A sold-out flight search display method, system, device and medium

Abstract

The present disclosure relates to the technical field of air flights, and particularly relates to a sold-out flight search display method, system, device and medium. A search request containing sold-out query preferences, personalization and dynamic reminder settings is obtained and a composite key value is generated; sold-out flights are filtered and deep analysis information is calculated; in combination with user historical travel data and associated service data, preference matching degree and associated service convenience are calculated to filter and prioritize sold-out flights; traffic, hotel, visa and other associated service adjustment suggestions are matched and generated; and according to the settings, a dynamic reminder task is bound and executed to release remaining tickets and provide early warning of alternative flights. The present disclosure converts the sold-out state into quantifiable decision information, provides deep and personalized one-stop travel solutions and real-time reminders for passengers, and provides data support for airlines and platforms to tap potential demand, optimize operations and precise marketing.

Description

Technical Field

[0001] This disclosure relates to the field of aviation flight technology, and in particular to a method, system, device and medium for searching and displaying sold-out flights. Background Technology

[0002] In current airline ticketing systems, when users search for flights, sold-out flights are often simply marked as sold out or not displayed in the search results at all. This approach has several drawbacks. On the one hand, passengers cannot fully understand the overall flight situation for a specific route and time period, making it difficult to make more flexible travel decisions. For example, they may not know if they can choose flights at nearby times or airports, nor can they determine if there are any potential ticket release opportunities for sold-out flights (such as refunds or rebooking). On the other hand, airlines and ticketing platforms cannot fully utilize the data on sold-out flights for precise marketing and operational strategy adjustments, such as promptly arranging extra flights for popular but sold-out routes, failing to fully leverage the information to uncover potential customer demand and optimize resource allocation.

[0003] The shortcomings of existing technologies are as follows: First, the information display is limited, only informing users of flight sell-out status without providing in-depth information such as historical ticket sales speed, comparison of sell-out trends of other flights on the same route, or cabin class distribution of sold-out flights. This makes it difficult for users to predict the popularity of a route and whether it is necessary to urgently book alternative flights. Second, there is a lack of personalized adaptation. Sold-out flight information is not filtered and prioritized based on users' historical travel preferences (such as whether they frequently choose low-cost carriers, whether they prefer direct flights, and their preferred cabin class). Users may be overwhelmed by a large number of irrelevant sold-out flight information, which reduces search efficiency. Third, there is insufficient data linkage. Sold-out flight information is not integrated with related data such as airport transportation information, hotel booking information, and visa processing time. Even if users know that a flight is sold out, they still need to spend extra time checking for adjustments to related services. Fourth, there is a lack of dynamic feedback mechanisms. Users cannot receive real-time notifications of available tickets for sold-out flights or price fluctuation warnings for alternative flights on the same route. Users need to repeatedly refresh the search page to obtain the latest information, resulting in a poor user experience.

[0004] Furthermore, from an airline operations perspective, existing technology can only passively receive sold-out results and cannot use search data for sold-out flights to analyze potential user travel needs (such as demand gaps in specific time periods or cabin classes), nor can it accurately identify operational optimizations (such as whether to increase flight frequency on specific routes or adjust cabin layouts). From the ticketing platform's perspective, the failure to utilize sold-out flight information to build more comprehensive user profiles limits the effectiveness of targeted marketing and prevents the provision of more targeted travel solutions to users. Summary of the Invention

[0005] To address the aforementioned issues, this disclosure provides a method, system, device, and medium for searching and displaying sold-out flights, which solves problems such as insufficient processing of sold-out flight information, single dimension, lack of personalization, poor data linkage, and lack of dynamic feedback in existing flight search and display methods.

[0006] Firstly, a method for searching and displaying sold-out flights includes: Obtain the user's flight search request, which includes the first search criteria, preferences for sold-out flights, personalized settings, and dynamic alert settings; Parse the request, extract parameters from the first query condition, sold-out flight query preference, personalized settings, and dynamic reminder settings, and generate composite key values; Based on the composite key value, query the entire set of flights that meet the first query condition and the preference for sold-out flights, obtain the inventory status of each flight, and filter out sold-out flights from the entire set of flights based on the inventory status. It calls the user profile database to obtain the user's historical travel data, and calls the related service database to obtain related service data; Perform in-depth analysis and calculation on sold-out flights to generate in-depth analysis information, which includes at least historical ticket sales speed, comparison coefficient of sold-out trend of the same route, cabin distribution sold-out status and probability of remaining ticket release. Based on users' historical travel data, related service data, and in-depth analysis information, the convenience of related services and the degree of matching with users' historical travel preferences for sold-out flights are calculated. Based on the degree of matching with users' historical travel preferences, the convenience of related services, and the probability of remaining tickets being released, sold-out flights are filtered and prioritized. Match the takeoff and landing information of sold-out flights with related service data to generate suggestions for adjusting related services; Based on the dynamic reminder settings, add the sold-out flights and alternative flights that need to be monitored to the reminder task queue for real-time listening; It integrates available flight information, sorted sold-out flight information, and related service adjustment suggestions to generate search results data, returns the search results data to the user, and executes dynamic reminders based on the monitoring results of the reminder task queue.

