet, and a first business prompt information for the target outlet is generated to prompt the target user to go to the target outlet to handle business. The first business prompt information may include the first waiting time for the target user to handle business at the first outlet, the predicted waiting time for the target user to go to the target outlet to handle business, and information such as transportation methods and route recommendations to the target outlet.

[0070] Optionally, when there is no target waiting time, that is, when each predicted waiting time is greater than the first waiting time, the difference between each predicted waiting time and the first waiting time can be calculated, and the predicted waiting time with the smallest difference with the first waiting time is obtained, which is determined as the candidate waiting time, and then the target network point can be determined based on the difference between the candidate waiting time and the first waiting time.

[0071] Specifically, in the process of determining the target outlet based on the difference between the candidate waiting time and the first waiting time, it is first possible to determine whether the difference between the candidate waiting time and the first waiting time is less than a preset target threshold, such as 5 minutes. When the difference is less than or equal to the target threshold, the second outlet corresponding to the candidate waiting time can be determined as the target outlet, and the first business prompt information can be generated based on the outlet information of the target outlet. When the difference is greater than the target threshold, it can be considered that the target user is more suitable for conducting business at the current first outlet. Therefore, the system can generate business promotion information based on the business information in the first outlet, and generate second business prompt information based on the business promotion information, wherein the second business prompt information can include the first waiting time for the target user to conduct business at the first outlet, as well as promotion information of other businesses in the first outlet except for the business that the target user needs to conduct, and finally complete the sending of the business prompt information.

[0072] This embodiment determines the target outlet and generates corresponding service prompt information by predicting the waiting time and the target threshold, thereby realizing the diversion of users in the first outlet and improving the efficiency of user service handling and user experience.

[0073] Optionally, in the method for generating business prompt information provided in an embodiment of the present application, after obtaining the first waiting time, the method also includes: determining whether the first waiting time is less than the preset waiting time; if the first waiting time is less than the preset waiting time, generating business promotion information according to the business information in the first outlet, and generating second business prompt information according to the business promotion information.

[0074] It should be noted that after obtaining the aforementioned first waiting time, the first waiting time and the preset waiting time can be compared to determine whether the first waiting time is less than the preset waiting time, wherein the preset waiting time is a pre-set waiting time, for example, 10 minutes. When the first waiting time is less than the preset waiting time, it means that the target user's waiting time at the first outlet is short. Therefore, corresponding business promotion information can be generated based on the business information in the first outlet, and second business prompt information can be generated based on the business promotion information for sending business promotion content to the target user.

[0075] For example, when the preset waiting time is 10 minutes, assuming that the first waiting time for the target user to handle deposit business in Bank Z is 8 minutes, in this case, the first waiting time is less than the preset waiting time. Therefore, the system can generate promotional information for other businesses besides deposit business based on the business information in the first branch, such as loans, credit card processing, etc., and then generate second business prompt information based on these business promotion information to allow the target user to learn more about the bank's business.

[0076] This embodiment preliminarily determines the length of waiting time for the target user to handle business at the first outlet by comparing the first waiting time with the preset waiting time, and generates relevant business prompt information, thereby improving user experience.

[0077] Optionally, in the method for generating business prompt information provided in the embodiment of the present application, after responding to the number-taking instruction submitted by the target user at the first outlet, the method also includes: obtaining the number of times the target user has received the first business prompt information within a historical time period to obtain a first number; determining the number of times the target user has gone to each second outlet to handle business within the historical time period to obtain a second number; determining the promotion success rate of the target user based on the first number and the second number; when the promotion success rate is less than the preset success rate, generating business promotion information based on the business information in the first outlet, and generating second business prompt information based on the business promotion information.

[0078] It should be noted that after responding to the number-taking instruction submitted by the target user at the first outlet, the system can obtain the number of times the target user receives the first business prompt information within a historical time period to obtain a first quantity, wherein the historical time period can be a period of time before the target user submits the number-taking instruction, which can be a quarter, a year, etc., and then the number of times the target user goes to each second outlet to handle business after receiving the first business prompt information within the historical time period can be counted to obtain a second quantity.

