Data control method and system of flight display broadcast industrial personal computer

Abstract

The invention relates to the technical field of data processing, and discloses a data control method and system for a flight display broadcast industrial personal computer, and the method comprises the steps: popping up a user preference questionnaire after a passenger completes the ticket buying, and collecting the flight information preference of the passenger through the user preference questionnaire; carrying out clustering analysis on the collected user preferences by utilizing data analysis, and identifying information demand characteristics of different passenger groups; according to the clustering analysis, a default information pushing strategy is set for each passenger group or a single passenger based on a user preference analysis result, and the default information pushing strategy comprises an information type and a pushing frequency; and combining real-time positions and flight states of passengers, including whether boarding gates are changed or not, whether flights are delayed or not, whether waiting for aircrafts or not and whether the passengers take off or not in flight or not. According to the method, personalized service is realized: a personalized service mode is provided according to factors such as historical preferences and member levels of the passengers, so that diversified requirements of the passengers can be met, and the satisfaction and loyalty of the passengers are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a data control method and system for an aerial display and broadcasting industrial computer. Background Art

[0002] Air travel has become one of the important ways for modern people to travel. With the rapid development of the aviation industry, passenger traffic has continued to increase, which has put higher requirements on the service quality and information push capabilities of airlines.

[0003] Diversification of passenger needs: Passengers' needs for information are becoming increasingly diverse, including flight dynamics, promotional information, airport services, etc. At the same time, different passengers have different preferences for information, and the system needs to be able to push information based on the personalized needs of passengers.

[0004] With the continuous advancement of information technology, especially the widespread application of technologies such as big data and artificial intelligence, airlines are provided with more accurate and intelligent means of information push. In the fierce market competition, airlines need to continuously improve service quality and increase passenger satisfaction and loyalty. Accurate push and personalized services have become one of the key means for airlines to enhance their competitiveness; With the rapid development of the aviation industry and the increasing diversification of passenger needs, airlines need to push information more accurately and personalized to meet passengers' real-time needs and improve passenger experience. However, traditional information push methods often lack pertinence and personalization, resulting in poor information push results and low passenger satisfaction. Therefore, a system is needed that can dynamically adjust information push strategies based on passengers' real-time location and flight status to achieve accurate push and personalized services; Therefore, in order to solve the above problems, a data control method and system of an aerial display and broadcasting industrial computer are needed. Summary of the invention

[0005] The purpose of the present invention is to provide a data control method and system for an industrial computer for flight display and broadcasting. The present invention can dynamically adjust the information push strategy according to the location of the passenger and the flight status to ensure that the pushed information is highly matched with the passenger's current needs and flight status. This precise push method helps to reduce the interference of irrelevant information and improve the effectiveness and utilization of information.

[0006] Personalized service: The system generates a personalized weight vector for each passenger based on the passenger's historical preferences, membership level and other factors, and determines the type and priority of information pushed based on the weight vector. This personalized service method helps meet the diverse needs of passengers and improve passenger satisfaction and loyalty.

[0007] The present invention is achieved in that: The present invention provides a data control method for an aerial display broadcasting industrial computer, which is specifically performed in the following steps: S1: First, after the passenger completes the ticket purchase, a user preference questionnaire pops up to collect the passenger's flight information preferences; the user preference questionnaire includes real-time dynamics of the aircraft's itinerary, boarding gate changes, baggage claim reminders, advertising information preferences, introductions to destination tourism projects, introductions to destination customs and culture, recommendations for tourist attractions, recommendations for special check-in spots, and introductions to specialties.

[0008] S2: Use data analysis to cluster the collected user preferences and identify the information demand characteristics of different traveler groups; Please follow the steps below: S2.1: First, remove duplicate, missing or invalid data records from the collected data, convert data of different dimensions into the same dimension, and compare and analyze them; specifically, use z-score standardization as shown below;

[0009] Among them, x is the original data of passengers' preference, μ is the mean, and σ is the standard deviation; S2.2: Then, features useful for cluster analysis are selected from the original data, including the degree of preference of passengers for various types of flight information; S2.3: Construct a preference matrix. When there are n passengers and m types of flight information, construct an n×m preference matrix P, where P[i][j] represents the preference of the i-th passenger for the j-th flight information and for various items in the questionnaire, where the preference degree is a numerical value or a grade; S2.4: Determine the optimal number of clusters k by using the K-means clustering algorithm, as shown below;

[0010] in, It is The center of the cluster, is the set of data points of the kth cluster; S2.5: Take the preference matrix P as input, run the selected clustering algorithm, and obtain the clustering results; then interpret the clustering results, analyze the passenger groups in each cluster, and identify the highest level of information demand characteristics.