[0007] Specifically, the matching degree with the user's historical travel preferences is calculated by matching each attribute of the current sold-out flight with the corresponding attributes in the user's historical travel data, such as airline selection, direct flight preference, cabin class, take-off and landing time preference, on-time rate preference, and code-share exclusion records, and then normalizing it to a score of 0-100.

[0008] The convenience of related services is assessed based on the availability of sold-out flights, with each of the following: airport transportation, hotel booking, and visa processing. The scores are weighted at 0.5 for transportation, 0.3 for hotels, and 0.2 for visa processing, resulting in a score of 0–100.

[0009] Furthermore, in-depth analysis and calculations were performed on the sold-out flights, including: Historical ticket sales speed is obtained by statistically analyzing the average ticket sales completion time for the same travel period within a recent preset timeframe for that flight. The comparison coefficient of the sell-out trend of the same route is obtained as follows: Select other flights within a preset number of days before and after the same departure and arrival points and departure date, and calculate the comparison value between the current percentage of remaining tickets for each flight and the historical sell-out progress of the target sell-out flight; The cabin availability information is as follows: The cabins are categorized and the order of their sell-out times and the percentage of remaining cabins are displayed, with a note indicating whether some cabins are sold out or the entire flight is sold out. The probability of remaining tickets being released is obtained as follows: based on the refund data and refund time distribution of the flight within a preset time period, combined with the current time until departure, it is calculated and divided into three probability levels: high, medium, and low.

[0010] Furthermore, sold-out flights are screened and prioritized, including: Based on users' historical travel data, such as airline selection, direct flight preference, cabin class preference, and shared flight rejection records, sold-out flights that do not match the user's preferences are filtered out. The overall score for sold-out flights is calculated using the following formula: Overall Score = Matching degree with user's historical travel preferences × First weight + Probability of remaining tickets being released × Second weight + Convenience of related services × Third weight; Sold-out flights are sorted from highest to lowest based on their overall scores.

[0011] Furthermore, it also includes customized displays based on the user's travel type: Identify the user's travel type. If the user is a business traveler, prioritize displaying on-time performance and airport lounge configuration information in the sold-out flight information. For tourists, the information on sold-out flights will prioritize displaying the convenience of transportation connections between the departure and arrival airports and scenic spots and hotels, as well as baggage allowance information.

[0012] Furthermore, the associated service data includes airport traffic information, hotel booking information, and visa processing information; Generate suggestions for adjusting related services, including: Airport transportation is linked to match the departure and arrival airports of sold-out flights and alternative flights with their corresponding transportation timetables. If the arrival time of the alternative flight is later than the last bus time of the original transportation mode, a transportation plan adjustment prompt is generated. The hotel booking is linked. If a user triggers a hotel-related request, the system will recommend nearby hotels that support free cancellation based on the arrival time of the alternative flight, and indicate the latest check-in time and distance from the airport. The visa processing mechanism is linked to international flights. If the timing of the alternative flight causes a conflict with the visa application deadline, a notification will be generated indicating that the visa grace period is insufficient.

[0013] Furthermore, dynamic reminders are executed based on the monitoring results of the reminder task queue, including: Ticket release reminder: When a sold-out flight is detected to have tickets canceled, resulting in the release of remaining tickets, a notification will be sent according to the reminder method set by the user. Alternate flight alerts are sent when the number of remaining tickets for flights on the same route falls below a ticket threshold, or when the price increases by more than a certain amount within a preset time. Once the user has viewed the alert, it will not be sent again.

[0014] Furthermore, search result data is returned to the user, including: Return sold-out flight information using a preset data structure, which includes a sold-out status indicator, a detailed array of sold-out cabins, in-depth analysis objects, associated service objects, personalized comprehensive scores, and an array of operation entry points. The in-depth analysis includes fields such as historical ticket sales speed, comparison coefficient of sell-out trend for the same route, probability of remaining tickets being released, and probability level; the operation entry array includes the entry to unfollow remaining tickets and the entry to view alternative flights.

[0015] Secondly, a system for searching and displaying sold-out flights includes: The request receiving module is used to obtain the user's flight search request. The request includes the first search criteria, sold-out flight search preferences, personalized settings, and dynamic reminder settings. The key value generation module is used to parse the request, extract parameters from the first query condition, sold-out flight query preferences, personalized settings, and dynamic reminder settings, and generate composite key values; The sold-out flight search module is used to query the entire set of flights that meet the first query condition and sold-out flight query preference based on composite key values, obtain the inventory status of each flight, and filter sold-out flights from the entire set of flights based on the inventory status. The data acquisition module is used to call the user profile database to obtain the user's historical travel data, and to call the related service database to obtain related service data; The in-depth analysis module is used to perform in-depth analysis and calculation on sold-out flights and generate in-depth analysis information. The in-depth analysis information includes at least the historical ticket sales speed, the comparison coefficient of the sold-out trend of the same route, the sold-out status of cabin allocation, and the probability of releasing remaining tickets. The personalized adaptation module is used to calculate the convenience of associated services and the matching degree with the user's historical travel preferences for sold-out flights based on the user's historical travel data, related service data and in-depth analysis information. Based on the matching degree with the user's historical travel preferences, the convenience of associated services and the probability of remaining tickets being released, the sold-out flights are filtered and prioritized. The data linkage module is used to match the takeoff and landing information of sold-out flights with related service data and generate suggestions for adjusting related services. The dynamic reminder module is used to add sold-out flights and alternative flights to the reminder task queue for real-time monitoring based on the dynamic reminder settings. The output module is used to integrate available flight information, sorted sold-out flight information, and related service adjustment suggestions to generate search results data, return the search results data to the user, and execute dynamic reminders based on the monitoring results of the reminder task queue.

