A freight rate data processing method, device, system and storage medium

Abstract

An embodiment of this specification discloses a freight rate data processing method, device, system, and storage medium. The method includes: obtaining freight rate data and at least one freight rate processing task; for each freight rate processing task, determining a combined freight rate related to the freight rate processing task and an index corresponding to the combined freight rate based on the freight rate data; transmitting at least one combined freight rate and at least one index related to the at least one freight rate processing task to a local storage device. The method processes multiple freight rate processing tasks simultaneously in a parallel manner, reducing the time for generating combined freight rates and improving the calculation speed.

Description

Technical Field

[0001] This specification relates to the field of computer technology, and particularly to a method, apparatus, system, and storage medium for processing freight rate data. Background Art

[0002] The current calculation of international freight rates can be based on freight rate data. However, the volume of freight rate data is huge, and it is time-consuming and resource-consuming to determine the freight rates that meet the user's travel requirements. Summary of the Invention

[0003] To solve the above problems, one embodiment of this specification provides a data processing method, which is simultaneously and parallelly executed by one or more of multiple processing nodes of a data processing device. The method includes: obtaining freight rate data and at least one freight rate processing task; for each freight rate processing task, determining a combined freight rate related to the freight rate processing task and an index corresponding to the combined freight rate based on the freight rate data; and transmitting at least one combined freight rate and at least one index related to the at least one freight rate processing task to a local storage device.

[0004] One embodiment of this specification provides a data processing method, which includes: obtaining freight rate retrieval data and determining a planned itinerary based on the freight rate retrieval data; obtaining flight information and its related data adapted to the planned itinerary, and determining a calculated freight rate corresponding to the planned itinerary based on the flight information and its related data using a freight rate calculation rule; determining a constraint corresponding to the calculated freight rate based on a combined freight rate-index data set composed of the combined freight rate and the index, and obtaining a determination of whether the calculated freight rate meets a display condition; where the constraint corresponding to the calculated freight rate is used to determine whether the calculated freight rate meets the display condition; and performing a display or hiding operation on the calculated freight rate based on the determination.

[0005] One embodiment of this specification provides a data processing apparatus. The data processing apparatus includes multiple processing nodes, and any one of the nodes includes: a first obtaining module for obtaining freight rate data and at least one freight rate processing task; a first processing module for, for each freight rate processing task, determining a combined freight rate related to the freight rate processing task and an index corresponding to the combined freight rate based on the freight rate data; and a transmitting module for transmitting at least one combined freight rate and at least one index related to the at least one freight rate processing task to a local storage device.

[0006] One embodiment of this specification provides a data processing device. The data processing device includes: A second acquisition module for acquiring freight rate retrieval data and determining a planned itinerary based on the freight rate retrieval data; A second determination module for acquiring flight information and its related data adapted to the planned itinerary and determining a calculated freight rate corresponding to the planned itinerary based on the flight information and its related data using a freight rate calculation rule; A third determination module for determining a constraint corresponding to the calculated freight rate based on a combined freight rate-index data set composed of the combined freight rate and an index, and obtaining a determination of whether the calculated freight rate meets a display condition; wherein, the constraint corresponding to the calculated freight rate is used to determine whether the calculated freight rate meets the display condition; An execution module for performing a display or hiding operation of the calculated freight rate based on the determination.

[0007] One embodiment of this specification provides a data processing system. The system includes a memory, a processor, and a computer program stored on the memory and executable on the processor. When the computer program is executed by the processor, the steps of the method described above are implemented.

[0008] One embodiment of this specification provides a computer-readable storage medium. A computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the method described above are implemented.

[0009] The technical solution disclosed in this specification generates a combined freight rate through cluster parallel processing, reducing the generation time and improving the calculation speed.

[0010] Additional features will be partially described in the following description, and for those skilled in the art, they will become apparent by referring to the following content and drawings, or can be understood by generating or operating examples. The features of the present invention can be realized and obtained through various aspects of the methods, tools, and combinations described in the following detailed examples. Brief Description of the Drawings

[0011] This specification will be further described in the manner of exemplary embodiments, and these exemplary embodiments will be described in detail through the drawings. These embodiments are not restrictive. In these embodiments, the same numbers represent the same structures, where:

[0012] Figure 1 is a schematic diagram of an application scenario of a data processing system shown in some embodiments of this specification;

[0013] Figure 2 is an exemplary block diagram of a processing device shown in some embodiments of this specification;

[0014] Figure 3An exemplary flowchart of a data processing method according to some embodiments of this specification;

[0015] Figure 4 An exemplary flowchart of a data verification round according to some embodiments of this specification;

[0016] Figure 5 An exemplary flowchart of determining target data according to some embodiments of this specification;

[0017] Figure 6 An exemplary module diagram of a data processing system according to some embodiments of this specification; and

[0018] Figure 7 An exemplary module diagram of another data processing system according to some embodiments of this specification. Detailed implementation manners

[0019] To more clearly illustrate the technical solutions of the embodiments of this specification, the accompanying drawings required for the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some examples or embodiments of this specification. For those of ordinary skill in the art, without creative efforts, this specification can also be applied to other similar scenarios based on these drawings. Unless obvious from the language context or otherwise stated, the same reference numerals in the figures represent the same structure or operation.

[0020] It should be understood that the "system", "device", "unit" and / or "module" used herein is a way to distinguish different components, elements, parts, portions or assemblies at different levels. However, if other words can achieve the same purpose, the said words can be replaced by other expressions.

[0021] As shown in this specification and the claims, unless the context clearly indicates an exception, words such as "a", "an", "one" and / or "the" are not specifically singular and may also include the plural. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of the clearly identified steps and elements, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements.

