Processing system and method for high-frequency passenger data

Abstract

The invention provides a processing system and method for high-frequency passenger data. The system comprises a data deduplication service module used for performing deduplication and filtering on high-frequency passenger data to obtain a high-frequency passenger data message and sending the high-frequency passenger data message to a data analysis service module; the data analysis service module is used for reconstructing the high-frequency passenger data message according to a deconstruction demand, an analysis demand and a statistics demand to obtain a passenger data type meeting the demand; the core business analysis service module is used for identifying a passenger travel business scene according to the passenger data type, constructing a core business model and generating core business scene data suitable for the client system; the data bus service module is used for storing core business scene data and performing classification management; and the data interaction service module is used for responding to a data reading request of the client system, reading the core business scene data in the data bus service module, and sending the core business scene data to the client system. According to the invention, a passenger data processing mode of a civil aviation business scene is optimized.

Description

Technical Field

[0001] The present application relates to the field of data processing, and in particular, to a system and method for processing high-frequency passenger data. Background Art

[0002] With the rapid development of the domestic civil aviation industry, the number of passengers who choose to travel by civil aviation is increasing. For passenger services, facing the increasing number of flights and passengers, and the growing business and industry requirements, it is more important to focus on improving the quality of passenger services and continuously improve the civil aviation service system. High-frequency passenger data provides data support for passenger travel services in the form of high-frequency transmission of messages. Stable passenger data support is the basis for building high-quality passenger services.

[0003] However, the traditional high-frequency passenger data support method only provides data through message queue message transmission. The data is pushed to the message queue, and the client completes the reading, analysis, and processing of the message queue data, and finally uses it for client services. The traditional method has the problem of business duplication. The same business scenario function is repeatedly implemented on multiple information systems, which can neither achieve the unification of business services nor waste resources for system construction. There is an information island problem. There is a lack of unified and standard data interaction specifications between various information systems, and passenger service data cannot be shared. There is a problem of difficulty in analyzing core business data. The analysis of core business scenario data needs to rely on manual analysis and processing by personnel proficient in the industry, which not only reduces the degree of automation of the system, but also increases the human cost of system construction. There is a problem of client performance degradation due to the large amount of data. High-frequency updates and a large amount of passenger data increase the data processing pressure of the client system, resulting in performance problems such as freezes in the client system.

[0004] Therefore, the present application provides a system and method for processing high-frequency passenger data to solve one of the above-mentioned technical problems. Summary of the invention

[0005] The purpose of this application is to provide a system and method for processing high-frequency passenger data, which can solve at least one of the technical problems mentioned above. The specific solution is as follows: According to the specific implementation mode of the present application, in the first aspect, the present application provides a processing system for high-frequency passenger data, including: a data deduplication service module, which is used to deduplicate and filter high-frequency passenger data, obtain high-frequency passenger data messages and send them to a data analysis service module; the data analysis service module is used to reconstruct the high-frequency passenger data messages according to deconstruction requirements, analysis requirements, and statistical requirements to obtain passenger data types that meet the requirements; a core business analysis service module is used to identify passenger travel business scenarios based on the passenger data types, build core business models, and generate core business scenario data suitable for client systems; a data bus service module is used to store the core business scenario data and classify and manage it; a data interaction service module is used to respond to data read requests from the client system, read the core business scenario data in the data bus service module, and send it to the client system.

[0006] In one embodiment, the system also includes: a data interaction configuration service module, which is used to manage data exchange rules between the client system and the data bus service module, and generate data interaction configuration information; wherein the data interaction configuration information is used to record the identity of the client system, the interaction type, and the types of interaction data supported by the client system; the data bus service module is also used to save and / or provide the data interaction configuration information; the data interaction service module is also used to execute data transmission between the data interaction service module and the client system according to the interaction type and interaction data type defined in the data interaction configuration information.

[0007] In one embodiment, the data deduplication service module performs deduplication filtering on the high-frequency passenger data to obtain a high-frequency passenger data message in the following manner: removes completely duplicate data entries in the high-frequency passenger data, and / or deduplicates similar business data in the high-frequency passenger data based on business keywords; filters abnormal data and / or worthless data in the deduplicated data to obtain the high-frequency passenger data message.