[0016] Thirdly, an electronic device includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, which stores computer programs; When a processor executes a computer program stored in memory, it implements the aforementioned method for searching and displaying sold-out flights.

[0017] Fourthly, a computer-readable storage medium stores a computer program that, when executed by a processor, implements the aforementioned method for searching and displaying sold-out flights.

[0018] This disclosure includes at least the following beneficial effects: This disclosure transforms sold-out status into quantifiable decision-making information, providing travelers with in-depth, personalized, one-stop travel solutions and real-time alerts, while also providing data support for airlines and platforms to uncover potential demand, optimize operations, and conduct precise marketing.

[0019] This disclosure improves the completeness, depth, and usability of flight information display, better meets passengers' personalized travel needs, and provides richer data support for the operational decisions of airlines and sales platforms.

[0020] Other features and advantages of this disclosure will be set forth in the following description and will be apparent in part from the description or may be learned by practicing the disclosure. The objects and other advantages of this disclosure may be realized and obtained by means of the structures pointed out in the description and the accompanying drawings. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of this disclosure or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a schematic diagram of the method flow according to an embodiment of the present disclosure; Figure 2 This is a schematic diagram illustrating the system principle of an embodiment of the present disclosure; Figure 3 This is a schematic diagram of the electronic device structure according to an embodiment of the present disclosure. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of the embodiments of this disclosure clearer, the technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, and not all embodiments. Based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.

[0024] like Figure 1 As shown, a method for searching and displaying sold-out flights includes: Obtain the user's flight search request, which includes the first search criteria, preferences for sold-out flights, personalized settings, and dynamic alert settings; Parse the request, extract parameters from the first query condition, sold-out flight query preference, personalized settings, and dynamic reminder settings, and generate composite key values; Based on the composite key value, query the entire set of flights that meet the first query condition and the preference for sold-out flights, obtain the inventory status of each flight, and filter out sold-out flights from the entire set of flights based on the inventory status. It calls the user profile database to obtain the user's historical travel data, and calls the related service database to obtain related service data; Perform in-depth analysis and calculation on sold-out flights to generate in-depth analysis information, which includes at least historical ticket sales speed, comparison coefficient of sold-out trend of the same route, cabin distribution sold-out status and probability of remaining ticket release. Based on users' historical travel data, related service data, and in-depth analysis information, the convenience of related services and the degree of matching with users' historical travel preferences for sold-out flights are calculated. Based on the degree of matching with users' historical travel preferences, the convenience of related services, and the probability of remaining tickets being released, sold-out flights are filtered and prioritized. Match the takeoff and landing information of sold-out flights with related service data to generate suggestions for adjusting related services; Based on the dynamic reminder settings, add the sold-out flights and alternative flights that need to be monitored to the reminder task queue for real-time listening; It integrates available flight information, sorted sold-out flight information, and related service adjustment suggestions to generate search results data, returns the search results data to the user, and executes dynamic reminders based on the monitoring results of the reminder task queue.

[0025] In practice: When searching for flights, this publication will not only display basic information about available flights (such as flight number, departure and arrival times, and prices), but also basic information and in-depth analysis information about sold-out flights (excluding prices). It will also integrate and present information based on user preferences and related service data, and provide dynamic reminders.

[0026] The problem addressed is that passengers can easily access comprehensive information (basic information + in-depth analysis) on sold-out flights, quickly filter relevant information based on their preferences, simultaneously receive suggestions for adjustments to related services, and receive real-time dynamic alerts. This allows them to fully understand the overall situation and trends of flights on specific routes and during specific time periods, enabling them to make more flexible and efficient travel decisions. Airlines and ticketing platforms can use the search data collected through this method to uncover potential demand and optimize operational strategies and marketing plans. Solving this problem primarily relies on a sold-out flight search module, a personalization adaptation module, a data linkage module, and a dynamic alert module. Among these, the sold-out flight search module is the core foundational module, while the other modules are innovative extensions.

[0027] In one embodiment, in-depth analysis and calculation are performed on sold-out flights, including: Historical ticket sales speed is obtained by statistically analyzing the average ticket sales completion time for the same travel period within a recent preset timeframe for that flight. The comparison coefficient of the sell-out trend of the same route is obtained as follows: Select other flights within a preset number of days before and after the same departure and arrival points and departure date, and calculate the comparison value between the current percentage of remaining tickets for each flight and the historical sell-out progress of the target sell-out flight; The cabin availability information is as follows: The cabins are categorized and the order of their sell-out times and the percentage of remaining cabins are displayed, with a note indicating whether some cabins are sold out or the entire flight is sold out. The probability of remaining tickets being released is obtained as follows: based on the refund data and refund time distribution of the flight within a preset time period, combined with the current time until departure, it is calculated and divided into three probability levels: high, medium, and low.

