Airline ticket order processing method and device, storage medium and equipment

Abstract

The invention belongs to the technical field of computers, and provides a route ticket order processing method and device, a storage medium and equipment, and the method comprises the steps: determining the user attribute of an ordering user based on the historical ticket refunding data of the ordering user in a second preset time period; when determining that the user attribute of the order placing user is a blacklist user, intercepting a current ticket business order; and under the condition that the user attribute of the order placing user is determined to be the white list user, processing the current ticket business order according to the target execution strategy to obtain a corresponding processing result. Through the processing method, the current ticket business order can be intercepted in time under the condition that the order placing user is determined to be the blacklist user; and under the condition that the order placing user is determined to be the white list user, the current ticket business order is flexibly processed according to different target execution strategies.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a method, device, storage medium and equipment for processing airline ticket orders. Background Art

[0002] There are three ways to prevent seat occupation on existing online booking platforms such as airline websites. Their respective modes and problems are as follows:

[0003] Method 1: By allowing passengers to pay first and then reserve seats on flights, after passengers place an order, a passenger record number is generated first, and then the flight seat is released. After the passenger pays, the seat is made up and the electronic ticket is issued. This solution is relatively simple and easy to implement, but the problem is that the problem of paying first and then reserving seats is that within 15-30 minutes of payment, the flight seats are likely to be booked by other passengers or ticket agents from various channels (official websites, applications, online travel agents, call centers, etc.). By the time the passenger goes to pay, the seats in the same cabin have been booked. The passenger can only refund first and then book a higher-priced ticket, which greatly reduces passenger satisfaction and increases travel costs.

[0004] Method 2: Airlines and other platforms process user booking requests based on the number of times the logged-in user cancels orders. If it is detected that the logged-in user cancels 3 or more orders within 24 hours, the user's permission to generate orders will be blocked for 24 hours. This method is simple and crude, and the user experience is poor. Passengers or agents may have booked many orders in 24 hours, but their order permissions will be blocked if they only cancel 3 orders, thereby reducing the user's ticket purchasing experience.

[0005] Method 3: Airlines and other platforms implement different strategies based on the remaining number of seats on the booked flight. For example, after the user places an order and generates a record number, if the remaining number of seats in the class is less than 3, the strategy of first occupying seats and then paying is implemented; if the remaining number of seats in the class is greater than or equal to 3, the mode of first paying and then occupying seats is implemented. The disadvantage of this mode is that the strategy implemented is not sophisticated enough, and there is a high probability that the mode of first paying and then occupying seats is implemented. When this mode is used to release seats first and then fill seats, the number of seats in the class does not meet the number of passengers' reservations, and tickets cannot be issued.

[0006] The above processing methods are unable to intercept malicious seat-occupying orders in a timely and effective manner.

[0007] Therefore, how to intercept malicious seat-occupying orders in a timely and effective manner is a technical problem to be solved. Summary of the invention

[0008] Based on this, it is necessary to provide a method, device, storage medium and equipment for processing airline ticket orders to address the defect that the existing method for processing airline ticket orders cannot intercept malicious seat-occupying orders in a timely and effective manner.

[0009] In a first aspect, an embodiment of the present invention provides a method for processing an airline ticket order, the method comprising:

[0010] In response to receiving a current ticket order for a target route, obtaining associated data of the current ticket order of the ordering user within a first preset time period, and obtaining a booking route scoring model;

[0011] Scoring the current ticket order based on the associated data of the target route within the first preset time period and the booking route scoring model to obtain a score value of the current ticket order;

[0012] Get the target execution strategy that matches the value range of the score value of the current ticket order;

[0013] Determine the user attribute of the ordering user based on the historical ticket refund data of the ordering user within the second preset time period, wherein the user attribute of the ordering user includes: the ordering user is a blacklist user, or the ordering user is a whitelist user;

[0014] In the case where it is determined that the user attribute of the ordering user is a blacklist user, the current ticket order is determined to be a malicious seat-occupying order, and the current ticket order is intercepted;

[0015] When it is determined that the user attribute of the ordering user is a whitelist user, the current ticket order is processed according to the target execution strategy to obtain a corresponding processing result.

[0016] Optionally, scoring the current ticket order based on the associated data of the current ticket order within the first preset time period and the booking route scoring model to obtain a score value of the current ticket order includes:

[0017] Acquire the associated data of the current ticket order within the first preset time period, wherein the associated data of the current ticket order includes the departure place of the target route, the destination of the target route, and the travel date of the target route;

[0018] Determine a target route attribute type corresponding to the target route based on the departure place of the target route and the destination of the target route, wherein the target route attribute type includes a popular route, a common route and a depression route;

[0019] Acquire a first scoring value range and a first weight value matching the target route attribute type;

[0020] Based on the historical travel data of the target route, the travel date is analyzed to determine the target off-season and peak-season type corresponding to the travel date, wherein the target off-season and peak-season type includes peak season, normal season and off-season;

[0021] Acquire a second scoring value range and a second weight value matching the target off-season or peak-season type;

[0022] The first scoring value range, the first weight value, the second scoring value range and the second weight value are all input into the booking route scoring model for processing to obtain the score value of the current ticket order.