[0022] Flowcharts are used in this specification to illustrate the operations performed by the systems according to the embodiments of this specification. It should be understood that the operations before or after may not be executed precisely in sequence. On the contrary, the steps can be processed in reverse order or simultaneously. At the same time, other operations can also be added to these processes, or one or several steps can be removed from these processes.

[0023] At present, the calculation of international freight rates generally includes offline freight rate calculation and online real-time calculation. Offline freight rate calculation analyzes historical user search data and order data to predict users' search routes and dates, and generates salable freight rate data offline every day by inputting the predicted retrieval parameters for users to retrieve. However, this method faces problems such as long calculation time, low accuracy of freight rate data, and missing freight rate data. Online real-time calculation uses a high-performance server to calculate salable freight rates by inputting users' search parameters in real time. However, this method faces problems such as high input costs and unstable calculation efficiency.

[0024] Based on this, in some embodiments of this specification, a data processing method based on cluster scale is proposed, which can calculate combined freight rates in parallel, improve the calculation speed, and reduce the calculation consumption.

[0025] Figure 1 It is an application scenario diagram of an exemplary data processing system shown in some embodiments of this specification. In some embodiments, the data processing system can be used to perform processing operations on freight rate data, such as data deletion, data addition, data modification, etc. As Figure 1 shown, the application scenario 100 may include a processing device 110, a storage device 120, a terminal 130, a network 140, and a data source 150.

[0026] The processing device 110 can be used to execute one or more functions disclosed in this specification. For example, the processing device 110 can obtain freight data and at least one freight rate processing task. For another example, the processing device 110 can determine the combined freight rate related to each freight rate processing task and the index corresponding to the combined freight rate based on the freight rate data. For still another example, the processing device 110 can transmit the above data to local for storage. For yet another example, the processing device 110 can receive external input and determine available freight rates according to the external data and display the available freight rates to the outside. In some embodiments, the processing device 110 can be an independent server or a server group. The server group can be centralized or distributed (e.g., the processing device 110 can be a distributed system). In some embodiments, the processing device 110 can be directly connected to the storage device 120 and the terminal 130 to access the information and / or data stored therein. In some embodiments, the processing device 110 can be executed on a cloud platform. For example, the cloud platform can include one or any combination of a private cloud, a public cloud, a hybrid cloud, a community cloud, a decentralized cloud, an internal cloud, etc.

[0027] In some embodiments, the processing device 110 may include one or more processing engines (e.g., a single-core processing engine or a multi-core processor). By way of example only, the processing device 110 may include a central processing unit (CPU), an application specific integrated circuit (ASIC), an application specific instruction set processor (ASIP), a graphics processing unit (GPU), a physics processing unit (PPU), a digital signal processor (DSP), a field programmable gate array (FPGA), a programmable logic device (PLD), a controller, a microcontroller unit, a reduced instruction set computer (RISC), a microprocessor, or a combination of one or more of the foregoing.

[0028] The storage device 120 may store data and / or instructions. In some embodiments, the storage device 120 may store data and / or instructions. The processing device 110 may execute or use the data and / or instructions to implement the exemplary methods in this specification. In some embodiments, the storage device 120 may be connected to the network 140 to communicate with one or more components in 100 (e.g., the processing device 110, the terminal 120, etc.). One or more components of the application scenario 100 may access the data or instructions stored in the storage device 120 through the network 140. In some embodiments, the storage device 120 may be directly connected to or communicate with one or more components of the application scenario 100 (e.g., the processing device 110, the terminal 120, the data source 150, etc.). In some embodiments, the storage device 120 may be part of the processing device 110. For example, the storage device 120 may be a local storage device of the processing device 110, such as a disk.

[0029] In some embodiments, the storage device 120 may include a mass storage device, a removable memory, a volatile read-write memory, a read-only memory (ROM), etc. or any combination thereof. Exemplary mass storage devices may include magnetic disks, optical disks, solid state disks, etc. Exemplary removable memories may include flash drives, floppy disks, optical disks, memory cards, compact disks, magnetic tapes, etc. Exemplary volatile read-only memories may include random access memory (RAM). Exemplary RAM may include dynamic RAM (DRAM), double data rate synchronous dynamic RAM (DDR SDRAM), static RAM (SRAM), thyristor RAM (T-RAM), and zero capacitor RAM (Z-RAM), etc. Exemplary ROM may include mask ROM (MROM), programmable ROM (PROM), erasable programmable ROM (PEROM), electrically erasable programmable ROM (EEPROM), CD-ROM, and digital versatile disk ROM, etc. In some embodiments, the storage device 120 may be implemented on a cloud platform. By way of example only, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an internal cloud, a multi-layer cloud, etc. or any combination thereof. For example, some algorithms or data disclosed in this specification may be stored on a certain cloud platform and updated regularly. The processing device 110 accesses these algorithms or data through a network to achieve the unification and interaction of the algorithms or data of the entire platform. In particular, some historical data may be uniformly stored on a cloud platform of the platform for multiple processing devices 110 or terminals 120 to access or update, so as to ensure the real-time nature and cross-platform use of the data.

[0030] The terminal 130 can be a device with data acquisition, storage, and / or transmission functions. For example, the terminal 130 can acquire travel information input by a user (who can also be referred to as the "user" of the terminal 130 in this specification) on the terminal 130 and transmit this travel information to the processing device 110. The processing device 110 can determine the itinerary fare corresponding to the travel information, such as the international flight fare, and transmit the fare to the terminal 130. The terminal 130 can display the international flight fare to the user after receiving it. For example, display it on a display screen. In some embodiments, the terminal 130 can include, but is not limited to, a smart mobile device 130-1, a tablet computer 130-2, a laptop computer 130-3, a desktop computer 130-4, etc., or any combination thereof. In some embodiments, the terminal 130 can send the acquired data to one or more devices in the application scenario 100. For example, the terminal 130 can transmit the acquired data to the processing device 110 or the storage device 120. In some embodiments, the terminal 130 can be a part of the processing device 110. For example, the terminal 130 can serve as a front-end operation device of the processing device 110 of the background server, and the user can send operation instructions to the processing device 110 through the terminal 130 to modify and / or update the data processing logic of the processing device 110.