[0008] In one embodiment, the data analysis service module reconstructs the high-frequency passenger data message in the following manner: according to the deconstruction requirements, the high-frequency passenger data message is decomposed into data elements; according to the analysis requirements, the statistical requirements, and a preset data model, the data elements are analyzed and counted, and reassembled into the passenger data type.

[0009] In one implementation, the passenger travel service scenario includes passenger check-in, baggage check-in, and / or cabin lift.

[0010] According to the specific implementation mode of the present application, in the second aspect, the present application provides a processing method for high-frequency passenger data, which is applied to a processing system for high-frequency passenger data, including: controlling the data deduplication service module to deduplicate and filter the high-frequency passenger data, obtain high-frequency passenger data messages and send them to the data analysis service module; controlling the data analysis service module to reconstruct the high-frequency passenger data messages according to the deconstruction requirements, analysis requirements, and statistical requirements, and obtain the passenger data type that meets the requirements; controlling the core business analysis service module to identify the passenger travel business scenarios according to the passenger data types, construct a core business model, and generate core business scenario data suitable for the client system; controlling the data bus service module to store the core business scenario data and classify and manage it; in response to receiving a data read request sent by the client system, controlling the data interaction service module to read the core business scenario data in the data bus service module and send it to the client system.

[0011] In one embodiment, the method also includes: controlling the data interaction configuration service module to manage the data exchange rules between the client system and the data bus service module, and generating data interaction configuration information; wherein the data interaction configuration information is used to record the identity of the client system, the interaction type, and the types of interaction data supported by the client system; controlling the data bus service module to save and / or provide the data interaction configuration information; controlling the data interaction service module to execute data transmission between the data interaction service module and the client system according to the interaction type and interaction data type defined in the data interaction configuration information.

[0012] In one embodiment, the high-frequency passenger data is de-duplicated and filtered to obtain a high-frequency passenger data message: the data de-duplication service module is controlled to remove completely repeated data entries in the high-frequency passenger data, and / or similar business data in the high-frequency passenger data is de-duplicated according to business keywords; the data de-duplication service module is controlled to filter abnormal data and / or worthless data in the de-duplicated data to obtain the high-frequency passenger data message.

[0013] In one embodiment, the high-frequency passenger data message is reconstructed by: controlling the data analysis service module to decompose the high-frequency passenger data message into data elements according to the deconstruction requirements; controlling the data analysis service module to analyze and count the data elements according to the analysis requirements, the statistical requirements, and a preset data model, and reassembling them into the passenger data type.

[0014] In one implementation, the passenger travel service scenario includes passenger check-in, baggage check-in, and / or cabin lift.

[0015] Compared with the prior art, the above scheme of the embodiment of the present application has at least the following beneficial effects: by introducing a data deduplication service module, a data analysis service module, a core business analysis service module, a data bus service module and a data interaction service module, the system significantly improves the efficiency and accuracy of high-frequency passenger data processing. The data deduplication service module effectively reduces redundant data and reduces the data load of subsequent processing steps, thereby improving the performance of the overall system. The data analysis service module ensures that the generated passenger data type can accurately meet actual needs and enhance the value of the data by deconstructing, analyzing and counting the data. The core business analysis service module further optimizes the business scenario identification and model building process, so that the generated core business scenario data can be directly used to improve the service quality of the client system. In addition, the data bus service module realizes efficient storage and classification management of these key data, and the data interaction service module ensures that these data can respond to the requests of the client system in a timely and accurate manner, thereby ensuring the smooth operation of the entire data link. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A block diagram of a processing system for high-frequency passenger data is shown; Figure 2 A schematic diagram of a process for decomposing a high-frequency passenger data message into data elements is shown; Figure 3 A schematic diagram of a process for analyzing, counting and reassembling data elements is shown; Figure 4 A schematic diagram of a process for classifying data in core business scenarios is shown; Figure 5 A logical schematic diagram showing the interaction between the processing system for high-frequency passenger data and the client system; Figure 6 A flow chart showing a method for processing high-frequency passenger data; Figure 7 A flow chart of a method for reconstructing high-frequency passenger data messages is shown. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present application.

[0018] The terms used in the embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the present application. The singular forms "a", "said" and "the" used in the embodiments of the present application and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings, and "multiple" generally includes at least two.