[0023] Optionally, the step of acquiring a target execution strategy that matches a numerical range to which the score value of the current ticket order belongs includes:

[0024] If the numerical range corresponding to the score value of the current ticket order is the numerical range of the first gear, the obtained matching target execution strategy includes: after paying the order fee corresponding to the current ticket order, generating a ticket including a seat number corresponding to the current ticket order;

[0025] If the numerical range corresponding to the score value of the current ticket order is the numerical range of the second gear, the obtained matching target execution strategy includes: using at least one verification code verification method for verification processing, and after the verification is passed, executing the processing of the current ticket order, the at least one verification code verification method includes: SMS verification code verification method, email verification code verification method, picture verification code verification method and voice verification code verification method;

[0026] If the numerical range corresponding to the score value of the current ticket order is the numerical range of the third gear, the obtained matching target execution strategy includes: using a warning reminder method to remind the ordering user, and after receiving the authorization processing instruction of the ordering user, executing the processing of the current ticket order.

[0027] Optionally, determining the user attribute of the ordering user based on the historical ticket refund data of the ordering user within a second preset time period includes:

[0028] Obtaining the historical ticket refund data;

[0029] If the historical ticket refund data shows that there are multiple ticket refund behaviors, and the number of ticket refunds is greater than or equal to a preset threshold, the user attribute of the ordering user is determined to be a blacklist user; otherwise, the user attribute of the ordering user is determined to be a whitelist user.

[0030] Optionally, when it is determined that the user attribute of the ordering user is a blacklist user, intercepting the current ticket order includes:

[0031] When it is determined that the user attribute of the ordering user is a blacklist user, an order blocking period is obtained, and all first ticket orders placed by the ordering user within the order blocking period are obtained;

[0032] All first ticket orders are determined as malicious seat-occupying orders, and any first ticket order is intercepted.

[0033] Optionally, when it is determined that the user attribute of the ordering user is a blacklist user, intercepting the current ticket order includes:

[0034] When it is determined that the user attribute of the ordering user is a blacklist user, all second ticketing orders placed by the ordering user within any time period are obtained;

[0035] All second ticket orders are identified as malicious seat-occupying orders, and any second ticket order is intercepted.

[0036] In a second aspect, an embodiment of the present invention provides a device for processing an airline ticket order, the device comprising:

[0037] A first acquisition module, configured to, in response to receiving a current ticket order for a target route, acquire associated data of the current ticket order of an ordering user within a first preset time period, and acquire a booking route scoring model;

[0038] A scoring module, configured to score the current ticket order based on the associated data of the target route within the first preset time period and the booking route scoring model, and obtain a score value of the current ticket order;

[0039] A second acquisition module is used to acquire a target execution strategy that matches the value range to which the score value of the current ticket order belongs;

[0040] A determination module, configured to determine a user attribute of the ordering user based on historical ticket refund data of the ordering user within a second preset time period, wherein the user attribute of the ordering user includes: the ordering user is a blacklist user, or the ordering user is a whitelist user;

[0041] An interception module, used to intercept the current ticket order when it is determined that the user attribute of the ordering user is a blacklist user;

[0042] The processing module is used to process the current ticket order according to the target execution strategy to obtain a corresponding processing result when it is determined that the user attribute of the ordering user is a whitelist user.

[0043] Optionally, the scoring module is specifically used for:

[0044] Acquire the associated data of the current ticket order within the first preset time period, wherein the associated data of the current ticket order includes the departure place of the target route, the destination of the target route, and the travel date of the target route;

[0045] Based on the departure place of the target route and the destination of the target route, determining the target route attribute type to which the target route belongs, the target route attribute type including a popular route, a common route and a depression route;

[0046] Acquire a first scoring value range and a first weight value matching the target route attribute type;

[0047] Based on the historical travel data of the target route, the travel date of the current ticket order is analyzed to determine the target off-season or peak-season type to which the travel date belongs, wherein the target off-season or peak-season type includes peak season, normal season and off-season;

[0048] Acquire a second scoring value range and a second weight value matching the target off-season or peak-season type;

[0049] The first scoring value range, the first weight value, the second scoring value range and the second weight value are all input into the booking route scoring model for processing to obtain the score value of the current ticket order.