[0031] The network 140 can facilitate the exchange of information and / or data. In some embodiments, one or more components of the application scenario 100 (such as the processing device 110, the storage device 120, the terminal 130, and the data source 150) can transmit information to other components of the application scenario 100 through the network 140. For example, the processing device 110 can obtain fare data from the storage device 120 through the network 140. In some embodiments, the network 140 can be any form of wired or wireless network, or any combination thereof. By way of example only, the network 140 can be a wired network, an optical fiber network, a telecommunications network, an internal network, the Internet, a local area network (LAN), a wide area network (WAN), a wireless local area network (WLAN), a metropolitan area network (MAN), a wide area network (WAN), a public switched telephone network (PSTN), a Bluetooth TM network, a ZigBee TMOne or more combinations of a network, a Near Field Communication (NFC) network, a Global System for Mobile Communications (GSM) network, a Code Division Multiple Access (CDMA) network, a Time Division Multiple Access (TDMA) network, a General Packet Radio Service (GPRS) network, an Enhanced Data Rate for GSM Evolution (EDGE) network, a Wideband Code Division Multiple Access (WCDMA) network, a High-Speed Downlink Packet Access (HSDPA) network, a Long Term Evolution (LTE) network, a User Datagram Protocol (UDP) network, a Transmission Control Protocol / Internet Protocol (TCP / IP) network, a Short Message Service (SMS) network, a Wireless Application Protocol (WAP) network, an Ultra-Wideband (UWB) network, a mobile communication (1G, 2G, 3G, 4G, 5G) network, Wi-Fi, Li-Fi, a Narrowband Internet of Things (NB-IoT), infrared communication, etc. In some embodiments, network 140 may include one or more network access points. For example, network 140 may include wired or wireless network access points such as base stations and / or Internet exchange points. Through this network access point, one or more components of application scenario 100 may be connected to network 140 to exchange information and / or data.

[0032] Data source 150 may provide a data source for the operation of other components in scenario 100. In some embodiments, informant 150 may provide original freight rate data. For example, airline freight rate data published by ATPCO (Airline Tariff Publishing Company). In some embodiments, data source 150 may also provide other data required for determining the freight rate. For example, weather conditions, geographical information, time data, etc. In some embodiments, data source 150 may be other third-party platforms. For example, data source 150 may be the data server of ATPCO. Data source 150 may be implemented in a single central server, multiple servers connected by a communication link, or multiple personal devices. When data source 150 is implemented in multiple personal devices, the personal devices may generate content (e.g., referred to as "user-generated content"), for example, by uploading text, voice, images, and videos to a cloud server. Then data source 150 may be generated by multiple personal devices and the cloud server. Processing device 110, storage device 120, and terminal 130 may also be information sources at the same time. For example, terminal 130 may provide the weather conditions at the real-time location as source data for other devices to obtain and use.

[0033] Figure 21 is a block diagram illustrating an exemplary processing device according to some embodiments of this specification. Processing device 110 may include any components used to implement the system described in the embodiments of this specification. For example, processing device 110 may be implemented using hardware, software programs, firmware, or a combination thereof. For convenience, only one processing device is depicted in the figure, but the computing functions related to application scenario 100 described in the embodiments of this specification can be implemented in a distributed manner by a group of similar platforms to disperse the processing load of the system.

[0034] In some embodiments, the processing device 110 may include a processor 210, a memory 220, an input / output component 230, and a communication port 240. In some embodiments, the processor (e.g., CPU) 210 may execute program instructions in the form of one or more processors. In some embodiments, the memory 220 includes different forms of program memory and data memory, such as a hard disk, a read-only memory (ROM), a random access memory (RAM), etc., for storing various data files processed and / or transmitted by the computer. In some embodiments, the input / output component 230 may be used to support input / output between the processing device 110 and other components. In some embodiments, the communication port 240 may be connected to a network for data communication. An exemplary processing device may include program instructions executed by the processor 210 stored in a read-only memory (ROM), a random access memory (RAM), and / or other types of non-transitory storage media. The methods and / or processes of the embodiments of this specification may be implemented in the form of program instructions. The processing device 110 may also receive the programs and data disclosed in this specification via network communication.

[0035] For ease of understanding, Figure 2 Only one processor is shown in the figure as an example. However, it should be noted that the processing device 110 in the embodiments of this specification may include multiple processors, and therefore the operations and / or methods implemented by one processor described in the embodiments of this specification may also be implemented jointly or independently by multiple processors. For example, if in this specification, the processor of the processing device 110 performs steps 1 and 2, it should be understood that steps 1 and 2 may also be performed jointly or independently by two different processors of the processing device 110 (for example, the first processor performs step 1 and the second processor performs step 2, or the first and second processors perform steps 1 and 2 jointly).

[0036] Figure 3is an exemplary flowchart of a freight rate data processing method shown in some embodiments of this specification. In some embodiments, process 300 may be executed by processing device 110. Processing device 110 may be a distributed processing system composed of multiple processing nodes. Process 300 may be executed simultaneously by multiple processing nodes in processing device 110 to implement a parallel processing operation. For example, process 300 may be stored in a storage device (such as the built-in storage unit of processing device 110, such as memory 220, or an external storage device, such as storage device 120) in the form of a program or instruction. When the program or instruction is extracted and executed by the processing node, process 300 may be implemented. In some embodiments, process 300 may be executed by the first processing system 600. As Figure 3 shown, process 300 may include the following operations.