[0019] It should be understood that the term "and / or" used in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0020] It should be understood that although the terms first, second, third, etc. may be used to describe in the embodiments of the present application, these descriptions should not be limited to these terms. These terms are only used to distinguish the descriptions. For example, without departing from the scope of the embodiments of the present application, the first may also be referred to as the second, and similarly, the second may also be referred to as the first.

[0021] As used herein, the words "if" and "if" may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrases "if it is determined" or "if (stated condition or event) is detected" may be interpreted as "when it is determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)", depending on the context.

[0022] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a product or system including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such a product or system. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the product or system including the elements.

[0023] It should be particularly noted that any symbols and / or numbers in the specification that are not marked in the accompanying drawings are not drawing marks.

[0024] The processing system for high-frequency passenger data provided by the present application is used as an upstream system of the client system. Among them, the client system can be, for example, a passenger service system, an operation management system, a marketing and customer relationship management (CRM) platform, a data analysis and reporting tool, a third-party partner interface, or a mobile application commonly used in the civil aviation field. The processing system for high-frequency passenger data provided by the present application provides the client system with clean and easy-to-use passenger data by making the high-frequency passenger data easy to read, thereby improving the data processing capabilities of both ends.

[0025] The optional embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0026] Combine the following Figure 1 The embodiments of the present application are described in detail.

[0027] Figure 1 A block diagram of a processing system for high-frequency passenger data is shown. Figure 1 As shown, the system includes a data deduplication service module 101 , a data analysis service module 102 , a core business analysis service module 103 , a data bus service module 104 , a data interaction service module 105 , and a data interaction configuration service module 106 .

[0028] The data deduplication service module 101 is used to deduplicate and filter the high-frequency passenger data, obtain the high-frequency passenger data message and send it to the data analysis service module 102 .

[0029] The data analysis service module 102 is used to reconstruct high-frequency passenger data messages according to deconstruction requirements, analysis requirements, and statistical requirements to obtain passenger data types that meet the requirements.

[0030] The core business analysis service module 103 is used to identify passenger travel business scenarios according to passenger data types, build core business models, and generate core business scenario data suitable for the client system.

[0031] The data bus service module 104 is used to store core business scenario data and perform classification management.

[0032] The data interaction service module 105 is used to respond to the data reading request of the client system, read the core business scenario data in the data bus service module 104, and send it to the client system.

[0033] In the embodiment of the present application, by introducing the data deduplication service module 101, the data analysis service module 102, the core business analysis service module 103, the data bus service module 104 and the data interaction service module 105, the system significantly improves the efficiency and accuracy of high-frequency passenger data processing.

[0034] First, the data deduplication service module 101 effectively reduces redundant data and reduces the data load of subsequent processing steps, thereby improving the performance of the overall system. Secondly, the data analysis service module 102 ensures that the generated passenger data type can accurately meet actual needs and enhance the value of the data by deconstructing, analyzing and counting the data. The core business analysis service module 103 further optimizes the business scenario identification and model building process, so that the generated core business scenario data can be directly used to improve the service quality of the client system. In addition, the data bus service module 104 realizes the efficient storage and classification management of these key data, and the data interaction service module 105 ensures that these data can respond to the requests of the client system in a timely and accurate manner, thereby ensuring the smooth operation of the entire data link. In summary, the system architecture provided by this application not only improves the speed and quality of passenger data processing, but also greatly reduces the development and operation costs of the client system.

[0035] In the present application, the data interaction configuration service module 106 is used to manage the data exchange rules between the client system and the data bus service module 104 and generate data interaction configuration information. The data interaction configuration information is used to record the identity of the client system, the interaction type, and the types of interaction data supported by the client system.

[0036] The data bus service module 104 is also used to store and / or provide data interaction configuration information.

[0037] The data interaction service module 105 is further used to execute data transmission between the data interaction service module 105 and the client system according to the interaction type and interaction data type defined in the data interaction configuration information.