[0079] Optionally, after obtaining the first number and the second number, the second number can be divided by the first number to determine the promotion success rate of the target user, that is, the proportion of the target users who actually go to the second outlet to handle business after receiving the first business prompt information, and then the corresponding prompt information can be generated according to the promotion success rate and the preset success rate, wherein the preset success rate is a success rate pre-set in the system, such as 50%. If the promotion success rate is less than the preset success rate, it can be considered that the promotion success rate of the target user is low, that is, the target user is more willing to wait at the first outlet to handle business. Therefore, business promotion information can be generated based on the business information in the first outlet, and the second business prompt information can be generated based on the business promotion information, so as to send the business promotion content of the first outlet to the target user.

[0080] This embodiment calculates the promotion success rate of the target user and compares it with the preset success rate, thereby determining the target user's response to the first business prompt information, and generates corresponding business prompt information according to different situations, thereby improving the promotion effect and user satisfaction.

[0081] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0082] Example 2

[0083] The embodiment of the present application also provides a device for generating service prompt information. It should be noted that the device for generating service prompt information in the embodiment of the present application can be used to execute the method for generating service prompt information provided in the above embodiment. The device for generating service prompt information provided in the embodiment of the present application is introduced below.

[0084] According to an embodiment of the present application, a device for implementing the above-mentioned method for generating service prompt information is also provided. Figure 3 is a schematic diagram of a device for generating business prompt information according to Embodiment 2 of the present application, such as Figure 3 As shown, the device comprises:

[0085] The first determining unit 31 is used to respond to the number taking instruction submitted by the target user at the first outlet, and determine the waiting time required for the target user to handle the service at the first outlet, so as to obtain a first waiting time.

[0086] The second determination unit 32 is used to determine the predicted flow of people at M second outlets within a target time period to obtain M flow prediction values, wherein the target time period is started at a target time, the target time is the time when the target user submits a number-taking instruction, and M is a positive integer.

[0087] The first acquisition unit 33 is used to obtain the waiting time required for the target user to handle business at each second outlet, obtain M second waiting times, and determine the predicted waiting time for the target user to go to each second outlet to handle business based on the M second waiting times, M traffic prediction values ​​and M target distances, and obtain M predicted waiting times.

[0088] The first generating unit 34 is used to generate service prompt information to be sent to the target user according to the M predicted waiting times and the first waiting time.

[0089] The device for generating business prompt information provided by the embodiment of the present application adopts a first determination unit to respond to the number-taking instruction submitted by the target user at the first outlet, and determines the waiting time required for the target user to handle the business at the first outlet, and obtains the first waiting time; the second determination unit determines the predicted flow of people at M second outlets within the target time period, and obtains M flow prediction values, wherein the target time period is taken as the starting time by the target time, the target time is the time when the target user submits the number-taking instruction, and M is a positive integer; the first acquisition unit obtains the waiting time required for the target user to handle the business at each second outlet, and obtains M second waiting times, and determines the predicted waiting time for the target user to go to each second outlet to handle the business according to the M second waiting times, the M flow prediction values ​​and the M target distances, and obtains M predicted waiting times; the first generation unit determines the predicted flow of people at M second outlets according to the M predicted flow values. The invention discloses a method for generating business prompt information to be sent to a target user by measuring the waiting time and the first waiting time. The method determines the first waiting time of the target user at the first outlet according to the user type and the business type handled by the historical user, and uses the prediction model to determine the predicted flow of people in multiple second outlets, and then calculates the second waiting time for handling business at each second outlet. The predicted waiting time of each second outlet is determined according to the second waiting time and the target distance from the target user to the second outlet. The business prompt information sent to the target user is finally generated by comparing the multiple predicted waiting times with the first waiting time. The problem of low user business handling efficiency caused by manual or self-service machines in the related technology is solved, thereby achieving the technical effect of improving user business handling efficiency and reducing the waiting time for user business handling.