[0011] S3: According to cluster analysis and user preference analysis results, a default information push strategy is set for each passenger group or individual passenger, including information type and push frequency; Combined with the passenger's real-time location and flight status, including whether the boarding gate has changed, whether the flight is delayed, whether the passenger is waiting, whether the passenger has taken off and is in flight, and whether the passenger has arrived at the destination, the content and priority of the information pushed can be dynamically adjusted. The specific steps are as follows: S3.1 collects passengers’ real-time location from airline systems, including boarding gates, waiting areas, and flight status. Flight status includes boarding time and flight delay data. S3.2: Calculate a dynamic adjustment factor A based on the passenger's real-time location and flight status, where the factor A is a scalar used to uniformly adjust the weights of all information types; or a vector used to adjust the weights of each information type separately; S3.3: Use the dynamic adjustment factor A to adjust the weight vector W to obtain an adjusted weight vector W′; If A is a scalar, by element-wise multiplication, then W′=A×W; as follows;

[0012] Wj represents the push weight of the jth information type; If A is a vector, then each element Wj′ of W′ is the result of any operation between Wj and Aj; S3.4: Determine the type and priority of the information to be pushed according to the adjusted weight vector W′; Specifically, the information types with the highest weights are selected for push, or different push priorities are set according to the weights; as shown in the following formula;

[0013] W' is the adjusted weight vector in the case of scalar A; S3.5: Generate push content. Generate specific push content based on the determined information type and priority, and send it to passengers through the ticket purchase APP, SMS, WeChat push or flight display broadcast.

[0014] Furthermore, the present invention provides a data control system for an air display broadcasting industrial computer, including a data collection and preprocessing module, which specifically performs data collection, collects basic passenger information including name, membership level, historical preferences and real-time flight status including take-off time, landing time and boarding gate information from the airline's database, passenger information system and flight status system; The data preprocessing module cleans, removes duplicates, and converts the format of the collected data; The weight vector initialization module generates weight vectors. Based on the passenger's historical preferences and membership level factors, an m-dimensional weight vector W is generated for each passenger. This reflects the passenger's preference for different types of information, including flight dynamics, promotional information, and airport services. The module then distributes weights and assigns specific weight values ​​to each dimension of the weight vector according to a preset algorithm or rule. The dynamic adjustment factor calculation module performs real-time data analysis and calculates the dynamic adjustment factor A based on the passenger's location, including whether he has arrived at the airport, whether he is waiting for the flight, whether he has boarded the flight, and the real-time status of the flight, including whether it is delayed or cancelled. Based on the results of the real-time data analysis, a predefined algorithm is used to calculate the dynamic adjustment factor A for adjusting the weight vector W.

[0015] The weight vector adjustment and information push strategy determination module adjusts the weight vector and uses the dynamic adjustment factor A to adjust the passenger's weight vector W to obtain the adjusted weight vector W'; and determines the information push strategy and determines the type and priority of the information to be pushed based on the adjusted weight vector W'; The push content generation and sending module generates push content. According to the determined information type and priority, it generates specific push content, including flight status, promotional information, and airport service reminders, and sends the push content. The generated push content is sent to passengers through channels such as the flight display broadcast system, SMS, and APP push.

[0016] Furthermore, the present invention provides a computer storable medium for executing any one of the above-mentioned data control methods for an aerial display and broadcasting industrial computer.

[0017] Compared with the prior art, the present invention has the following beneficial effects: 1. The system can dynamically adjust the information push strategy based on the passenger's location and flight status to ensure that the pushed information is highly matched with the passenger's current needs and flight status. This precise push method helps reduce the interference of irrelevant information and improve the effectiveness and utilization of information.

[0018] 2. Personalized service: The system generates a personalized weight vector for each passenger based on the passenger's historical preferences, membership level and other factors, and determines the type and priority of information pushed based on the weight vector. This personalized service method helps to meet the diverse needs of passengers and improve passenger satisfaction and loyalty.

[0019] 3. Improve the operational efficiency and competitiveness of airlines. To improve operational efficiency, the system realizes real-time monitoring and push of passenger information and flight status through automation and intelligence, reducing manual intervention and error rate. This helps to improve the operational efficiency of airlines and reduce operating costs. Enhance competitiveness. By providing accurate push and personalized services, airlines can better meet the needs and expectations of passengers and improve passenger satisfaction and loyalty. This helps to enhance the competitiveness of airlines in the market and attract more passengers to choose the services of the airline. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments will be briefly introduced below. It is understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0021] Figure 1 is a flow chart of the method of the present invention; Figure 2 It is a system structure diagram of the present invention. DETAILED DESCRIPTION

[0022] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work belong to the scope of protection of the present invention. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the invention claimed for protection, but is only for selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work belong to the scope of protection of the present invention.