[0038] In the embodiment of the present application, after adding the data interaction configuration service module 106, the system can manage the data exchange rules between the client system and the data bus service more flexibly and securely. Specifically, by generating detailed data interaction configuration information, the system can accurately record the identity of each client system, the interaction type and the data types it supports, which not only simplifies the data interaction process, but also enhances the scalability and security of the system. More importantly, saving and providing these configuration information provides a reliable basis for subsequent data transmission, ensuring the accuracy and consistency of data interaction. Finally, data transmission is performed according to the defined interaction type and data type, so that the data interaction service module 105 can efficiently complete the data transfer task, while minimizing unnecessary data transmission, thereby optimizing resource utilization efficiency.

[0039] In the present application, the data deduplication service module 101 performs deduplication filtering on the high-frequency passenger data in the following manner to obtain a high-frequency passenger data message. For example, the data deduplication service module 101 removes completely repeated data entries in the high-frequency passenger data, and / or deduplicates similar business data in the high-frequency passenger data according to business keywords. The data deduplication service module 101 filters abnormal data and / or worthless data in the deduplicated data to obtain a high-frequency passenger data message.

[0040] In the embodiment of the present application, a specific method is used to deduplicate and filter high-frequency passenger data, which not only effectively solves the problem of a large amount of duplicate data in traditional methods, but also significantly improves the quality and availability of data. Among them, by removing completely duplicate data entries and deduplicating similar business data based on business keywords, the amount of data can be greatly reduced while retaining important information, reducing the complexity of subsequent processing.

[0041] In the above embodiment, after deduplication and filtering, high-frequency passenger data messages become more compact and have higher value, which helps to improve the efficiency and accuracy of data analysis, and ultimately achieve more efficient passenger services. While ensuring data integrity, it greatly optimizes the efficiency of data processing.

[0042] In the embodiment of the present application, the data analysis service module 102 reconstructs the high-frequency passenger data message in the following manner. For example, the data analysis service module 102 decomposes the high-frequency passenger data message into data elements according to the deconstruction requirements, analyzes and counts the data elements according to the analysis requirements, statistical requirements, and the preset data model, and reassembles them into passenger data types.

[0043] In the embodiment of the present application, the reconstruction method for high-frequency passenger data messages significantly improves the practicality and pertinence of the data through refined data decomposition, analysis, statistics and reassembly. First, the data message is decomposed into data elements according to the deconstruction requirements, so that each data element can be processed separately, increasing the flexibility of data processing. Next, based on the analysis requirements, statistical requirements and preset data models, these data elements are deeply analyzed and counted to dig out valuable information hidden behind the data. Finally, these analysis results are reassembled into new passenger data types to ensure that the final output data can meet specific needs and has a high degree of accuracy and relevance. This reconstruction method not only improves the depth and breadth of data processing, but also enhances the data's support for downstream applications, enabling the client system to better serve the travel needs of passengers, thereby significantly improving the user experience and service quality.

[0044] Figure 2 FIG. 1 shows a flow chart of decomposing a high-frequency passenger data message into data elements. For example, Figure 2As shown, first obtain the high-frequency passenger data (XML), then create a JAXBContext object, and then use the object to create an Unmarshaller object. Subsequently, use the Unmarshaller object to deserialize the XML data and convert it into a Java object. Next, decompose the Java object according to business needs, and finally store the decomposed data as a data element.

[0045] Figure 3 A schematic diagram of a process of analyzing, counting, and reassembling data elements is shown. Figure 3 As shown, taking excess baggage calculation as an example, firstly, the data elements of high-frequency passenger data are obtained, and data processing and business scenario analysis are performed on them. Then, the passenger baggage data is extracted, including the free baggage allowance, the number of free baggage pieces and the number of passenger baggage pieces. Then, based on the passenger baggage information, the excess baggage charging standard is calculated. Subsequently, through data calculation and data statistics, the excess baggage data is generated, including the number of excess baggage pieces, excess baggage allowance and excess baggage fees.

[0046] In some embodiments, the passenger travel service scenario includes passenger check-in, baggage check-in, and / or cabin lift.

[0047] Figure 4 A schematic diagram of a process for classifying data in core business scenarios is shown. Figure 4 As shown, first collect high-frequency passenger data, including departing passenger data, booking data and departing ticket data. In the departing passenger data, it is necessary to obtain detailed information such as passenger flight segment master information, departing baggage information, passenger transfer, passenger check-in, cabin lift and special services. In the booking data, it is necessary to record the booking master information, booking passenger information, group information, flight segment information and frequent flyer information. In the departing ticket data, it is necessary to pay attention to the specific details of the ticket master information, fare group related, tax related, payment method related and flight segment group related.