[0090] Optionally, in the device for generating business prompt information provided in the embodiment of the present application, the first determination unit 31 includes: a first acquisition module, used to acquire the user type of the historical user located before the target user in the first outlet, and obtain N first user types, where N is a positive integer; a second acquisition module, used to acquire the business that each historical user needs to handle, and obtain N first businesses, and determine the business handling time of each user according to the user type and the first business of each user, and obtain N business handling times; an addition module, used to add the N business handling times to obtain the first waiting time.

[0091] Optionally, in the device for generating business prompt information provided in the embodiment of the present application, the second determination unit 32 includes: a third acquisition module, used to obtain, for each second outlet, environmental information and multiple historical traffic flows of the second outlet within a target time period, wherein the environmental information of the time period in which each historical traffic flow is located is the same as the environmental information of the second outlet; an input module, used to input multiple historical traffic flows and environmental information into a traffic prediction model to obtain an initial prediction value for the second outlet; a first judgment module, used to judge whether there is activity information at the second outlet within the target time period; a change module, used to change the initial prediction value according to the activity information when there is activity information, to obtain a traffic prediction value for the second outlet; and a first determination module, used to determine the initial prediction value as the traffic prediction value for the second outlet when there is no activity information.

[0092] Optionally, in the device for generating business prompt information provided in the embodiment of the present application, the first acquisition unit 33 includes: a first calculation module, used to calculate, for each second outlet, the time required for the target user to reach the second outlet according to the target distance, to obtain a first time; a second calculation module, used to calculate the number of new people at the second outlet according to the traffic prediction value and the first time; a second determination module, used to calculate the new waiting time based on the new number of people, and determine the predicted waiting time for the second outlet based on the new waiting time, the second waiting time and the first time.

[0093] Optionally, in the device for generating the service prompt information provided in the embodiment of the present application, the first generating unit 34 includes: a second judging module, used to judge whether there is a target waiting time shorter than the first waiting time in the M predicted waiting times; a third determining module, used to, if there is at least one target waiting time, determine the second outlet to which the smallest target waiting time belongs as the target outlet, and generate the first service prompt information according to the outlet information of the target outlet, wherein the first service prompt information is used to prompt the target user to go to the second outlet to handle the service; and a fourth obtaining module, used to, if there is no target waiting time, obtain the information related to the first outlet. a candidate waiting time with the smallest difference in waiting time; a third judging module, used to judge whether the difference between the candidate waiting time and the first waiting time is less than a target threshold; a fourth determining module, used to, when the difference is less than or equal to the target threshold, determine the second outlet to which the candidate waiting time belongs as the target outlet, and generate first business prompt information based on the outlet information of the target outlet; a generating module, used to, when the difference is greater than the target threshold, generate business promotion information based on the business information in the first outlet, and generate second business prompt information based on the business promotion information, wherein the second business prompt information is used to promote business to target users.

[0094] Optionally, in the device for generating business prompt information provided in the embodiment of the present application, after obtaining the first waiting time, the method also includes: a judgment unit, used to judge whether the first waiting time is less than the preset waiting time; a second generation unit, used to generate business promotion information according to the business information in the first outlet when the first waiting time is less than the preset waiting time, and generate second business prompt information according to the business promotion information.

[0095] Optionally, in the device for generating business prompt information provided in the embodiment of the present application, after responding to the number-taking instruction submitted by the target user at the first outlet, the method also includes: a second acquisition unit, used to acquire the number of times the target user has received the first business prompt information within a historical time period, and obtain a first number; a third determination unit, used to determine the number of times the target user has gone to each second outlet to handle business within the historical time period, and obtain a second number; a fourth determination unit, used to determine the promotion success rate of the target user based on the first number and the second number; a third generation unit, used to generate business promotion information based on the business information in the first outlet when the promotion success rate is less than a preset success rate, and generate second business prompt information based on the business promotion information.