[0050] In a third aspect, an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program is used to execute the above method steps.

[0051] In a fourth aspect, an embodiment of the present invention provides an electronic device, the electronic device comprising:

[0052] processor;

[0053] a memory for storing instructions executable by the processor;

[0054] The processor is used to read the executable instructions from the memory and execute the executable instructions to implement the above method steps.

[0055] In an embodiment of the present invention, in response to receiving the current ticket order of the target route, the associated data of the current ticket order of the ordering user within the first preset time period is obtained, and the booking route scoring model is obtained; based on the associated data of the target route within the first preset time period and the booking route scoring model, the current ticket order is scored to obtain the score value of the current ticket order; a target execution strategy matching the numerical range to which the score value of the current ticket order belongs is obtained; based on the historical refund data of the ordering user within the second preset time period, the user attribute of the ordering user is determined; if it is determined that the user attribute of the ordering user is a blacklist user, the current ticket order is intercepted and processed; and if it is determined that the user attribute of the ordering user is a whitelist user, the current ticket order is processed according to the target execution strategy to obtain a corresponding processing result. The processing method of the route ticket order provided by the embodiment of the present invention can intercept and process the current ticket order in a timely manner when it is determined that the ordering user is a blacklist user; and flexibly process the current ticket order according to different target execution strategies when it is determined that the ordering user is a whitelist user. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] By referring to the following drawings, a more complete understanding of the exemplary embodiments of the present invention can be obtained. The drawings are used to provide a further understanding of the embodiments of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the drawings, the same reference numerals generally represent the same components or steps.

[0057] Figure 1 A flowchart of a method for processing an airline ticket order according to an exemplary embodiment of the present invention;

[0058] Figure 2 It is a schematic diagram of the structure of an apparatus 200 for processing airline ticket orders according to an exemplary embodiment of the present invention. DETAILED DESCRIPTION

[0059] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0060] It should be noted that, unless otherwise specified, the technical terms or scientific terms used in the present invention should have the common meanings understood by those skilled in the art to which the present invention belongs.

[0061] In addition, the terms "first" and "second" etc. are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, device, product or equipment that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or equipment.

[0062] Embodiments of the present invention provide a method and device for processing airline ticket orders, a system, an electronic device, and a computer-readable medium, which are described below in conjunction with the accompanying drawings.

[0063] Example 1

[0064] The processing method for route ticketing orders provided by the embodiment of the present invention abandons the relatively single flight seat protection mode of the current airline website, and adopts a multi-dimensional, personalized, and configurable mode, through dimensions such as route attributes, flight schedules, and member attributes, and combined with information such as members' historical purchase behavior and order cancellations, it has both general prevention and control strategies and can flexibly configure processing strategies according to the needs of different application scenarios. The processing method provided by the present invention can effectively distinguish between blacklist users and whitelist users, and provides different processing strategies for whitelist users, greatly improving the success rate of ticket purchases. In this way, it not only improves the user experience, but also increases user stickiness.

[0065] Please refer to Figure 1 , which shows a flow chart of a method for processing airline ticket orders provided by some embodiments of the present invention, such as Figure 1 As shown, the method for processing an airline ticket order may include the following steps:

[0066] Step S101: in response to receiving a current ticket order for a target route, obtaining associated data of the current ticket order of the ordering user within a first preset time period, and obtaining a booking route scoring model.

[0067] Step S102: Based on the associated data of the target route within the first preset time period and the booking route scoring model, the current ticket order is scored to obtain a score value of the current ticket order.

[0068] In a possible implementation, scoring the current ticket order based on the associated data of the current ticket order within the first preset time period and the booking route scoring model to obtain the score value of the current ticket order includes the following steps:

[0069] Acquire the associated data of the current ticket order within the first preset time period, the associated data of the current ticket order including the departure place of the target route, the destination of the target route, and the travel date of the target route;

[0070] Based on the departure place and the destination of the target route, determine the target route attribute type corresponding to the target route, the target route attribute type includes a popular route, a common route and a depression route;

[0071] Obtain a first scoring value range and a first weight value that match the target route attribute type;

[0072] Based on the historical travel data of the target route, the travel date is analyzed to determine the target off-season and peak-season types corresponding to the travel date. The target off-season and peak-season types include peak season, normal season and off-season.

[0073] Obtain a second scoring value range and a second weight value that match the target off-season or peak-season type;

[0074] The first scoring value range, the first weight value, the second scoring value range and the second weight value are all input into the booking route scoring model for processing to obtain the score value of the current ticket order.

[0075] It should be noted that there is no specific limitation on the duration of the first preset time period in the above steps, and it can be adjusted according to the requirements of different application scenarios, which will not be elaborated here.