[0048] Figure 5 A logical diagram showing the interaction between the processing system for high-frequency passenger data and the client system is shown.

[0049] For example, Figure 5As shown in the figure, the data deduplication service module is responsible for deep deduplication and filtering of high-frequency passenger data, not only removing completely duplicate data entries, but also deduplication of similar business data based on business keywords to ensure the uniqueness of each business data. At the same time, this module is also responsible for filtering out abnormal or worthless data to ensure the quality and efficiency of subsequent data processing. The data analysis service module takes over the data that has been initially processed, deconstructs it into data elements, and performs detailed analysis and statistics based on the preset data model. These operations include decomposing high-frequency passenger data messages into basic data elements, analyzing and counting them according to specific needs, and finally reassembling them into new passenger analysis data types to meet the specific needs of different business scenarios. Subsequently, the core business analysis service module takes over the processed data, focusing on identifying the key business scenarios of passenger travel and building corresponding core business models. Based on these models, it generates common core business scenario data suitable for downstream client systems, such as data for important business scenarios such as passenger check-in, baggage check-in, and cabin lift. These classified core business scenario data can provide accurate data support according to the actual needs of the client system, thereby optimizing the customer service process.

[0050] As the core hub of the system, the data bus service module is responsible for storing and managing all core business scenario data and business data from the client system. It not only stores data by data type and business scenario, but also accurately matches and outputs the required data. At the same time, it saves the data interaction configuration information generated by the data interaction configuration service module to ensure the compliance of rules and data transmission accuracy during the data interaction process. The data interaction configuration service module manages the data exchange rules between the client system and the data bus service module, and generates detailed system interaction configuration information by recording the identity of each client system, the interaction type (push or obtain data) and the types of data it supports. The data interaction service module performs data transmission tasks with the client system based on this configuration information. Whether it is responding to the client system's data reading request or processing its data push request, it can complete data interaction efficiently and accurately, ensuring the smooth operation of the entire system and the safe and reliable transmission of data.

[0051] This application effectively solves the redundancy problem caused by the push of full-scale high-frequency passenger data in the existing technology by providing accurate passenger travel business data support, and greatly reduces the performance consumption and high-performance hardware requirements of the client system caused by processing a large amount of unnecessary data. In addition, this application introduces the core business scenario identification function of passenger travel, which not only directly provides the client system with analyzed and processed data, but also significantly reduces the client system's investment in complex business analysis, including development costs and human resource consumption of senior business analysts through business scenario identification, model building and data output methods. Finally, through unified business scenario data support, this application avoids the need for the client system to implement data processing and analysis on its own, greatly simplifies the development process, and thus greatly reduces the development cost and technical threshold of the client system. In summary, this application not only improves the accuracy and efficiency of data services, but also brings significant cost savings and technical implementation convenience to the client system.

[0052] The present application also provides a method embodiment that is based on the above embodiment, which is used to implement the module functions of the above embodiment. The explanation based on the same name meaning is the same as the above embodiment, and has the same technical effect as the above embodiment, which will not be repeated here.

[0053] Figure 6 A flowchart of a method for processing high-frequency passenger data is shown. Figure 6 As shown, the following steps are included.

[0054] Step S601, controlling the data deduplication service module to deduplicate and filter the high-frequency passenger data, obtain the high-frequency passenger data message and send it to the data analysis service module.

[0055] Step S602, controlling the data analysis service module to reconstruct the high-frequency passenger data message according to the deconstruction requirements, analysis requirements, and statistical requirements to obtain the passenger data type that meets the requirements.

[0056] Step S603, control the core business analysis service module to identify passenger travel business scenarios according to passenger data types, build core business models, and generate core business scenario data suitable for the client system.

[0057] Step S604, control the data bus service module to store the core business scenario data and perform classification management.

[0058] Step S605 , in response to receiving the data reading request sent by the client system, the data interaction service module is controlled to read the core business scenario data in the data bus service module and send it to the client system.