[0037] Step S310, obtain freight rate data and at least one freight rate processing task. This step may be executed by the first obtaining module 610.

[0038] In some embodiments, the freight rate data may be the freight rate data published by a freight rate data publisher. The freight rate data publisher may be the Airline Tariff Publishing Company (ATPCO), the International Air Transport Association (IATA), China Civil Aviation Information Network Co., Ltd. (TravelSky), etc. In some embodiments, the freight rate data may be the ATPCO freight rate data published by ATPCO. As an example, the ATPCO freight rate data may be composed of Fare and Rule. Fare may include Throughfare and Add-on. Rule may include Fareclass, Category, RBD, and Routing. In some embodiments, the freight rate data may be the preprocessed ATPCO freight rate data. The preprocessing may be an operation of identifying / extracting / merging the valid data in the original ATPCO freight rate data. For example, the ATPCO freight rate data may be published in the form of an FTP file. However, the FTP file is not conducive to computer processing. Then the preprocessing may be to identify the above-mentioned valid data in the FTP file and merge and convert it into other file forms that are easier to store and calculate, such as NSD files.

[0039] In some embodiments, a fare processing task can be used to determine a fare (e.g., a candidate fare) for an air itinerary. It is understood that different fares can exist for a flight from a particular departure point to a particular destination, depending on the carrier, specific route, time, and various restrictions. Therefore, a fare processing task can be used to determine a calculated fare for a flight under certain conditions. This calculated fare can serve as a candidate fare and be offered to passengers if certain conditions are met.

[0040] In some embodiments, the fare processing task can be constructed based on at least one of the following task component dimensions: airline, fare definition number (TarrifNo), and fare restriction rule number (RuleNo). Fare definitions are developed by ATPCO based on flight geographic regions and are categorized as Public and Private, containing elements such as Fare, Rules, General Rules, Arbitrary, Routing, GI, and Area. The fare definition number can be a numerical and / or alphanumeric identifier that can include subnumbers for each element. The fare restriction rule number can also be a numerical and / or alphanumeric code that indicates the fare restriction rules, such as sales rules. Different airlines, fare definition numbers, and fare restriction rule numbers can be permuted and combined to generate different fare processing tasks (e.g., <AirlineX, TarrifNoY, RuleNoZ>). Each fare processing task can have a corresponding combined fare (e.g., the combined fare determined in step 320) based on the above task component dimensions. In some embodiments, the fare processing task may be based on at least the airline, fare definition number (TarrifNo) and fare restriction rule number (RuleNo) components. It is understood that dimensions such as time may also participate in the formation of the fare processing task.

[0041] In some embodiments, the freight rate data and the freight rate processing task may be pre-acquired, processed, generated, and stored in a data storage device (e.g., a memory included in the processing device 110 (or the first processing system 600), such as the memory 210 or the storage device 120). The first acquisition module 610 may communicate with the above data storage device to obtain the freight rate data and the at least one freight rate processing task.

[0042] Step S320 : For each freight rate processing task, determine the combined freight rate associated with the freight rate processing task and the index corresponding to the combined freight rate based on the freight rate data. This step may be performed by the first determining module 620 .

[0043] In some embodiments, the combined fare may refer to the calculated fare for a certain itinerary. As an example, assume there is a flight from origin A to destination B. If the flight is a direct flight, there may be a direct fare. If the flight is a non-direct flight, there may be a proportionate fare (A - C, C - B). However, the above fares cannot be directly sold to passengers. Many restrictive conditions will result in the final fare being different from the above fares. The combined fare is a candidate final fare determined according to certain calculation rules under many restrictive conditions. After meeting the verification conditions, the flight fare between A and B can be sold at the combined fare. Based on the foregoing description, the task composition dimensions constituting the fare processing task have indicated the restrictive conditions for calculating the combined fare. The first determination module 620 may obtain relevant data according to the task composition dimensions and determine the combined fare corresponding to the fare processing task based on these relevant data.

[0044] In some embodiments, the index corresponding to the combined fare may be the unique label of the restrictive conditions (such as fare restriction rules) used in the calculation of the combined fare. As an example, the restrictive conditions used may have a tree structure or a hierarchical structure. For example, the restrictive conditions may have a main restrictive range (such as the root node of a tree), and under this main restrictive range, there may be lower-level secondary restrictive ranges or sub-restrictive ranges (such as the leaf nodes of the tree). If the tree branches, there may be two or more parallel secondary restrictive ranges or sub-restrictive ranges. Each restrictive range has an independent number, for example, a combination of numbers and / or characters. The determination module 630 may determine a unique number corresponding to the restrictive conditions according to these numbers. And use this number as the index of the combined fare.

[0045] For the determination of the combined fare related to the fare processing task and the determination of the index corresponding to the combined fare, reference may be made to other parts of this specification. For example, Figure 4 Part.

[0046] Step S330, transmit at least one combined fare and at least one index related to at least one fare processing task to the local storage device. This step may be executed by the transmission module 630.

[0047] In some embodiments, the local storage device may be the built-in storage unit of the processing device 110, such as the memory 220, or the storage unit possessed by the processing node itself. Or, the local storage device may be the storage module of the first processing system 600 ( Figure 6 not shown in the figure). After the transmission module 630 obtains the combined fare related to the fare processing task and the index corresponding to the combined fare, it can directly transmit them to the local storage device for storage. In this way, the data is stored locally, which can improve the data pulling speed and reduce resource overhead when used later.