[0096] It should be noted that the first determining unit 31, the second determining unit 32, the first acquiring unit 33, and the first generating unit 34 correspond to steps S201 to S204 in Embodiment 1, and the first determining unit 31, the second determining unit 32, the first acquiring unit 33, and the first generating unit 34 are the same as the examples and application scenarios implemented by the corresponding steps, but are not limited to the contents disclosed in the above Embodiment 1. It should be noted that the above modules or units may be hardware components or software components stored in a memory (e.g., memory 104) and processed by one or more processors (e.g., processors 102a, 102b, ..., 102n), and the above modules may also be part of the device and may be run in the computer terminal 10 provided in Embodiment 1.

[0097] Example 3

[0098] An embodiment of the present application may provide an electronic device, Figure 4 is a structural block diagram of an electronic device according to an embodiment of the present application. Figure 4 As shown, the electronic device may include: one or more ( Figure 4 (only one is shown) processor 1002, memory 1004, storage controller, and peripheral interface, wherein the peripheral interface is connected to the radio frequency module, audio module and display.

[0099] Among them, the memory can be used to store software programs and modules, such as the program instructions / modules corresponding to the method and device for generating the business prompt information in the embodiment of the present application, and the processor executes various functional applications and data processing by running the software programs and modules stored in the memory, that is, realizing the above-mentioned method for generating the business prompt information. The memory may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include a memory remotely arranged relative to the processor, and these remote memories may be connected to the terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0100] The processor can call the information and application stored in the memory through the transmission device to perform the following steps: respond to the number-taking instruction submitted by the target user at the first outlet, and determine the waiting time required for the target user to handle business at the first outlet, and obtain a first waiting time; determine the predicted flow of people at M second outlets within the target time period, and obtain M flow prediction values, wherein the target time period is started at the target time, the target time is the time when the target user submits the number-taking instruction, and M is a positive integer; obtain the waiting time required for the target user to handle business at each second outlet, and obtain M second waiting times, and determine the predicted waiting time for the target user to go to each second outlet to handle business based on the M second waiting times, the M flow prediction values ​​and the M target distances, and obtain M predicted waiting times; generate business prompt information sent to the target user based on the M predicted waiting times and the first waiting time.

[0101] The processor can also call the information and application stored in the memory through the transmission device to perform the following steps: obtain the user type of the historical user before the target user in the first outlet, and obtain N first user types, where N is a positive integer; obtain the services that each historical user needs to handle, and obtain N first services, and determine the service handling time of each user according to the user type and the first service of each user, and obtain N service handling times; add the N service handling times to obtain the first waiting time.

[0102] The processor can also call the information and application programs stored in the memory through the transmission device to perform the following steps: for each second network point, obtain the environmental information and multiple historical human flows of the second network point within the target time period, wherein the environmental information of the time period in which each historical human flow is located is the same as the environmental information of the second network point; input the multiple historical human flows and environmental information into the flow prediction model to obtain the initial prediction value of the second network point; determine whether there is activity information of the second network point within the target time period; if there is activity information, change the initial prediction value according to the activity information to obtain the flow prediction value of the second network point; if there is no activity information, determine the initial prediction value as the flow prediction value of the second network point.

[0103] The processor can also call the information and application programs stored in the memory through the transmission device to perform the following steps: for each second network point, calculate the time required for the target user to reach the second network point according to the target distance to obtain the first time; calculate the new number of people at the second network point according to the traffic prediction value and the first time; calculate the new waiting time according to the new number of people, and determine the predicted waiting time for the second network point according to the new waiting time, the second waiting time and the first time.

[0104] The processor can also call the information and application stored in the memory through the transmission device to perform the following steps: determine whether there is a target waiting time less than the first waiting time among the M predicted waiting times; if there is at least one target waiting time, determine the second outlet to which the smallest target waiting time belongs as the target outlet, and generate first business prompt information based on the outlet information of the target outlet, wherein the first business prompt information is used to prompt the target user to go to the second outlet to handle the business; if there is no target waiting time, obtain the candidate waiting time with the smallest difference from the first waiting time; determine whether the difference between the candidate waiting time and the first waiting time is less than the target threshold; if the difference is less than or equal to the target threshold, determine the second outlet to which the candidate waiting time belongs as the target outlet, and generate first business prompt information based on the outlet information of the target outlet; if the difference is greater than the target threshold, generate business promotion information based on the business information in the first outlet, and generate second business prompt information based on the business promotion information, wherein the second business prompt information is used to promote business to the target user.