[0023] See also Figure 1-Figure 2 The present invention provides a data control method for an aerial display and broadcasting industrial computer, which is specifically performed in the following steps: S1: First, after the passenger completes the ticket purchase, a user preference questionnaire pops up to collect the passenger's flight information preferences; the user preference questionnaire includes real-time dynamics of the aircraft's itinerary, boarding gate changes, baggage claim reminders, advertising information preferences, introductions to destination tourism projects, introductions to destination customs and culture, recommendations for tourist attractions, recommendations for special check-in spots, and introductions to specialties.

[0024] S2: Use data analysis to cluster the collected user preferences and identify the information demand characteristics of different traveler groups; Please follow the steps below: S2.1: First, remove duplicate, missing or invalid data records from the collected data, convert data of different dimensions into the same dimension, and compare and analyze them; specifically, use z-score standardization as shown below;

[0025] Among them, x is the original data of passengers' preference, μ is the mean, and σ is the standard deviation; S2.2: Then, features useful for cluster analysis are selected from the original data, including the degree of preference of passengers for various types of flight information; S2.3: Construct a preference matrix. When there are n passengers and m types of flight information, construct an n×m preference matrix P, where P[i][j] represents the preference of the i-th passenger for the j-th flight information and for various items in the questionnaire, where the preference degree is a numerical value or a grade; S2.4: Determine the optimal number of clusters k by using the K-means clustering algorithm, as shown below;

[0026] in, It is The center of the cluster, is the set of data points of the kth cluster; S2.5: Take the preference matrix P as input, run the selected clustering algorithm, and obtain the clustering results; then interpret the clustering results, analyze the passenger groups in each cluster, and identify the highest level of information demand characteristics.

[0027] S3: According to cluster analysis and user preference analysis results, a default information push strategy is set for each passenger group or individual passenger, including information type and push frequency; Combined with the passenger's real-time location and flight status, including whether the boarding gate has changed, whether the flight is delayed, whether the passenger is waiting, whether the passenger has taken off and is in flight, and whether the passenger has arrived at the destination, the content and priority of the information pushed can be dynamically adjusted. The specific steps are as follows: S3.1 collects passengers’ real-time location from airline systems, including boarding gates, waiting areas, and flight status. Flight status includes boarding time and flight delay data. S3.2: Calculate a dynamic adjustment factor A based on the passenger's real-time location and flight status, where the factor A is a scalar used to uniformly adjust the weights of all information types; or a vector used to adjust the weights of each information type separately; S3.3: Use the dynamic adjustment factor A to adjust the weight vector W to obtain an adjusted weight vector W′; If A is a scalar, by element-wise multiplication, then W′=A×W; as follows;

[0028] Wj represents the push weight of the jth information type; If A is a vector, then each element Wj′ of W′ is the result of any operation between Wj and Aj; S3.4: Determine the type and priority of the information to be pushed according to the adjusted weight vector W′; Specifically, the information types with the highest weights are selected for push, or different push priorities are set according to the weights; as shown in the following formula;

[0029] W' is the adjusted weight vector in the case of scalar A; S3.5: Generate push content. Generate specific push content based on the determined information type and priority, and send it to passengers through the ticket purchase APP, SMS, WeChat push or flight display broadcast.

[0030] In this embodiment, the present invention provides a data control system for an air display broadcasting industrial computer, including a data collection and preprocessing module, which specifically collects data and collects basic passenger information including name, membership level, historical preferences and real-time flight status including take-off time, landing time and boarding gate information from the airline's database, passenger information system and flight status system; The data preprocessing module cleans, removes duplicates, and converts the format of the collected data; The weight vector initialization module generates weight vectors. Based on the passenger's historical preferences and membership level factors, an m-dimensional weight vector W is generated for each passenger. This reflects the passenger's preference for different types of information, including flight dynamics, promotional information, and airport services. The module then distributes weights and assigns specific weight values ​​to each dimension of the weight vector according to a preset algorithm or rule. The dynamic adjustment factor calculation module performs real-time data analysis and calculates the dynamic adjustment factor A based on the passenger's location, including whether he has arrived at the airport, whether he is waiting for the flight, whether he has boarded the flight, and the real-time status of the flight, including whether it is delayed or cancelled. Based on the results of the real-time data analysis, a predefined algorithm is used to calculate the dynamic adjustment factor A for adjusting the weight vector W.