[0076] In actual application scenarios, in the process of determining the target route attribute type corresponding to the target route based on the departure place and the destination of the target route, the first score value range of the popular route can be set to between 8 and 10 points, and the first score value range of the ordinary route can be set to between 4 and 7 points, and the first score value range of the depression route can be set to between 1 and 3 points, and the first weight value is set to 70%.

[0077] In the process of analyzing the travel dates based on the historical travel data of the target routes to determine the target peak or off-season types corresponding to the travel dates, the second scoring range for the peak season can be set to between 8 and 10 points, the second scoring range for the average season can be set to between 4 and 7 points, and the second scoring range for the off-season can be set to between 1 and 3 points, and the second weight value can be set to 30%.

[0078] The above is only an example, and the first scoring value range, the first weight value, the second scoring value range and the second weight value can be configured according to the requirements of different application scenarios, and are not specifically limited here. Through the above steps, the score value of the current ticket order can be accurately determined.

[0079] It should be noted that the above-mentioned booking route scoring model adopts the above-mentioned scoring strategy, and the model construction method of the booking route scoring model is a conventional method, which will not be repeated here.

[0080] It should be noted that in other application scenarios, the above-mentioned booking route scoring model can also introduce other influencing factors, for example, the membership attribute of the ordering user. If the ordering user is a certified member, the ordering user will be scored lower. Or, if it is detected that the ordering user has a historical paid route ticket order, it is determined that the possibility of the ordering user maliciously occupying a seat is low, and the ordering user will be scored lower. The above is just an example. Other influencing factors can be introduced into the above-mentioned booking route scoring model according to the needs of different application scenarios, which will not be repeated here.

[0081] Step S103: Acquire a target execution strategy that matches the numerical range to which the score value of the current ticket order belongs.

[0082] In a possible implementation, obtaining a target execution strategy that matches the value range to which the score value of the current ticket order belongs includes the following steps:

[0083] If the numerical range corresponding to the score value of the current ticket order is the numerical range of the first gear, the obtained matching target execution strategy includes: after paying the order fee corresponding to the current ticket order, generating a ticket including a seat number corresponding to the current ticket order;

[0084] If the numerical range corresponding to the score value of the current ticket order is the numerical range of the second gear, the obtained matching target execution strategy includes: using at least one verification code verification method for verification processing, and after the verification is passed, executing the processing of the current ticket order, the at least one verification code verification method includes: SMS verification code verification method, email verification code verification method, picture verification code verification method and voice verification code verification method;

[0085] If the numerical range corresponding to the score value of the current ticket order is the numerical range of the third tier, the obtained matching target execution strategy includes: using a warning reminder method to remind the ordering user, and after receiving the authorization processing instruction of the ordering user, executing the processing of the current ticket order; wherein, any score value in the first tier is greater than any score value in the second tier, and any score value in the second tier is greater than any score value in the third tier.

[0086] In actual application scenarios, any score value of the first tier is greater than any score value of the second tier, and any score value of the second tier is greater than any score value of the third tier. The current ticket orders of the first tier often correspond to popular routes. Therefore, the protection strategy adopted for the current ticket orders of the first tier is higher, and protection can be provided by paying first and then occupying seats to avoid malicious users occupying seats. For example, in a specific application scenario, the value range of the first tier is between 8 and 10 points.

[0087] The current ticket orders of the second tier often correspond to ordinary routes, and therefore, can be verified by verification code verification methods, such as SMS verification code verification method, email verification code verification method, picture verification code verification method, and voice verification code verification method. For example, in a specific application scenario, the value range of the second tier is between 4 and 7 points.

[0088] In actual application scenarios, in addition to the verification method of the above verification code, the following protection strategies can also be adopted: shorten the payment time limit and reduce the time the seat is occupied. Different payment time limits can be configured according to different situations; or, according to dimensions such as route and time, pay first and then occupy the seat. Book the passenger's reservation record first and then release the seat. After payment, occupy the seat and issue the ticket.

[0089] The current ticket orders in the first tier often correspond to the low-lying routes. In a specific application scenario, the value range of the first tier is between 1 and 3. Use the alert reminder method and send the statistical data by email later.

[0090] Step S104: determining the user attributes of the ordering user based on the historical ticket refund data of the ordering user within the second preset time period, the user attributes of the ordering user including: the ordering user is a blacklist user, or the ordering user is a whitelist user.

[0091] It should be noted that there is no specific limitation on the duration of the second preset time period in the above steps, and it can be adjusted according to the requirements of different application scenarios, which will not be elaborated here.