[0048] It should be noted that the descriptions of the respective steps in the above Figure 3 are only for illustration and explanation, and do not limit the scope of application of this specification. For those skilled in the art, various corrections and changes can be made to the Figure 3 respective steps under the guidance of this specification. However, these corrections and changes are still within the scope of this specification. For example, a data storage operation can be performed after each step.

[0049] Figure 4 is an exemplary flowchart of a processing method for a freight rate processing task according to some embodiments of this specification. In some embodiments, process 400 can be executed by processing device 110. Processing device 110 can be a distributed processing system composed of multiple processing nodes. Process 300 can be implemented by any one of the processing nodes in processing device 110. For example, process 400 can be stored in a storage device (such as the built-in storage unit of processing device 110, such as memory 220, or an external storage device, such as storage device 120) in the form of a program or instruction. When the program or instruction is retrieved and executed by the processing node, process 300 can be implemented. In some embodiments, process 400 can be executed by first determination module 620. As Figure 4 shown, process 400 can include the following operations.

[0050] Step S410, obtaining relevant calculation data from the freight rate data based on the task composition dimension.

[0051] Combined with the description in process 300, assuming that the representation of the fare processing task is <Airline X, TarrifNo Y, RuleNo Z>, the relevant calculation data may include Fare, FareRecord, and Category. Fare may include ThroughFare (direct fare) and / or Add-on (proportional fare). FareRecord (fare record) may include fare-related information such as the actual fare price, the operating airline, Tariff, etc. Category may be the content in specific fare restriction rules. Generally, Category may include 35 different rules. RuleNo may be used to indicate specific fare restriction rules. Each of the 35 rules in Category has its own numerical number. RuleNo may be any combination of these numbers and hierarchical symbols. For example, RuleNo may be expressed as (02, -14, --15). The numbers represent the corresponding content in Category. For example, 02 is the date / time restriction (DAY / TIME), 14 is the travel restriction (TRAVEL RESTRICTIONS), and 15 is the sales restriction (SALES RESTRICTIONS). The symbols before the numbers may represent the hierarchy. For example, no symbol before the number represents the fare restriction rule of the first level, "-" represents the fare restriction rule of the second level, and "--" represents the fare restriction rule of the third level going down. And so on.

[0052] In some embodiments, the first determination module 620 may obtain the relevant calculation data from the fare data according to the information carried by the task composition dimension that constitutes the fare processing task. For example, the first determination module 620 may look up the relevant data of each element from the fare data according to TarrifNo and obtain the content of the corresponding Category according to RuleNo. Subsequently, these data may be extracted and designated as the relevant calculation data.

[0053] Step S420, based on the relevant calculation data, use the first preset calculation rule to determine the combined fare related to the fare processing task.

[0054] In some embodiments, the first predefined calculation rule may be a calculation rule adapted to the freight rate data. For example, assuming that the freight rate data is ATPCO freight rate data published by ATPCO, the first predefined calculation rule may also be a freight rate calculation rule published by ATPCO for calculating freight rates based on ATPCO freight rate data. Similarly, if the freight rate data is IATA freight rate data published by IATA, the first predefined calculation rule may also be a freight rate calculation rule published by IATA for calculating freight rates based on IATA freight rate data. In some embodiments, the freight rate data includes ATPCO freight rate data (or preprocessed ATPCO freight rate data), and the first predefined calculation rule may include an ATPCO calculation rule.

[0055] The specific process of determining the combined freight rate may be common in the aviation field and will not be elaborated here again.

[0056] Step S430: Obtain the freight rate limit rule number for constructing the freight rate processing task.

[0057] In some embodiments, the freight rate limit rule number may be included in the task composition dimension of the freight rate processing task. For example, RuleNo in the task composition dimension indicates the freight rate limit rule number. The first determination module 620 may obtain the freight rate limit rule number by directly analyzing the task composition dimension of the freight rate processing task.

[0058] Step S440: Based on the freight rate limit rule number, use the second predefined calculation rule to determine the target identifier corresponding to the freight rate limit rule number, and specify the target identifier as the index corresponding to the combined freight rate.

[0059] In some embodiments, the second predefined calculation rule may be a unique number conversion rule that can convert multiple numbers (including numbers at different levels) into a unique identifier. For a simple example, the second predefined calculation rule may be expressed as follows: f = ax + by + cz + …. Where f represents the result obtained after conversion, a, b, c, and so on can represent known mathematical expressions, such as known parameters such as 1, 3, 5, etc., and established mathematical operations such as square root. The selection of a, b, c, and so on can make the calculated values arranged in order. For example, the value of ax is an integer, the value of by can be a value with one decimal place such as 0.5, and the value of cz can be a value with two decimal places such as 0.07. x, y, z, and so on represent the numbering of the freight rate limit rules at each level. For example, x represents the numbering of the freight rate limit rule at the first level, y represents the numbering of the freight rate limit rule at the second level, z represents the numbering of the freight rate limit rule at the third level, and so on. Substituting the numbering of the freight rate limit rules at each level into the second predefined calculation rule can obtain a unique value. This value can be used as the target identifier corresponding to the freight rate limit rule number. Through this target identifier, the combined freight rate related to the freight rate processing task can be determined. There is a corresponding relationship between the two. The first determination module 620 can use the target identifier as the index corresponding to the combined freight rate.

[0060] It should be noted that the descriptions of the above Figure 4 for each step are only for illustration and explanation, and do not limit the scope of application of this specification. For those skilled in the art, under the guidance of this specification, various corrections and changes can be made to Figure 4 each step. However, these corrections and changes are still within the scope of this specification. For example, a data storage operation can be performed after each step.