[0059] In some embodiments, the present application may also control the data interaction configuration service module to manage the data exchange rules between the client system and the data bus service module, and generate data interaction configuration information.

[0060] The data interaction configuration information is used to record the identity of the client system, the interaction type, and the types of interaction data supported by the client system.

[0061] In some embodiments, the present application may also control the data bus service module to save and / or provide data interaction configuration information.

[0062] In some embodiments, the present application may also control the data interaction service module to execute data transmission between the data interaction service module and the client system according to the interaction type and interaction data type defined in the data interaction configuration information.

[0063] In some embodiments, the present application may also perform de-duplication filtering on high-frequency passenger data to obtain high-frequency passenger data messages, control the data de-duplication service module to remove completely repeated data entries in the high-frequency passenger data, and / or deduplicate similar business data in the high-frequency passenger data according to business keywords. Further, the present application may also control the data de-duplication service module to filter abnormal data and / or worthless data in the de-duplicated data to obtain high-frequency passenger data messages.

[0064] Figure 7 A flow chart of a method for reconstructing high-frequency passenger data messages is shown, such as Figure 7 As shown, the following steps are included.

[0065] Step S701, controlling the data analysis service module to decompose the high-frequency passenger data message into data elements according to the deconstruction requirements.

[0066] Step S702, controlling the data analysis service module to analyze and count the data elements according to the analysis requirements, statistical requirements, and the preset data model, and reassemble them into passenger data types.

[0067] This application reconstructs high-frequency passenger data messages by controlling the data analysis service module. This method can generate more accurate and practical passenger data types. Among them, by deconstructing, analyzing, counting and reassembling the data messages, the system can dig out more valuable information to meet different business needs. By controlling the data analysis service module to decompose the data according to the deconstruction requirements, process the data elements according to the analysis and statistical requirements, and reassemble the data according to the preset model, the system can generate high-quality passenger data types. These data not only cover comprehensive business information, but also have the characteristics of high precision, and can be directly applied to various passenger service scenarios.

[0068] In some embodiments, the passenger travel service scenario includes passenger check-in, baggage check-in, and / or cabin lift.

[0069] Regarding the method in the above embodiment, the specific way in which each module performs the operation is described in detail. If there are any unclear points about the functions performed by the modules, you can still refer to the system in the above embodiment, and it will not be explained in detail here.

[0070] Although operations are described in a particular order in the drawings, this should not be understood as requiring that the operations be performed in the particular order shown or in serial order, or that all shown operations be performed to achieve desired results. In certain circumstances, multitasking and parallel processing may be advantageous.

[0071] Any steps, operations or procedures described herein may be performed or implemented using one or more hardware or software service modules, either alone or in combination with other devices. In one embodiment, the software service module is implemented using a computer program product including a computer-readable medium containing computer program code, which can be executed by a computer processor to perform any or all of the described steps, operations or procedures.

[0072] The foregoing description of the implementation of the present application has been given for the purpose of illustration and description. The foregoing description is not exhaustive nor is it intended to limit the present application to the exact form disclosed, and various variations and modifications may exist according to the above teachings or may be obtained from the practice of the present application. These embodiments are selected and described in order to illustrate the principles of the present application and its practical application, so that those skilled in the art can utilize the present application in various embodiments and various modifications suitable for the specific purpose contemplated.

[0073] Regarding the system in the above embodiment, the specific manner in which each service module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0074] It can be further understood that, unless otherwise specified, “connection” includes a direct connection without other components between the two, and also includes an indirect connection with other components between the two.

[0075] It is further understood that, although the operations are described in a specific order in the drawings in the embodiments of the present application, it should not be understood as requiring the operations to be performed in the specific order or serial order shown, or requiring the execution of all the operations shown to obtain the desired results. In certain environments, multitasking and parallel processing may be advantageous.

[0076] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. The present application is intended to encompass any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary techniques in the field of the present application that are not disclosed in the present application. The specification and embodiments are intended to be exemplary only, and the true scope and spirit of the present application are indicated by the following scope of rights.

[0077] It should be understood that the present application is not limited to the precise structures described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the scope of the appended claims.