[0028] In one embodiment, screening and prioritizing sold-out flights includes: Based on users' historical travel data, such as airline selection, direct flight preference, cabin class preference, and shared flight rejection records, sold-out flights that do not match the user's preferences are filtered out. The overall score for sold-out flights is calculated using the following formula: Overall Score = Matching degree with user's historical travel preferences × First weight + Probability of remaining tickets being released × Second weight + Convenience of related services × Third weight; Sold-out flights are sorted from highest to lowest based on their overall scores.

[0029] In one embodiment, the system also includes a customized display based on the user's travel type: Identify the user's travel type. If the user is a business traveler, prioritize displaying on-time performance and airport lounge configuration information in the sold-out flight information. For tourists, the information on sold-out flights will prioritize displaying the convenience of transportation connections between the departure and arrival airports and scenic spots and hotels, as well as baggage allowance information.

[0030] In one embodiment, the associated service data includes airport traffic information, hotel booking information, and visa processing information; Generate suggestions for adjusting related services, including: Airport transportation is linked to match the departure and arrival airports of sold-out flights and alternative flights with their corresponding transportation timetables. If the arrival time of the alternative flight is later than the last bus time of the original transportation mode, a transportation plan adjustment prompt is generated. The hotel booking is linked. If a user triggers a hotel-related request, the system will recommend nearby hotels that support free cancellation based on the arrival time of the alternative flight, and indicate the latest check-in time and distance from the airport. The visa processing mechanism is linked to international flights. If the timing of the alternative flight causes a conflict with the visa application deadline, a notification will be generated indicating that the visa grace period is insufficient.

[0031] In one embodiment, executing dynamic reminders based on the monitoring results of the reminder task queue includes: Ticket release reminder: When a sold-out flight is detected to have tickets canceled, resulting in the release of remaining tickets, a notification will be sent according to the reminder method set by the user. Alternate flight alerts are sent when the number of remaining tickets for flights on the same route falls below a ticket threshold, or when the price increases by more than a certain amount within a preset time. Once the user has viewed the alert, it will not be sent again.

[0032] In one embodiment, returning search result data to the user includes: Return sold-out flight information using a preset data structure, which includes a sold-out status indicator, a detailed array of sold-out cabins, in-depth analysis objects, associated service objects, personalized comprehensive scores, and an array of operation entry points. The in-depth analysis includes fields such as historical ticket sales speed, comparison coefficient of sell-out trend for the same route, probability of remaining tickets being released, and probability level; the operation entry array includes the entry to unfollow remaining tickets and the entry to view alternative flights.

[0033] like Figure 2 As shown, a system for searching and displaying sold-out flights includes: The request receiving module is used to obtain the user's flight search request. The request includes the first search criteria, sold-out flight search preferences, personalized settings, and dynamic reminder settings. The key value generation module is used to parse the request, extract parameters from the first query condition, sold-out flight query preferences, personalized settings, and dynamic reminder settings, and generate composite key values; The sold-out flight search module is used to query the entire set of flights that meet the first query condition and sold-out flight query preference based on composite key values, obtain the inventory status of each flight, and filter sold-out flights from the entire set of flights based on the inventory status. The data acquisition module is used to call the user profile database to obtain the user's historical travel data, and to call the related service database to obtain related service data; The in-depth analysis module is used to perform in-depth analysis and calculation on sold-out flights and generate in-depth analysis information. The in-depth analysis information includes at least the historical ticket sales speed, the comparison coefficient of the sold-out trend of the same route, the sold-out status of cabin allocation, and the probability of releasing remaining tickets. The personalized adaptation module is used to calculate the convenience of associated services and the matching degree with the user's historical travel preferences for sold-out flights based on the user's historical travel data, related service data and in-depth analysis information. Based on the matching degree with the user's historical travel preferences, the convenience of associated services and the probability of remaining tickets being released, the sold-out flights are filtered and prioritized. The data linkage module is used to match the takeoff and landing information of sold-out flights with related service data and generate suggestions for adjusting related services. The dynamic reminder module is used to add sold-out flights and alternative flights to the reminder task queue for real-time monitoring based on the dynamic reminder settings. The output module is used to integrate available flight information, sorted sold-out flight information, and related service adjustment suggestions to generate search results data, return the search results data to the user, and execute dynamic reminders based on the monitoring results of the reminder task queue.

[0034] In practice, the implementation process of this system and method corresponds one-to-one.

[0035] Sold-out Flight Search Module: This is a core module designed to provide basic and in-depth analysis of sold-out flights in the flight search results. This module can be triggered by setting the list of airlines and preferences for sold-out flights in the request.

[0036] Personalized Adaptation Module: Based on users' historical travel data and current search preferences, the module filters, prioritizes, and customizes the display of sold-out flight information to improve the efficiency of users obtaining information.