[0105] The processor can also call the information and application stored in the memory through the transmission device to perform the following steps: determine whether the first waiting time is less than the preset waiting time; when the first waiting time is less than the preset waiting time, generate business promotion information based on the business information in the first outlet, and generate second business prompt information based on the business promotion information.

[0106] The processor can also call the information and application programs stored in the memory through the transmission device to perform the following steps: obtain the number of times the target user receives the first business prompt information within the historical time period to obtain a first number; determine the number of times the target user goes to each second outlet to handle business within the historical time period to obtain a second number; determine the promotion success rate of the target user based on the first number and the second number; when the promotion success rate is less than the preset success rate, generate business promotion information based on the business information in the first outlet, and generate second business prompt information based on the business promotion information.

[0107] It can be understood by those skilled in the art that Figure 4 The structure shown is for illustration only, and the electronic device may also be a smart phone (such as an Android phone, an iOS phone, etc.), a tablet computer, a PDA, a mobile Internet device (Mobile Internet Devices, MID), a PAD, or other terminal devices. Figure 4 The structure of the electronic device is not limited. Figure 4 More or fewer components (such as network interfaces, display devices, etc.) shown in, or having Figure 4 Different configurations are shown.

[0108] A person of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing the hardware related to the terminal device through a program, and the program can be stored in a computer-readable storage medium, and the storage medium may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0109] Example 4

[0110] The embodiment of the present application further provides a storage medium. Optionally, in this embodiment, the storage medium can be used to store the program code executed by the method for generating service prompt information provided in the first embodiment.

[0111] Optionally, in this embodiment, the above storage medium may be located in any computer terminal in a computer terminal group in a computer network, or in any mobile terminal in a mobile terminal group.

[0112] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing the steps of the method for generating business prompt information.

[0113] The present application also provides a computer-readable storage medium, which includes a stored executable program, wherein when the executable program is running, the program controls the device where the computer-readable storage medium is located to execute the steps of the method for generating business prompt information.

[0114] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0115] In the above embodiments of the present application, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0116] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0117] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0118] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0119] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk and other media that can store program codes.

[0120] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for generating business prompt information, characterized in that: include: Responding to a number-taking instruction submitted by a target user at a first outlet, and determining a waiting time required for the target user to handle a service at the first outlet, thereby obtaining a first waiting time; Determine the predicted flow of people at M second outlets within a target time period, and obtain M flow prediction values, wherein the target time period is started at a target time, the target time is the time when the target user submits the number-taking instruction, and M is a positive integer; Obtaining the waiting time required for the target user to handle business at each second outlet, obtaining M second waiting times, and determining the predicted waiting time for the target user to go to each second outlet to handle business according to the M second waiting times, the M traffic prediction values, and the M target distances, obtaining M predicted waiting times; Generate service prompt information to be sent to the target user according to the M predicted waiting times and the first waiting time.

2. The method according to claim 1, characterized in that Determining the waiting time required for the target user to handle business at the first outlet, where obtaining the first waiting time includes: Obtaining user types of historical users before the target user in the first network point to obtain N first user types, where N is a positive integer; Obtain the services that each historical user needs to handle, obtain N first services, and determine the service handling time of each user according to the user type and the first service of each user, and obtain N service handling time; The N service processing times are added together to obtain the first waiting time.