[0031] The weight vector adjustment and information push strategy determination module adjusts the weight vector and uses the dynamic adjustment factor A to adjust the passenger's weight vector W to obtain the adjusted weight vector W'; and determines the information push strategy and determines the type and priority of the information to be pushed based on the adjusted weight vector W'; The push content generation and sending module generates push content. According to the determined information type and priority, it generates specific push content, including flight status, promotional information, and airport service reminders, and sends the push content. The generated push content is sent to passengers through channels such as the flight display broadcast system, SMS, and APP push.

[0032] In this embodiment, a specific calculation process is listed, including passenger information, aviation information, dynamic adjustment factor, weight vector adjustment, push strategy determination and push content generation. As shown in Table 1, the passenger information obtained through the questionnaire and historical information; Table 1 Passenger preference information Traveler ID Name Membership Level Historical Preference (Weight) 001 Zhang San Gold Member Flight status (0.4), travel guide (0.3), featured products (0.2), recommended attractions (0.1) 002 Li Si Platinum Member Flight status (0.2), recommended attractions (0.4), check-in spots (0.3), featured products (0.1) Flight information is shown in Table 2; Table 2 Passenger flight information Flight number Departure time Landing time destination Flight Status CA123 2024-11-15 08:00 2024-11-15 14:00 Paris Take off on time CZ456 2024-11-15 10:00 2024-11-15 16:00 Tokyo Delayed 1 hour The destination information is shown in Table 3; Table 3 Passenger flight information destination Special tourist attractions Check-in location Travel guide Featured Products Paris Eiffel Tower, Louvre Champs-Elysees It is recommended to spend at least 3 days in Paris and taste French cuisine French red wine, Parisian perfume Tokyo Tokyo Tower, Sensoji Temple Akihabara, Harajuku Takeshita Shopping and dining in Tokyo Japanese-style items, anime-related items Dynamic Adjustment Factor Traveler ID Real-time location Flight Status Destination interest (based on historical visit records) Dynamic Adjustment Factor 001 Arrived at the airport Take off on time Gao (been to Paris) 1.1 002 Waiting for flight Delayed 1 hour Medium (interested in XX) 1.2 In this embodiment, weight vector adjustment and information push strategy determination are performed. Zhang San (passenger ID 001): Original weight vector: [0.4, 0.3, 0.2, 0.1] Dynamically adjusted weight vector (taking into account the destination interest): [0.4×1.1, 0.3×1.1, 0.2×1.1, 0.1×1.1] = [0.44, 0.33, 0.22, 0.11] Push strategy: Since Zhang San has a high interest in Paris and is a gold member, in addition to flight status, we focus on pushing travel guides and special products for Paris.

[0033] Li Si (passenger ID 002): Original weight vector: [0.2, 0.4, 0.3, 0.1] Dynamically adjusted weight vector (taking into account flight delays and interest): [0.2×1.2, 0.4×1.2, 0.3×1.2, 0.1×1.2] = [0.24, 0.48, 0.36, 0.12] Push strategy: Since Li Si’s flight was delayed and he is interested in XX culture, in addition to flight status, we will focus on pushing XX’s attraction recommendations and check-in location information.

[0034] Push content generation and delivery Zhang San: Push content: Flight CA123 has taken off on time. Wish you a pleasant journey! Paris Travel Guide: It is recommended to visit Paris for at least 3 days, and don't forget to taste French food. It is recommended to buy French red wine and Paris perfume as souvenirs.

[0035] Sending channel: APP push Li Si: Push content: Flight CZ456 is delayed by 1 hour and is expected to take off at 2024-11-15 11:00. Please be patient and we have prepared tea and snacks for you.

[0036] XX attractions recommendation: Don’t forget to visit Tokyo Tower and Sensoji Temple, as well as the check-in spots in Akihabara and Harajuku Takeshita. Shopping and food experiences are also an indispensable part of XX.

[0037] In this embodiment, the present invention provides a computer storable medium for executing any one of the above-mentioned data control methods for an aerial display and broadcasting industrial computer.