[0092] In a possible implementation, determining the user attribute of the ordering user based on the historical ticket refund data of the ordering user within the second preset time period includes the following steps:

[0093] Get historical ticket refund data;

[0094] If the historical ticket refund data shows that there are multiple ticket refund behaviors, and the number of ticket refunds is greater than or equal to the preset threshold, the user attribute of the ordering user is determined to be a blacklist user; otherwise, the user attribute of the ordering user is determined to be a whitelist user.

[0095] Step S105: When it is determined that the user attribute of the ordering user is a blacklist user, the current ticket order is intercepted.

[0096] In a possible implementation, when it is determined that the user attribute of the ordering user is a blacklist user, the current ticket order is intercepted and processed, including the following steps:

[0097] When it is determined that the user attribute of the ordering user is a blacklist user, the order blocking period is obtained, and all first ticketing orders placed by the ordering user within the order blocking period are obtained;

[0098] All first ticket orders are determined as malicious seat-occupying orders, and any first ticket order is intercepted.

[0099] In a possible implementation, when it is determined that the user attribute of the ordering user is a blacklist user, the current ticket order is intercepted and processed, including the following steps:

[0100] When it is determined that the user attribute of the ordering user is a blacklist user, all second ticketing orders placed by the ordering user within any time period are obtained;

[0101] All second ticket orders are identified as malicious seat-occupying orders, and any second ticket order is intercepted.

[0102] Step S106: When it is determined that the user attribute of the ordering user is a whitelist user, the current ticket order is processed according to the target execution strategy to obtain a corresponding processing result.

[0103] In this step S106, if the numerical range corresponding to the score value of the current ticket order is the numerical range of the first gear, the obtained matching target execution strategy includes: after paying the order fee corresponding to the current ticket order, generating a ticket including a seat number corresponding to the current ticket order;

[0104] If the numerical range corresponding to the score value of the current ticket order is the numerical range of the second gear, the obtained matching target execution strategy includes: using at least one verification code verification method for verification processing, and after the verification is passed, executing the processing of the current ticket order, the at least one verification code verification method includes: SMS verification code verification method, email verification code verification method, picture verification code verification method and voice verification code verification method;

[0105] If the numerical range corresponding to the score value of the current ticket order is the numerical range of the third tier, the obtained matching target execution strategy includes: using a warning reminder method to remind the ordering user, and after receiving the authorization processing instruction of the ordering user, executing the processing of the current ticket order; wherein, any score value in the first tier is greater than any score value in the second tier, and any score value in the second tier is greater than any score value in the third tier.

[0106] The above are only examples, and the above target execution strategies may also be adjusted according to the requirements of different application scenarios, and are not specifically limited here.

[0107] The method for processing airline ticket orders provided by the embodiment of the present invention can intercept and process the current ticket order in a timely manner when it is determined that the ordering user is a blacklist user; and when it is determined that the ordering user is a whitelist user, the current ticket order can be flexibly processed according to different target execution strategies.

[0108] In the above embodiment, a method for processing an airline ticket order is provided. Correspondingly, the present invention also provides a device for processing an airline ticket order. The device for processing an airline ticket order provided in the embodiment of the present invention can implement the above method for processing an airline ticket order. The device for processing an airline ticket order can be implemented by software, hardware, or a combination of software and hardware. For example, the device for processing an airline ticket order can include integrated or separate functional modules or units to execute the corresponding steps in the above methods.

[0109] Example 2

[0110] Please refer to Figure 2 , which shows a schematic diagram of a flight ticket order processing device provided by some embodiments of the present invention. Since the device embodiment is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. The device embodiment described below is only illustrative.

[0111] like Figure 2 As shown, the airline ticket order processing device 200 may include:

[0112] A first acquisition module 201 is used for, in response to receiving a current ticket order for a target route, acquiring associated data of the current ticket order of the ordering user within a first preset time period, and acquiring a booking route scoring model;

[0113] The scoring module 202 is used to score the current ticket order based on the associated data of the target route within the first preset time period and the booking route scoring model to obtain a score value of the current ticket order;

[0114] The second acquisition module 203 is used to acquire a target execution strategy that matches the value range to which the score value of the current ticket order belongs;

[0115] The determination module 204 is used to determine the user attribute of the ordering user based on the historical ticket refund data of the ordering user within the second preset time period, and the user attribute of the ordering user includes: the ordering user is a blacklist user, or the ordering user is a whitelist user;

[0116] The interception module 205 is used to intercept the current ticket order when it is determined that the user attribute of the ordering user is a blacklist user;

[0117] The processing module 206 is used to process the current ticket order according to the target execution strategy to obtain a corresponding processing result when it is determined that the user attribute of the ordering user is a whitelist user.