[0037] Data linkage module: Integrates sold-out flight information with related service data such as airport transportation, hotel booking, and visa processing, providing users with a one-stop travel solution reference.

[0038] Dynamic Alert Module: Monitors the release of remaining tickets for sold-out flights in real time, as well as the price and sold-out status of alternative flights on the same route, and pushes personalized alerts based on user settings.

[0039] like Figure 3 As shown, this disclosure provides an electronic device, including a processor 301, a communication interface 302, a memory 303, and a communication bus 304, wherein the processor 301, the communication interface 302, and the memory 303 communicate with each other through the communication bus 304; Memory 303 stores computer programs; The processor 301 implements the above method when executing a computer program stored in the memory 303.

[0040] This disclosure provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0041] The computer-readable storage medium may be included in the device / apparatus described in the above embodiments; or it may exist independently and not assembled into the device / apparatus. The computer-readable storage medium carries one or more programs that, when executed, implement the method according to the embodiments of this disclosure.

[0042] According to embodiments of this disclosure, the computer-readable storage medium can be a non-volatile computer-readable storage medium, such as including, but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this disclosure, the computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0043] To enable those skilled in the art to better understand this disclosure, the principles of this disclosure are explained as follows: This disclosure acquires search requests containing sold-out query preferences, personalized settings, and dynamic alert settings, and generates composite key values; filters sold-out flights and calculates in-depth analysis information; combines user historical travel data and related service data to calculate preference matching degree and related service convenience, and filters and prioritizes sold-out flights; generates adjustment suggestions for related services such as transportation, hotels, and visas; and binds dynamic alert tasks according to settings and executes alerts for remaining tickets and alternative flights. This disclosure transforms sold-out status into quantifiable decision-making information, providing passengers with in-depth, personalized, one-stop travel solutions and real-time alerts, while providing data support for airlines and platforms to explore potential demand, optimize operations, and conduct precise marketing.

[0044] Step 1: The user initiates a request; Users initiate flight search requests through ticketing platform apps, websites, and other channels. These requests may include, but are not limited to: First search criteria: departure date, origin, destination, number of travelers, and cabin class preference; Sold-out flight search preferences: search airline list, whether code-share flights are allowed, connecting flight type preferences (online / interline); Personalized settings: Whether to filter results based on historical travel preferences, and prioritize the information dimensions displayed (such as on-time rate, transportation connections, etc.). Dynamic alert settings: Whether to enable ticket availability alerts, whether to receive alternative flight alerts, and alert method (SMS / APP push).

[0045] Step 2: The system generates composite key values; The system parses the user request and extracts the following information to generate composite key values: Basic dimensions: departure date, origin, destination, cabin class preference; Sold-out query dimensions: query airline list, code-share permission status, and intermodal transport type preference; Personalization dimensions: User ID (linked to historical travel data), priority information display dimensions; Reminder dimensions: Remaining ticket reminder switch, early warning receiving switch, and reminder method.

[0046] The settings for the fields related to sold-out flight search preferences in the interface are shown in the table below. avJourneysOption and carrier are required fields; the remaining fields are filled in as needed. New personalized settings and reminder settings fields have been added to meet diverse user needs. The fields are shown in Table 1.

[0047] Table 1

[0048] Extended Scenario Examples Scenario 1: Business user A (who frequently selects a certain flight, prefers direct flights, prioritizes on-time performance and VIP lounge access, and needs ticket availability alerts) searches for sold-out flights on the destination route and for the corresponding time. Code-sharing is not allowed, and connecting flights are only available online.

[0049] Scenario 2: Travel user B (no fixed airline preference, not opposed to code-sharing, prioritizes transportation and hotels, does not need ticket availability reminders), searches for destination routes and sold-out flights for corresponding times, connecting flights are allowed online and interline.

[0050] Step 3: Data query and integration; The system completes data query and preliminary processing step by step based on composite key values: Call the flight data database, schedule system, and AV system to query the complete set of flights that meet the first query condition and the preference for sold-out flights, and obtain the basic information of each flight (airline, flight number, departure and arrival time, aircraft type, cabin class distribution, etc.) and inventory status (whether sold out, partial cabin class sold out, etc.). Access the user profile database to obtain the historical travel data of the user who initiated the request (airline selection records, travel type, preferred cabin class, whether they are opposed to shared flights, etc. in the past year). Call the associated service database to obtain related information such as airport transportation, nearby hotels, and visa processing (international flights) for the corresponding flight route; The entire set of retrieved flights is filtered to extract sold-out flights (including those sold out entirely and those with partial cabin availability) for further in-depth processing.