[0078] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A system for processing high-frequency passenger data, characterized in that: include: The data deduplication service module is used to deduplicate and filter the high-frequency passenger data, obtain the high-frequency passenger data message and send it to the data analysis service module; The data analysis service module is used to reconstruct the high-frequency passenger data message according to the deconstruction requirements, analysis requirements, and statistical requirements to obtain the passenger data type that meets the requirements; A core business analysis service module, used to identify passenger travel business scenarios based on the passenger data type, build a core business model, and generate core business scenario data suitable for the client system; A data bus service module, used to store the core business scenario data and perform classification management; The data interaction service module is used to respond to the data reading request of the client system, read the core business scenario data in the data bus service module, and send it to the client system.

2. The system according to claim 1, characterized in that The system further comprises: A data interaction configuration service module, used to manage the data exchange rules between the client system and the data bus service module, and generate data interaction configuration information; wherein the data interaction configuration information is used to record the identity of the client system, the interaction type, and the types of interaction data supported by the client system; The data bus service module is further used to store and / or provide the data interaction configuration information; The data interaction service module is further used to execute data transmission between the data interaction service module and the client system according to the interaction type and interaction data type defined in the data interaction configuration information.

3. The system according to claim 1 or 2, characterized in that: The data deduplication service module performs deduplication filtering on the high-frequency passenger data to obtain high-frequency passenger data messages in the following manner: Removing completely duplicate data entries in the high-frequency passenger data, and / or removing duplicates of similar business data in the high-frequency passenger data according to business keywords; Abnormal data and / or worthless data are filtered out from the deduplicated data to obtain the high-frequency passenger data message.

4. The system according to claim 1 or 2, characterized in that: The data analysis service module reconstructs the high-frequency passenger data message in the following manner: Decomposing the high-frequency passenger data message into data elements according to the deconstruction requirements; The data elements are analyzed and counted according to the analysis requirements, the statistical requirements, and a preset data model, and reassembled into the passenger data type.

5. The system according to claim 1 or 2, characterized in that: The passenger travel business scenarios include passenger check-in, baggage check-in, and / or cabin lift.

6. A method for processing high-frequency passenger data, characterized in that: Applied to systems for processing high-frequency passenger data, including: Control the data deduplication service module to deduplicate and filter the high-frequency passenger data, obtain the high-frequency passenger data message and send it to the data analysis service module; The control data analysis service module reconstructs the high-frequency passenger data message according to the deconstruction requirements, analysis requirements, and statistical requirements to obtain the passenger data type that meets the requirements; Control the core business analysis service module to identify passenger travel business scenarios according to the passenger data type, build a core business model, and generate core business scenario data applicable to the client system; Control the data bus service module to store the core business scenario data and perform classification management; In response to receiving the data reading request sent by the client system, the control data interaction service module reads the core business scenario data in the data bus service module and sends it to the client system.

7. The method according to claim 6, characterized in that The method further comprises: Controlling the data interaction configuration service module to manage the data exchange rules between the client system and the data bus service module, and generating data interaction configuration information; wherein the data interaction configuration information is used to record the identity of the client system, the interaction type, and the types of interaction data supported by the client system; Controlling the data bus service module to save and / or provide the data interaction configuration information; The data interaction service module is controlled to execute data transmission between the data interaction service module and the client system according to the interaction type and interaction data type defined in the data interaction configuration information.

8. The method according to claim 6 or 7, characterized in that: The high-frequency passenger data is filtered to remove overlaps, and a high-frequency passenger data message is obtained: Controlling the data deduplication service module to remove completely duplicate data entries in the high-frequency passenger data, and / or deduplicating similar business data in the high-frequency passenger data according to business keywords; The data deduplication service module is controlled to filter abnormal data and / or worthless data in the deduplicated data to obtain the high-frequency passenger data message.

9. The method according to claim 6 or 7, characterized in that: The high frequency passenger data message is reconstructed: Controlling the data analysis service module to decompose the high-frequency passenger data message into data elements according to the deconstruction requirements; The data analysis service module is controlled to analyze and count the data elements according to the analysis requirements, the statistical requirements, and a preset data model, and reassemble the data elements into the passenger data type.

10. The method according to claim 6 or 7, characterized in that: The passenger travel business scenarios include passenger check-in, baggage check-in, and / or cabin lift.

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