[0118] In some implementations of the embodiments of the present invention, the scoring module 202 is specifically used to:

[0119] Acquire the associated data of the current ticket order within the first preset time period, the associated data of the current ticket order including the departure place of the target route, the destination of the target route, and the travel date of the target route;

[0120] Based on the departure place and the destination of the target route, determine the target route attribute type corresponding to the target route, the target route attribute type includes a popular route, a common route and a depression route;

[0121] Obtain a first scoring value range and a first weight value that match the target route attribute type;

[0122] Based on the historical travel data of the target route, the travel date is analyzed to determine the target off-season and peak-season types corresponding to the travel date. The target off-season and peak-season types include peak season, normal season and off-season.

[0123] Obtain a second scoring value range and a second weight value that match the target off-season or peak-season type;

[0124] The first scoring value range, the first weight value, the second scoring value range and the second weight value are all input into the booking route scoring model for processing to obtain the score value of the current ticket order.

[0125] In some implementations of the embodiments of the present invention, the second acquisition module 203 is specifically used to:

[0126] If the numerical range corresponding to the score value of the current ticket order is the numerical range of the first gear, the obtained matching target execution strategy includes: after paying the order fee corresponding to the current ticket order, generating a ticket including a seat number corresponding to the current ticket order;

[0127] If the numerical range corresponding to the score value of the current ticket order is the numerical range of the second gear, the obtained matching target execution strategy includes: using at least one verification code verification method for verification processing, and after the verification is passed, executing the processing of the current ticket order, the at least one verification code verification method includes: SMS verification code verification method, email verification code verification method, picture verification code verification method and voice verification code verification method;

[0128] If the numerical range corresponding to the score value of the current ticket order is the numerical range of the third gear, the matching target execution strategy obtained includes: using a warning reminder method to remind the ordering user, and after receiving the authorization processing instruction from the ordering user, executing the processing of the current ticket order.

[0129] In some implementations of the embodiments of the present invention, the determination module 204 is specifically used to:

[0130] Get historical ticket refund data;

[0131] If the historical ticket refund data shows that there are multiple ticket refund behaviors, and the number of ticket refunds is greater than or equal to the preset threshold, the user attribute of the ordering user is determined to be a blacklist user; otherwise, the user attribute of the ordering user is determined to be a whitelist user.

[0132] In some implementations of the embodiments of the present invention, the interception module 205 is specifically used to:

[0133] When it is determined that the user attribute of the ordering user is a blacklist user, the order blocking period is obtained, and all first ticketing orders placed by the ordering user within the order blocking period are obtained;

[0134] All first ticket orders are determined as malicious seat-occupying orders, and any first ticket order is intercepted.

[0135] In some implementations of the embodiments of the present invention, the interception module 205 is specifically used to:

[0136] When it is determined that the user attribute of the ordering user is a blacklist user, all second ticketing orders placed by the ordering user within any time period are obtained;

[0137] All second ticket orders are identified as malicious seat-occupying orders, and any second ticket order is intercepted.

[0138] In some implementations of the embodiments of the present invention, the apparatus 200 for processing airline ticket orders provided by the embodiments of the present invention is based on the same inventive concept as the method for processing airline ticket orders provided by the aforementioned embodiments of the present invention and has the same beneficial effects.

[0139] Example 3

[0140] The embodiment of the present invention provides a system for processing airline ticket orders, which includes a management subsystem, a strategy subsystem and an airline ticket order processing device.

[0141] The functions of the above management subsystem are: responsible for maintaining and managing information such as route areas and flight cycles, special flights, member blacklists and whitelists, etc.

[0142] The description of various management functions of the management subsystem is as follows:

[0143] Basic route information management:

[0144] Responsible for managing basic route information, including hot routes, ordinary routes, and low-lying routes, based on route departure and destination information, and supporting EXCEL table import, batch update and deletion, etc. It is also responsible for managing the off-season, normal season, and peak season attributes of routes, and supporting EXCEL table import, batch update and deletion, etc.

[0145] Special flight management:

[0146] In addition to basic route information management, it is also possible to carry out refined management of specific flights of airlines and implement special target execution strategies. For example, especially popular flights may only have a payment period of 5 minutes, or reservations may require a mobile phone verification code verification, etc. Special flight management gives airlines personalized control capabilities beyond automatic calculations on the platform.

[0147] Member blacklist and whitelist management:

[0148] Responsible for managing the blacklist and whitelist based on the member attributes of the airline platform. The whitelist is manually added by the administrator and generally includes the member's unique ID, order information, whitelist ID, etc. The blacklist can be added by the administrator or automatically generated by the calculation engine. Both the blacklist and whitelist can be deleted and modified in batches through the background, and log records are retained.