[0051] Step 4: In-depth processing of sold-out flights; In-depth analysis of indicator calculation: According to preset rules, for each sold-out flight, calculate the historical ticket sales speed, the comparison coefficient of the sold-out trend of the same route, the sold-out status of cabin class distribution, the probability and level of remaining ticket release; Example: For a sold-out flight, the average ticket completion time for the same period in the past 3 months is 48 hours. The sell-out trend comparison coefficient for the same route is 0.92. The sell-out order of cabin classes is Business Class → Economy Class → First Class (currently all sold out). The cancellation rate in the past 6 months is 8%. There are currently 72 hours left before departure, and the probability of releasing remaining tickets is 65% (high class). Personalized adaptation: Based on users' historical travel data, sold-out flights are filtered and prioritized, and displayed according to comprehensive scores; Example: When user A (who frequently selects a certain flight and prefers business class) searches, the flight with the best overall score of 92 points is ranked first due to matching airline and cabin class preferences; another sold-out flight with a poor airline matching score of 65 points is ranked lower. Related service matching: Link the departure and arrival times and airport information of sold-out flights with related service data to generate transportation connection suggestions, hotel recommendations, etc. Example: When a flight is sold out, recommend alternative flights and simultaneously display the last subway train time after the flight arrives at the airport, as well as 3 hotels within 3 kilometers that offer free cancellation (distance and price are indicated).

[0052] Step 5: Dynamic reminder binding; For users who have enabled the remaining ticket release reminder, the system stores information such as the flight number of the sold-out flight, user ID, and reminder method in the reminder task queue, and monitors the system's inventory changes in real time; for alternative flight alerts, the system binds the inventory and price data of available flights on the same route and sets trigger thresholds (remaining tickets ≤ 20% or price increase ≥ 30%).

[0053] Step 6: Returning and displaying results; The system integrates the following information to generate the final search results and return them to the user: Available flight information: Flight number, departure and arrival times, price, number of tickets remaining, etc. will be displayed according to the original rules; Sold-out flight information: Displayed in personalized sorting, each sold-out flight includes: Basic information: airline, flight number, departure time, arrival time, aircraft type, on-time performance rate; In-depth analysis of information: historical ticket sales speed, comparison of sell-out trends for the same route (visualized with bar charts), sell-out status of cabin classes, probability and tier of remaining tickets; Related service information: transportation suggestions, hotel recommendations (if selected by the user), visa application tips (international flights); Operation entry points: "Follow available tickets" (if already enabled, "Unfollow" will be displayed) and "View alternative flights"; Reminder settings status: Clearly indicate the on / off status of current available ticket reminders and alternative flight alerts, and allow users to modify them directly on the results page.

[0054] Step 7: Dynamically remind users to execute; Remaining Ticket Release Alert: When the system detects that there are remaining tickets available for a sold-out flight, the system retrieves the user information corresponding to the flight from the alert task queue and sends a notification according to the set alert method. Example of notification content: [XX Ticketing] 2 economy class tickets have been released for the flight you are interested in. Book now: XX link, valid for 30 minutes; Alternative Flight Alert: When the available flights on the same route trigger the alert threshold, the system generates an alert notification. Example: [XX Ticketing] Only 5 flights remain available for the route you searched for, and the price has increased by 35% compared to 1 hour ago. We recommend alternative flights. Click to book: XX link; Reminder status update: After a user clicks on a notification or modifies reminder settings on the results page, the system updates the reminder task queue in real time to ensure that the reminder status is consistent with the user's operation.

[0055] The core logic of the sold-out flight search and display is as follows: The user initiates a request (including the first query condition, sold-out flight search preferences, personalized settings, and reminder on / off) → The system integrates the request information to generate composite key values ​​(first query condition + sold-out flight search parameters + user personalized tags) → The system calls the flight data database, schedule system, and AV system to obtain the complete flight set, inventory data, and basic information → The sold-out flight search module filters sold-out flights, extracts basic information, and calculates in-depth analysis indicators → The personalized adaptation module filters and sorts sold-out flight information according to user preferences → The data linkage module calls the related service database to match the related service information corresponding to sold-out flights → The dynamic reminder module binds the sold-out flights and alternative flights to be monitored according to user settings → The system integrates available flight information, processed sold-out flight information, related service information, and reminder settings results, and returns them to the user.

[0056] In addition to the Schedule system (flight planning) and AV system (flight inventory), the external systems involved in the query process include a new user profile database (storing users' historical travel preferences, search records, etc.) and a related service database (storing information such as airport buses, subways, nearby hotels, and visa processing times). The system needs to regularly synchronize data from all external systems to ensure data accuracy and timeliness.

[0057] The calculation rules for in-depth analysis indicators are as follows: Historical ticket sales speed: The average time (from the start of ticket sales to sell out) for the same travel period of this flight within the past 3 months is used as a reference indicator, and the unit is "hours".

[0058] Comparison of sell-out trends on the same route: Select other flights with the same origin-destination and departure date within 3 days before and after, calculate the proportion of the current remaining tickets for each flight to the total number of tickets, compare it with the historical sell-out progress of the target sold-out flight, and generate a trend comparison coefficient (0-1, the closer the coefficient is to 1, the faster the flight sells out and the higher the popularity).

[0059] Cabin availability: Classified by First Class, Business Class, and Economy Class (including Premium Economy), the system displays the order of sell-out times for each class, the percentage of remaining seats (if any), and clearly indicates whether some seats are sold out (rather than the entire flight).

[0060] Probability of remaining tickets being released: Based on the refund data of the flight over the past 6 months, the probability of remaining tickets being released is calculated by statistically analyzing the time period of refunds (such as within 24 hours or 48 hours before departure), the proportion of refunds to total tickets sold, and the current time remaining before departure. The probability is marked as high (≥60%), medium (30%-59%), and low (<30%).