[0061] Figure 5 is an exemplary flowchart of a data processing method shown according to some embodiments of this specification. In some embodiments, process 500 can be executed by processing device 110. For example, process 500 can be stored in a storage device (such as the built-in storage unit of processing device 110, such as memory 220, or an external storage device, such as storage device 120) in the form of a program or instruction. When the program or instruction is extracted and executed by a processing node, process 500 can be implemented. In some embodiments, process 500 can be executed by second processing system 700. As Figure 5 shown, process 500 may include the following operations.

[0062] Step S510, obtain freight rate retrieval data and determine a planned itinerary based on the freight rate retrieval data. This step can be executed by second acquisition module 710.

[0063] In some embodiments, the fare retrieval data may be data for retrieving travel fares input from the outside. For example, a user of the terminal 130 (such as a passenger who needs to purchase an air ticket) may input the fare data in a mobile application (which may also be referred to as an APP) installed on the terminal 130 (such as a smart mobile phone). The terminal 130 may transmit the fare retrieval data to the processing device 110 (or the second processing system 700) through the network 120. In some embodiments, the fare retrieval data may at least include the departure place and the destination. For example, if the user's planned itinerary is from Shanghai to New York, then Shanghai as the departure place and New York as the destination may be input by the user and then acquired by the second acquisition module 710. In some embodiments, the fare retrieval data may further include other data, such as the departure time, the number of passengers, the personal information of the passengers, etc.

[0064] In some embodiments, after acquiring the fare retrieval data, the second acquisition module 710 may determine the planned itinerary. The planned itinerary is an itinerary that meets the fare retrieval data input by the user. For example, assuming that the fare retrieval data includes the departure place and the destination, then the planned itinerary may be an air route between the departure place and the destination. This air route may be direct or may involve transfers. Exemplarily, the second acquisition module 710 may determine the planned itinerary by retrieving relevant information about the departure place and the destination (such as whether there is an airport, whether passenger air service is provided, the available flight routes, etc.).

[0065] Step S420: Acquire flight information and its related data adapted to the planned itinerary, and determine the calculated fare corresponding to the planned itinerary at least based on the flight information and its related data using the fare calculation rules. This step may be executed by the second determination module 720.

[0066] In some embodiments, the flight information adapted to the planned itinerary may include information on all flights that can complete the planned itinerary. For example, if the planned itinerary is from Shanghai to New York. Then the flight information adapted to the planned itinerary may include information on all flights providing air passenger service from Shanghai to New York. The relevant information of the flight information may include specific information about the flight schedule, including but not limited to flight number, inventory, cabin class, flight direction, etc.

[0067] In some embodiments, the freight rate calculation rule may include the ATPCO freight rate calculation rule. The second determination module 720 may use the freight rate calculation rule to determine the planned freight rate based on the flight information and its related data, as well as the passenger related information (e.g., passenger name, age, etc.). The planned freight rate may be a candidate freight rate. It can also be understood as a freight rate whose availability has not been verified. To some extent, it can reflect the cost that the user needs to pay to complete the trip, but it is not the actual cost that finally needs to be paid.

[0068] Step S530, determine the constraints corresponding to the calculated freight rate, and obtain the determination of whether the calculated freight rate meets the display condition. This step may be performed by the third determination module 730.

[0069] In some embodiments, the constraints corresponding to the planned freight rate may refer to the freight rate limitation rules that will make the planned freight rate. For the description of the freight rate limitation rules, reference may be made to the foregoing part. In some embodiments, the third determination module 730 may use the combined freight rate determined in process 400 and the combined freight rate-index data set formed by the indexes to determine the constraints corresponding to the planned freight rate. In process 400, after each processing node determines the combined freight rate related to its respective freight rate processing task and the index corresponding to the combined freight rate, they may be stored in the local storage device. All the combined freight rates and their corresponding indexes constitute the above-mentioned combined freight rate-index data set. This data set may exist in the form of a table or a mapping set, and is not limited. Therefore, the third determination module 730 may communicate with the local storage device to obtain the combined freight rate-index data set.

[0070] In some embodiments, the third determination module 730 may determine the combined freight rate in the combined freight rate-index data set that matches the calculated freight rate. The matching may include that the calculated freight rate is equal to the combined freight rate, or the difference between the calculated freight rate and the combined freight rate is less than a predetermined threshold, such as 0.5 or 1. The third determination module 730 may compare with each combined freight rate in the combined freight rate-index data set to determine the combined freight rate that matches the planned freight rate.

[0071] In some embodiments, the third determination module 730 may obtain the index corresponding to the combined freight rate that matches the calculated freight rate. Obviously, according to the combined freight rate-index data set, after determining the combined freight rate, the third determination module 730 may directly determine the index.

[0072] In some embodiments, the third determination module 730 may determine the freight rate limit rule number corresponding to the index based on the third pre-designed calculation rule. Combining with the description of step S440 in process 400, the third pre-designed calculation rule may be a reverse presentation of the second pre-designed calculation rule. The second pre-designed calculation rule is used to convert the freight rate limit rule number into a unique index, while the third pre-designed calculation rule converts this index into the corresponding freight rate limit rule number. Exemplarily, the preset second pre-designed calculation rule is to substitute a value (e.g., the freight rate limit rule number) into an equation to obtain a result (e.g., an index), and the third pre-designed calculation rule may be to inversely calculate the value substituted into the equation based on the result.

[0073] In some embodiments, after determining the freight rate limit rule number corresponding to the index, the third determination module 730 may directly use the freight rate limit rule corresponding to the freight rate number as the constraint.