[0149] The functions of the above-mentioned strategy subsystem are: to calculate the payment ticketing rate by accessing the airline's access orders, to be responsible for route scoring, matching strategies and execution strategies, and to access airline members and extract relevant information.

[0150] The description of the strategy subsystem is as follows:

[0151] System access layer: responsible for accessing the airline sales platform, extracting the platform's order information and member information into the airline ticket order processing system, and also ensuring transmission security and data security. If the marketing system has a blacklist or whitelist, the list can be synchronized to the airline ticket order processing system.

[0152] Index calculation engine: The calculation engine can calculate the proportion of a member's paid ticketing orders, canceled orders, and total orders based on the order information extracted from the airline sales platform. Different strategies can be configured for different proportions. Members with too high cancellation orders and no paid unticketed orders can be automatically added to the blacklist, and the relevant proportions are configurable.

[0153] Route scoring module: Based on the basic flight information in the background, the flight information is scored. Popular routes are scored high, with scores of 8 to 10 points, ordinary routes are scored medium, with scores of 4 to 7 points, and low-lying routes are scored low, with scores of 1 to 3 points. The overall route attribute score accounts for 70%, and the percentage can be configured. Analyze the travel date of the flight and divide the travel date into peak season, flat season, and off-season. A high score in the peak season can get 8-10 points, a medium score in the flat season can get 4 to 7 points, and a low score in the off-season can get 1 to 3 points. The date ratio accounts for 30%, and the percentage can be configured.

[0154] Strategy matching module: Different target execution strategies are matched according to different route scores. The target execution strategies are divided into three categories: popular routes have a high degree of protection, while unpopular routes have a low degree of protection. Special flights configured by airlines apply special target execution strategies to avoid malicious seat occupation in a timely and targeted manner.

[0155] API (Application Programming Interface) is an interface provided to the airline marketing platform. The platform can call the route ticket order processing system through this set of interfaces. The marketing platform inputs relevant information, including booked flights, departure places, destinations, flight times, booking member unique identifiers, passenger information, etc., and obtains the code corresponding to the target execution strategy through the internal calculation engine of the route ticket order processing system to execute the target execution strategy through the airline marketing platform.

[0156] For the description of the processing device for the above-mentioned airline ticket order, please refer to the description of the same or similar parts mentioned above, which will not be repeated here.

[0157] Example 4

[0158] An embodiment of the present invention provides a computer device, including a memory and a processor, wherein the processor is used to read instructions stored in the memory, and the instructions can execute a method for processing an airline ticket order in any of the above method embodiments.

[0159] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, devices, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD ROM, optical storage, etc.) containing computer-usable program codes.

[0160] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (apparatus), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0161] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0162] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0163] Example 5

[0164] This embodiment provides a computer-readable storage medium, wherein the computer storage medium stores computer-executable instructions, and the computer-executable instructions can execute a method for processing a flight ticket order in any of the above method embodiments. The storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), a flash memory, a hard disk drive (HDD), or a solid state drive (SSD), etc.; the storage medium can also include a combination of the above types of memory.

[0165] Obviously, the above embodiments are merely examples for the purpose of clear explanation, and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived therefrom are still within the scope of protection of the invention.

Claims

1. A method for processing airline ticket orders, characterized in that: The method comprises: In response to receiving a current ticket order for a target route, obtaining associated data of the current ticket order of the ordering user within a first preset time period, and obtaining a booking route scoring model; Scoring the current ticket order based on the associated data of the target route within the first preset time period and the booking route scoring model to obtain a score value of the current ticket order; Get the target execution strategy that matches the value range of the score value of the current ticket order; Determine the user attribute of the ordering user based on the historical ticket refund data of the ordering user within the second preset time period, wherein the user attribute of the ordering user includes: the ordering user is a blacklist user, or the ordering user is a whitelist user; When it is determined that the user attribute of the ordering user is a blacklist user, the current ticket order is intercepted; When it is determined that the user attribute of the ordering user is a whitelist user, the current ticket order is processed according to the target execution strategy to obtain a corresponding processing result.

2. The processing method according to claim 1, characterized in that: Scoring the current ticket order based on the associated data of the current ticket order within the first preset time period and the booking route scoring model to obtain a score value of the current ticket order includes: Acquire the associated data of the current ticket order within the first preset time period, wherein the associated data of the current ticket order includes the departure place of the target route, the destination of the target route, and the travel date of the target route; Determine a target route attribute type corresponding to the target route based on the departure place of the target route and the destination of the target route, wherein the target route attribute type includes a popular route, a common route and a depression route; Acquire a first scoring value range and a first weight value matching the target route attribute type; Based on the historical travel data of the target route, the travel date is analyzed to determine the target off-season and peak-season type corresponding to the travel date, wherein the target off-season and peak-season type includes peak season, normal season and off-season; Acquire a second scoring value range and a second weight value matching the target off-season or peak-season type; The first scoring value range, the first weight value, the second scoring value range and the second weight value are all input into the booking route scoring model for processing to obtain the score value of the current ticket order.