[0061] The personalized adaptation rules are as follows: Filtering: Based on the user's historical travel data (such as the airlines selected in the past year, whether direct flights are frequently selected, preferred cabin class, whether they are averse to shared flights, etc.), filter out sold-out flights that do not match the user's preferences (for example, if the user never chooses low-cost carriers, then hide the sold-out information of low-cost carrier flights).

[0062] Priority ranking: Sold-out flights are ranked according to a comprehensive score (0-100 points) calculated based on "match with users' historical travel preferences (60% weight) + probability of remaining tickets being released (30% weight) + convenience of related services (10% weight)". The higher the score, the higher the ranking.

[0063] Customized display: For business travelers, prioritize displaying information such as the on-time rate of sold-out flights and airport lounge facilities; for leisure travelers, prioritize displaying information such as the convenience of transportation connections between the departure and arrival airports and scenic spots / hotels, and baggage allowance for sold-out flights.

[0064] The data linkage logic is as follows: Airport transportation linkage: Based on the departure and arrival airports of sold-out flights and the departure / arrival city area selected by the user, match the corresponding airport bus timetable, subway lines and last train times, estimated ride-hailing fares and waiting times, and mark "whether the transportation plan needs to be adjusted" (e.g., if the original plan was to take the subway, but the alternative flight arrives later than the last subway train, then prompt for adjustment).

[0065] Hotel booking integration: If the user has already linked their hotel booking information (or selected "Hotels to be synchronized" during the search), then based on the arrival time of the alternative flight, nearby hotels with free cancellation / rescheduling will be recommended, and the latest check-in time and distance from the airport will be indicated.

[0066] Visa processing linkage: For international flights, considering the visa processing time of the user's destination country, if the original travel time of a sold-out flight conflicts with the visa processing deadline, the system will recommend alternative flights and simultaneously prompt "Is there sufficient visa processing buffer period?"

[0067] The rules for triggering dynamic reminders are as follows: Remaining Ticket Release Alert: After a user selects "Follow Remaining Tickets," the system monitors the inventory changes of sold-out flights in real time. When the system reports that a flight has been canceled, resulting in the release of remaining tickets, it immediately notifies the user via SMS and APP push notification. The notification includes the flight number, the number of remaining tickets, and the booking link.

[0068] Alternative Flight Alert: When a user has not checked "Follow for Remaining Tickets" but the number of remaining tickets for the same route is ≤20% (or the price increases by ≥30% within 1 hour), an alert notification will be sent saying "Available flights for the same route are scarce, it is recommended to book as soon as possible," along with the best alternative flight recommendation.

[0069] Reminder frequency control: Reminders for available tickets for the same flight will be pushed a maximum of 3 times within 24 hours (first time, 6 hours later, and 12 hours later) to avoid disturbing users; Alternate flight alerts will only be pushed once, and will not be pushed again after the user clicks "Viewed".

[0070] Although the present disclosure has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present disclosure.

Claims

1. A method for searching and displaying sold-out flights, characterized in that, include: Obtain the user's flight search request, which includes the first search criteria, preferences for sold-out flights, personalized settings, and dynamic alert settings; Parse the request, extract parameters from the first query condition, sold-out flight query preference, personalized settings, and dynamic reminder settings, and generate composite key values; Based on the composite key value, query the entire set of flights that meet the first query condition and the preference for sold-out flights, obtain the inventory status of each flight, and filter out sold-out flights from the entire set of flights based on the inventory status. It calls the user profile database to obtain the user's historical travel data, and calls the related service database to obtain related service data; Perform in-depth analysis and calculation on sold-out flights to generate in-depth analysis information, which includes at least historical ticket sales speed, comparison coefficient of sold-out trend of the same route, cabin distribution sold-out status and probability of remaining ticket release. Based on users' historical travel data, related service data, and in-depth analysis information, the convenience of related services and the degree of matching with users' historical travel preferences for sold-out flights are calculated. Based on the degree of matching with users' historical travel preferences, the convenience of related services, and the probability of remaining tickets being released, sold-out flights are filtered and prioritized. Match the takeoff and landing information of sold-out flights with related service data to generate suggestions for adjusting related services; Based on the dynamic reminder settings, add the sold-out flights and alternative flights that need to be monitored to the reminder task queue for real-time listening; It integrates available flight information, sorted sold-out flight information, and related service adjustment suggestions to generate search results data, returns the search results data to the user, and executes dynamic reminders based on the monitoring results of the reminder task queue.

2. The method for searching and displaying sold-out flights according to claim 1, characterized in that, In-depth analysis and calculations were performed on sold-out flights, including: Historical ticket sales speed is obtained by statistically analyzing the average ticket sales completion time for the same travel period within a recent preset timeframe for that flight. The comparison coefficient of the sell-out trend of the same route is obtained as follows: Select other flights within a preset number of days before and after the same departure and arrival points and departure date, and calculate the comparison value between the current percentage of remaining tickets for each flight and the historical sell-out progress of the target sell-out flight; The cabin availability information is as follows: The cabins are categorized and the order of their sell-out times and the percentage of remaining cabins are displayed, with a note indicating whether some cabins are sold out or the entire flight is sold out. The probability of remaining tickets being released is obtained as follows: based on the refund data and refund time distribution of the flight within a preset time period, combined with the current time until departure, it is calculated and divided into three probability levels: high, medium, and low.