[0074] In some embodiments, the display condition may mean that the planned freight rate is available and can be displayed to the user for the user to choose to purchase. As described above, the planned freight rate is a candidate freight rate, not a final freight rate. It can only be sold after verifying its availability. When the planned freight rate meets the display condition, the planned freight rate can be considered as an available actual freight rate for the itinerary. The user can pay the corresponding fee to obtain the corresponding travel voucher (i.e., air ticket) and start traveling at the subsequent specified time. In some embodiments, the calculation of whether the freight rate meets the display condition may be performed by a third-party verification agency. The third determination module 730 may send the calculated freight rate and the constraint corresponding to the calculated freight rate to the third-party agency. The third-party agency may use the constraint corresponding to the calculated freight rate to verify the availability of the calculated freight rate and return a verification result, that is, a determination of whether the calculated freight rate meets the display condition. In some embodiments, the third determination module 730 may perform the verification operation itself to determine whether the calculated freight rate is available.

[0075] Step S540, perform the display or concealment operation of the calculated freight rate based on the determination. This step may be executed by the execution module 740.

[0076] In some embodiments, the determination may include that the calculated fare is available and the calculated fare is unavailable. When the planned fare is available, it can indicate that the calculated fare can be used as the actual cost that a user needs to pay for a trip. The execution module 740 may perform a display operation on the planned fare. The display operation may be to send the planned fare as the trip price to the front end, such as the terminal 130, and the terminal 130 displays it to the user. It indicates the available trip price obtained before the fare retrieval data input by the user this time. When the planned fare is unavailable, it can indicate that the calculated fare cannot be used as the actual cost that a user needs to pay for a trip. The execution module 740 may perform a hiding operation on the planned fare. The hiding operation may mean not transmitting the planned fare to the front end, such as the terminal 130, and displaying it to the user.

[0077] It should be noted that the descriptions of the above Figure 4 for each step are only for illustration and explanation, and do not limit the scope of application of this specification. For those skilled in the art, under the guidance of this specification, various corrections and changes can be made to Figure 4 each step. However, these corrections and changes are still within the scope of this specification. For example, a data storage operation can be performed after each step.

[0078] Figure 6 is an exemplary module diagram of a fare data processing system shown according to some embodiments of this specification. A fare data processing system can be used as a processing node and jointly form a cluster system with multiple other fare processing systems. As Figure 6 shown, the fare data processing system 600 may include a first acquisition module 610, a first determination module 620, and a transmission module 630.

[0079] The first acquisition module 610 can acquire data. In some embodiments, the first acquisition module 610 can acquire fare data and at least one fare processing task. The fare data may be the fare data published by the fare data publisher. The fare processing task may be a task for determining the fare of an air travel itinerary. The fare data may include preprocessed ATPCO fare data. The fare processing task may be constructed based on at least one of the following task composition dimensions: airline, fare definition number, or fare restriction rule number.

[0080] The first determination module 620 can determine, based on the freight rate data, a combined freight rate associated with the freight rate processing task and an index corresponding to the combined freight rate. For each freight rate processing task, the first determination module 620 can retrieve relevant calculation data from the freight rate data based on the task component dimensions. Based on the relevant calculation data, the first determination module 620 can determine the combined freight rate associated with the freight rate processing task using a first preset calculation rule. The first preset calculation rule can include an ATPCO calculation rule.

[0081] In some embodiments, the first determination module 620 may obtain the fare restriction rule number for constructing the fare processing task, and determine the target identifier corresponding to the fare restriction rule number based on the fare restriction rule number using a second preset calculation rule. Subsequently, the first determination module 620 may specify the target identifier as the index corresponding to the combined fare.

[0082] The transmission module 630 can transmit at least one combined freight rate and at least one index related to the at least one freight rate processing task to a local storage device. The local storage device can be a storage unit of the freight rate processing system 600, such as a storage module ( Figure 6 not shown).

[0083] about Figure 6 For other descriptions of the modules in , please refer to the flowchart section of this manual, for example, Figure 3 .

[0084] Figure 7 is an exemplary module diagram of a data processing system according to some embodiments of this specification. Figure 7 As shown, the data processing system 700 may include a second acquisition module 710 , a second determination module 720 , a third determination module 730 and an execution module 740 .

[0085] The second acquisition module 710 can acquire fare retrieval data and determine a planned itinerary based on the fare retrieval data. The fare retrieval data can be data input from the outside for retrieving travel fares. The planned itinerary can be an itinerary that meets the fare retrieval data input by the user.

[0086] The second determination module 720 may obtain flight information and related data suitable for the planned itinerary, and determine a calculated fare corresponding to the planned itinerary using fare calculation rules based at least on the flight information and related data. The flight information suitable for the planned itinerary may include information about all flights that can complete the planned itinerary, and the relevance information of the flight information may include specific information about flight schedules. The fare calculation rules may include ATPCO fare calculation rules.

[0087] The second determination module 730 may determine the constraints corresponding to the calculated freight rate and obtain a determination of whether the calculated freight rate meets the display condition. The constraints corresponding to the planned freight rate may refer to the freight rate limit rules that will make the planned freight rate. The third determination module 730 may determine the combined freight rate in the combined freight rate-index dataset that matches the calculated freight rate and obtain the index corresponding to the combined freight rate that matches the calculated freight rate. The third determination module 730 may determine the freight rate limit rule number corresponding to the index based on the third preset calculation rule. After determining the freight rate limit rule number corresponding to the index, the third determination module 730 may directly use the freight rate limit rule corresponding to the freight rate limit number as the constraint. In some embodiments, the third determination module 730 may send the calculated freight rate and the constraints corresponding to the calculated freight rate to a third party and obtain a return result from the third party. The third determination module 730 may also perform a determination operation itself.