3. The processing method according to claim 1, characterized in that: The step of obtaining a target execution strategy that matches a numerical range to which the score value of the current ticket order belongs includes: If the numerical range corresponding to the score value of the current ticket order is the numerical range of the first gear, the obtained matching target execution strategy includes: after paying the order fee corresponding to the current ticket order, generating a ticket including a seat number corresponding to the current ticket order; If the numerical range corresponding to the score value of the current ticket order is the numerical range of the second gear, the obtained matching target execution strategy includes: using at least one verification code verification method for verification processing, and after the verification is passed, executing the processing of the current ticket order, the at least one verification code verification method includes: SMS verification code verification method, email verification code verification method, picture verification code verification method and voice verification code verification method; If the numerical range corresponding to the score value of the current ticket order is the numerical range of the third gear, the obtained matching target execution strategy includes: using a warning reminder method to remind the ordering user, and after receiving the authorization processing instruction of the ordering user, executing the processing of the current ticket order.

4. The processing method according to claim 1, characterized in that: The determining the user attribute of the ordering user based on the historical ticket refund data of the ordering user within the second preset time period includes: Obtaining the historical ticket refund data; If the historical ticket refund data shows that there are multiple ticket refund behaviors, and the number of ticket refunds is greater than or equal to a preset threshold, the user attribute of the ordering user is determined to be a blacklist user; otherwise, the user attribute of the ordering user is determined to be a whitelist user.

5. The processing method according to claim 1, characterized in that: When it is determined that the user attribute of the ordering user is a blacklist user, intercepting the current ticket order includes: When it is determined that the user attribute of the ordering user is a blacklist user, an order blocking period is obtained, and all first ticket orders placed by the ordering user within the order blocking period are obtained; All first ticket orders are determined as malicious seat-occupying orders, and any first ticket order is intercepted.

6. The processing method according to claim 1, characterized in that: When it is determined that the user attribute of the ordering user is a blacklist user, intercepting the current ticket order includes: When it is determined that the user attribute of the ordering user is a blacklist user, all second ticketing orders placed by the ordering user within any time period are obtained; All second ticket orders are identified as malicious seat-occupying orders, and any second ticket order is intercepted.

7. A device for processing airline ticket orders, characterized in that: The device: A first acquisition module, configured to, in response to receiving a current ticket order for a target route, acquire associated data of the current ticket order of an ordering user within a first preset time period, and acquire a booking route scoring model; A scoring module, configured to score the current ticket order based on the associated data of the target route within the first preset time period and the booking route scoring model, and obtain a score value of the current ticket order; A second acquisition module is used to acquire a target execution strategy that matches the value range to which the score value of the current ticket order belongs; A determination module, configured to determine a user attribute of the ordering user based on historical ticket refund data of the ordering user within a second preset time period, wherein the user attribute of the ordering user includes: the ordering user is a blacklist user, or the ordering user is a whitelist user; An interception module, used to intercept the current ticket order when it is determined that the user attribute of the ordering user is a blacklist user; The processing module is used to process the current ticket order according to the target execution strategy to obtain a corresponding processing result when it is determined that the user attribute of the ordering user is a whitelist user.

8. The processing device according to claim 7, characterized in that The scoring module is specifically used for: Acquire the associated data of the current ticket order within the first preset time period, wherein the associated data of the current ticket order includes the departure place of the target route, the destination of the target route, and the travel date of the target route; Based on the departure place of the target route and the destination of the target route, determining the target route attribute type to which the target route belongs, the target route attribute type including a popular route, a common route and a depression route; Acquire a first scoring value range and a first weight value matching the target route attribute type; Based on the historical travel data of the target route, the travel date of the current ticket order is analyzed to determine the target off-season or peak-season type to which the travel date belongs, wherein the target off-season or peak-season type includes peak season, normal season and off-season; Acquire a second scoring value range and a second weight value matching the target off-season or peak-season type; The first scoring value range, the first weight value, the second scoring value range and the second weight value are all input into the booking route scoring model for processing to obtain the score value of the current ticket order.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and the computer program is used to execute the processing method according to any one of claims 1 to 6.

10. An electronic device, characterized in that: The electronic device comprises: processor; a memory for storing executable instructions for the processor; The processor is used to read the executable instructions from the memory and execute the executable instructions to implement the processing method described in any one of claims 1 to 6.

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