3. The method for searching and displaying sold-out flights according to claim 1, characterized in that, Screening and prioritizing sold-out flights, including: Based on users' historical travel data, such as airline selection, direct flight preference, cabin class preference, and shared flight rejection records, sold-out flights that do not match the user's preferences are filtered out. The overall score for sold-out flights is calculated using the following formula: Overall Score = Matching degree with user's historical travel preferences × First weight + Probability of remaining tickets being released × Second weight + Convenience of related services × Third weight; Sold-out flights are sorted from highest to lowest based on their overall scores.

4. The method for searching and displaying sold-out flights according to claim 1, characterized in that, It also includes customized displays based on user travel type: Identify the user's travel type. If the user is a business traveler, prioritize displaying on-time performance and airport lounge configuration information in the sold-out flight information. For tourists, the information on sold-out flights will prioritize displaying the convenience of transportation connections between the departure and arrival airports and scenic spots and hotels, as well as baggage allowance information.

5. The method for searching and displaying sold-out flights according to claim 1, characterized in that, Related service data includes airport transportation information, hotel booking information, and visa processing information; Generate suggestions for adjusting related services, including: Airport transportation is linked to match the departure and arrival airports of sold-out flights and alternative flights with their corresponding transportation timetables. If the arrival time of the alternative flight is later than the last bus time of the original transportation mode, a transportation plan adjustment prompt is generated. The hotel booking is linked. If a user triggers a hotel-related request, the system will recommend nearby hotels that support free cancellation based on the arrival time of the alternative flight, and indicate the latest check-in time and distance from the airport. The visa processing mechanism is linked to international flights. If the timing of the alternative flight causes a conflict with the visa application deadline, a notification will be generated indicating that the visa grace period is insufficient.

6. The method for searching and displaying sold-out flights according to claim 1, characterized in that, Dynamic reminders are executed based on the monitoring results of the reminder task queue, including: Ticket release reminder: When a sold-out flight is detected to have tickets canceled, resulting in the release of remaining tickets, a notification will be sent according to the reminder method set by the user. Alternate flight alerts are sent when the number of remaining tickets for flights on the same route falls below a ticket threshold, or when the price increases by more than a certain amount within a preset time. Once the user has viewed the alert, it will not be sent again.

7. The method for searching and displaying sold-out flights according to claim 1, characterized in that, Return search results data to the user, including: Return sold-out flight information using a preset data structure, which includes a sold-out status indicator, a detailed array of sold-out cabins, in-depth analysis objects, associated service objects, personalized comprehensive scores, and an array of operation entry points. The in-depth analysis includes fields such as historical ticket sales speed, comparison coefficient of sell-out trend for the same route, probability of remaining tickets being released, and probability level; the operation entry array includes the entry to unfollow remaining tickets and the entry to view alternative flights.

8. A system for searching and displaying sold-out flights, characterized in that, include: The request receiving module is used to obtain the user's flight search request. The request includes the first search criteria, sold-out flight search preferences, personalized settings, and dynamic reminder settings. The key value generation module is used to parse the request, extract parameters from the first query condition, sold-out flight query preferences, personalized settings, and dynamic reminder settings, and generate composite key values; The sold-out flight search module is used to query the entire set of flights that meet the first query condition and sold-out flight query preference based on composite key values, obtain the inventory status of each flight, and filter sold-out flights from the entire set of flights based on the inventory status. The data acquisition module is used to call the user profile database to obtain the user's historical travel data, and to call the related service database to obtain related service data; The in-depth analysis module is used to perform in-depth analysis and calculation on sold-out flights and generate in-depth analysis information. The in-depth analysis information includes at least the historical ticket sales speed, the comparison coefficient of the sold-out trend of the same route, the sold-out status of cabin allocation, and the probability of releasing remaining tickets. The personalized adaptation module is used to calculate the convenience of associated services and the matching degree with the user's historical travel preferences for sold-out flights based on the user's historical travel data, related service data and in-depth analysis information. Based on the matching degree with the user's historical travel preferences, the convenience of associated services and the probability of remaining tickets being released, the sold-out flights are filtered and prioritized. The data linkage module is used to match the takeoff and landing information of sold-out flights with related service data and generate suggestions for adjusting related services. The dynamic reminder module is used to add sold-out flights and alternative flights to the reminder task queue for real-time monitoring based on the dynamic reminder settings. The output module is used to integrate available flight information, sorted sold-out flight information, and related service adjustment suggestions to generate search results data, return the search results data to the user, and execute dynamic reminders based on the monitoring results of the reminder task queue.

9. An electronic device, characterized in that, It includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, which stores computer programs; A processor, when executing a computer program stored in memory, implements a method for searching and displaying sold-out flights as described in any one of claims 1-7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements a method for searching and displaying sold-out flights as described in any one of claims 1-7.

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