[0038] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention has various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A data control method for an aerial display and broadcasting industrial computer, characterized in that: Please follow the steps below: S1: First, after the passenger completes the ticket purchase, a user preference questionnaire pops up to collect the passenger's flight information preferences; S2: Use data analysis to perform cluster analysis on the collected user preferences and identify the information demand characteristics of different passenger groups; specifically, follow the following steps: S2.1: First, remove duplicate, missing or invalid data records from the collected data, convert data of different dimensions into the same dimension, and compare and analyze them; specifically, use z-score standardization as shown below; Among them, x is the original data of passengers' preference, μ is the mean, and σ is the standard deviation; S2.2: Then, features useful for cluster analysis are selected from the original data, including the degree of preference of passengers for various types of flight information; S2.3: Construct a preference matrix. When there are n passengers and m types of flight information, construct an n×m preference matrix P, where P[i][j] represents the preference of the i-th passenger for the j-th flight information and for various items in the questionnaire, where the preference degree is a numerical value or a grade; S2.4: Determine the optimal number of clusters k by using the K-means clustering algorithm, as shown below; in, It is The center of the cluster, is the set of data points of the kth cluster; S2.5: Take the preference matrix P as input, run the selected clustering algorithm, and obtain the clustering results; then interpret the clustering results, analyze the passenger groups in each cluster, and identify the highest level of information demand characteristics; S3: According to cluster analysis and user preference analysis results, a default information push strategy is set for each passenger group or individual passenger, including information type and push frequency; The information content and priority of the push notifications are dynamically adjusted based on the passenger's real-time location and flight status, including whether the boarding gate has changed, whether the flight is delayed, whether the passenger is waiting for the flight, whether the passenger has taken off or is in flight, and whether the passenger has arrived at the destination. Please follow the steps below: S3.1 collects passengers’ real-time location from airline systems, including boarding gates, waiting areas, and flight status. Flight status includes boarding time and flight delay data. S3.2: Calculate a dynamic adjustment factor A based on the passenger's real-time location and flight status, where the factor A is a scalar used to uniformly adjust the weights of all information types; or a vector used to adjust the weights of each information type separately; S3.3: Use the dynamic adjustment factor A to adjust the weight vector W to obtain the adjusted weight vector W′; If A is a scalar, by element-wise multiplication, then W′=A×W; as follows; W j represents the push weight of the jth information type; If A is a vector, then each element Wj′ of W′ is j and A j Any operation result of ; S3.4: Determine the type and priority of the information to be pushed according to the adjusted weight vector W′; Specifically, the information types with the highest weights are selected for push, or different push priorities are set according to the weights; as shown in the following formula; W' is the adjusted weight vector in the case of scalar A; S3.5: Generate push content. Generate specific push content based on the determined information type and priority, and send it to passengers through the ticket purchase APP, SMS, WeChat push or flight display broadcast.

2. The data control method of the aerial display broadcasting industrial computer according to claim 1 is characterized by: In step S1, the user preference questionnaire includes real-time dynamics of the flight, boarding gate changes, baggage claim reminders, advertising information preferences, introductions to destination tourism projects, introductions to destination customs and culture, recommendations for tourist attractions, recommendations for special check-in spots, and introductions to special products.

3. A data control system for an aerial display and broadcasting industrial computer, characterized in that: It includes a data collection and preprocessing module, which specifically collects data from the airline's database, passenger information system, and flight status system to collect basic passenger information including name, membership level, historical preferences, and real-time flight status, including take-off time, landing time, and boarding gate information; The data preprocessing module cleans, removes duplicates, and converts the format of the collected data; The weight vector initialization module generates weight vectors. Based on the passenger's historical preferences and membership level factors, an m-dimensional weight vector W is generated for each passenger. This reflects the passenger's preference for different types of information, including flight dynamics, promotional information, and airport services. The module then distributes weights and assigns specific weight values ​​to each dimension of the weight vector according to a preset algorithm or rule. The dynamic adjustment factor calculation module performs real-time data analysis and calculates the dynamic adjustment factor A using a predefined algorithm based on the passenger's location, including whether the passenger has arrived at the airport, is waiting for the flight, has boarded the flight, and the flight's real-time status, including whether the flight is delayed or canceled. The dynamic adjustment factor A is used to adjust the weight vector W. The weight vector adjustment and information push strategy determination module adjusts the weight vector and uses the dynamic adjustment factor A to adjust the passenger's weight vector W to obtain the adjusted weight vector W'; and determines the information push strategy and determines the type and priority of the information to be pushed based on the adjusted weight vector W'; The push content generation and sending module generates push content. According to the determined information type and priority, it generates specific push content, including flight status, promotional information, and airport service reminders, and sends the push content. The generated push content is sent to passengers through channels such as the flight display broadcast system, SMS, and APP push.

4. A computer storable medium, characterized in that: A data control method for an aerial display and broadcasting industrial computer as described in any one of claims 1-2.

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