3. The method according to claim 1, characterized in that Determine the predicted passenger flow of M second outlets within the target time period, and obtain M flow prediction values ​​including: For each second network point, obtaining environmental information and multiple historical human flows of the second network point in the target time period, wherein the environmental information of the time period in which each historical human flow falls is the same as the environmental information of the second network point; Inputting the plurality of historical human flows and the environmental information into a flow prediction model to obtain an initial prediction value of the second network point; Determine whether the second network point has activity information within the target time period; In the case where the activity information exists, the initial prediction value is changed according to the activity information to obtain a traffic prediction value of the second network point; In the absence of the activity information, the initial prediction value is determined as the traffic prediction value of the second network point.

4. The method according to claim 1, characterized in that: Determining the predicted waiting time for the target user to go to each second outlet to handle business according to the M second waiting time periods, the M traffic prediction values, and the M target distances, and obtaining the M predicted waiting time periods includes: For each second network point, calculating the time required for the target user to reach the second network point according to the target distance to obtain a first time length; Calculate the number of new users at the second network point according to the traffic prediction value and the first duration; An additional waiting time is calculated according to the additional number of people, and a predicted waiting time for the second network point is determined according to the additional waiting time, the second waiting time and the first waiting time.

5. The method according to claim 1, characterized in that Generating the service prompt information sent to the target user according to the M predicted waiting times and the first waiting time includes: Determine whether there is a target waiting time shorter than the first waiting time among the M predicted waiting times; In the case where there is at least one target waiting time, determining the second network point to which the minimum target waiting time belongs as the target network point, and generating first service prompt information according to the network point information of the target network point, wherein the first service prompt information is used to prompt the target user to go to the second network point to handle the service; In the case where the target waiting time does not exist, obtaining a candidate waiting time having the smallest difference with the first waiting time; Determine whether the difference between the candidate waiting time and the first waiting time is less than a target threshold; In the case where the difference is less than or equal to the target threshold, determining the second network point to which the candidate waiting time belongs as the target network point, and generating the first service prompt information according to the network point information of the target network point; When the difference is greater than the target threshold, business promotion information is generated according to the business information in the first network point, and second business prompt information is generated according to the business promotion information, wherein the second business prompt information is used to promote the business to the target user.

6. The method according to claim 5, characterized in that After obtaining the first waiting time, the method further includes: Determining whether the first waiting time is less than a preset waiting time; When the first waiting time is less than the preset waiting time, business promotion information is generated according to the business information in the first network point, and the second business prompt information is generated according to the business promotion information.

7. The method according to claim 5, characterized in that After responding to the number acquisition instruction submitted by the target user at the first network point, the method further includes: Acquire the number of times the target user receives the first service prompt information in a historical time period to obtain a first quantity; Determine the number of times the target user went to each second outlet to handle business within the historical time period to obtain a second number; Determine a promotion success rate of the target user according to the first number and the second number; When the promotion success rate is lower than the preset success rate, business promotion information is generated according to the business information in the first network point, and second business prompt information is generated according to the business promotion information.

8. A device for generating business prompt information, characterized in that: include: A first determining unit is used to respond to a number taking instruction submitted by a target user at a first outlet, and determine a waiting time required for the target user to handle a service at the first outlet, thereby obtaining a first waiting time; A second determining unit is used to determine the predicted flow of people at M second outlets within a target time period, and obtain M flow prediction values, wherein the target time period is started at a target time, the target time is the time when the target user submits the number-taking instruction, and M is a positive integer; A first acquisition unit is used to acquire the waiting time required for the target user to handle the business at each second outlet, obtain M second waiting times, and determine the predicted waiting time for the target user to go to each second outlet to handle the business according to the M second waiting times, the M traffic prediction values, and the M target distances, to obtain M predicted waiting times; A first generating unit is configured to generate service prompt information to be sent to the target user according to the M predicted waiting times and the first waiting time.

9. A computer program product comprising computer instructions, characterized in that When the computer instructions are executed by a processor, the steps of the method for generating business prompt information according to any one of claims 1 to 7 are implemented.

10. An electronic device, characterized in that: include: A memory storing an executable program; A processor is used to run the program, wherein the program executes the method for generating business prompt information according to any one of claims 1 to 7 when running.

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