[0088] The execution module 740 may perform a display or concealment operation on the calculated freight rate based on the determination. The determination may include that the calculated freight rate is available and that the calculated freight rate is unavailable. When the planned freight rate is available, the execution module 740 may perform a display operation on the planned freight rate. When the planned freight rate is unavailable, it may indicate at this time that the calculated freight rate cannot be used as the actual cost that a user needs to pay for a trip, and the execution module 740 may perform a concealment operation on the planned freight rate.

[0089] Regarding Figure 7 For other descriptions of the modules in Figure 4 and Figure 5 .

[0090] It should be understood that Figure 6 and Figure 7The system and its modules shown can be implemented in various ways. For example, in some embodiments, the system and its modules can be implemented through hardware, software, or a combination of software and hardware. Among them, the hardware part can be implemented using dedicated logic; the software part can be stored in a memory and executed by an appropriate instruction execution system, such as a microprocessor or dedicated designed hardware. Those skilled in the art can understand that the above methods and systems can be implemented using computer-executable instructions and / or included in processor control code. For example, such code is provided on a carrier medium such as a disk, CD, or DVD-ROM, a programmable memory such as a read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The system and its modules of this specification can be implemented not only by hardware circuits such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips and transistors, or programmable hardware devices such as field programmable gate arrays and programmable logic devices, but also by software executed by various types of processors, or by a combination of the above hardware circuits and software (for example, firmware).

[0091] It should be noted that the above description of the candidate display and determination of the system and its modules is only for convenience of description and does not limit this specification within the scope of the examples given. It can be understood that for those skilled in the art, after understanding the principle of the system, they may, without departing from this principle, make any combination of the modules, or form a subsystem and connect it with other modules. For example, the modules can share a storage module, or each module can have its own storage module respectively. Such variations are all within the protection scope of this specification.

[0092] The beneficial effects that the embodiments of this specification may bring include but are not limited to: (1) The combined freight rate is calculated in a cluster manner, with short calculation time and less resource consumption; (2) The composition of the freight rate processing task uses all data, avoiding the lack of the calculated combined freight rate; (3) Indexes of the component combined freight rate and freight rate limit rules are used to filter out invalid rules; and the data is stored in the local node, improving the data extraction speed and reducing the input cost; (4) The overall cluster scale is scalable.

[0093] The basic concepts have been described above. Obviously, for those skilled in the art, the above detailed disclosure is only an example and does not constitute a limitation to this specification. Although not explicitly stated here, those skilled in the art may make various modifications, improvements, and corrections to this specification. Such modifications, improvements, and corrections are proposed in this specification, so such modifications, improvements, and corrections still belong to the spirit and scope of the exemplary embodiments of this specification.

[0094] Meanwhile, this specification uses specific terms to describe the embodiments of this specification. For example, "an embodiment", "one embodiment", and / or "some embodiments" mean a certain feature, structure, or characteristic related to at least one embodiment of this specification. Therefore, it should be emphasized and noted that the "one embodiment" or "an embodiment" or "an alternative embodiment" mentioned twice or more at different positions in this specification does not necessarily refer to the same embodiment. In addition, certain features, structures, or characteristics in one or more embodiments of this specification can be appropriately combined.

[0095] In addition, those skilled in the art can understand that various aspects of this specification can be illustrated and described by several patentable types or situations, including any new and useful process, machine, product, or composition of matter, or any new and useful improvement thereof. Accordingly, various aspects of this specification can be executed entirely by hardware, entirely by software (including firmware, resident software, microcode, etc.), or by a combination of hardware and software. The above hardware or software can all be referred to as "data blocks", "modules", "engines", "units", "components", or "systems". In addition, various aspects of this specification may be embodied as a computer product located in one or more computer-readable media, which includes computer-readable program code.

[0096] A computer storage medium may contain a propagated data signal containing computer program code, such as on a baseband or as part of a carrier wave. This propagated signal may have various forms of manifestation, including electromagnetic form, optical form, etc., or a suitable combination thereof. A computer storage medium can be any computer-readable medium other than a computer-readable storage medium, which can be connected to an instruction execution system, apparatus, or device to implement communication, propagation, or transmission of a program for use. The program code located on the computer storage medium can be propagated through any suitable medium, including radio, cable, fiber optic cable, RF, or similar media, or any combination of the above media.

[0097] The computer program codes required for the operations of each part of this specification can be written in any one or more programming languages, including object-oriented programming languages such as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C++, C#, VB.NET, Python, etc., conventional procedural programming languages such as C language, Visual Basic, Fortran 2003, Perl, COBOL 2002, PHP, ABAP, dynamic programming languages such as Python, Ruby and Groovy, or other programming languages. The program codes can run entirely on the user's computer, or run on the user's computer as an independent software package, or partially run on the user's computer and partially on a remote computer, or run entirely on a remote computer or server. In the latter case, the remote computer can be connected to the user's computer through any network form, such as a local area network (LAN) or a wide area network (WAN), or connected to an external computer (for example, through the Internet), or in a cloud computing environment, or used as a service such as software as a service (SaaS).

[0098] In addition, unless explicitly stated in the claims, the order of the processing elements and sequences, the use of numbers and letters, or the use of other names in this specification are not used to limit the order of the processes and methods in this specification. Although some currently considered useful embodiments of the invention are discussed through various examples in the above disclosure, it should be understood that such details only serve the purpose of illustration, and the appended claims are not limited to the disclosed embodiments. On the contrary, the claims are intended to cover all modifications and equivalent combinations that conform to the essence and scope of the embodiments of this specification. For example, although the system components described above can be implemented by hardware devices, they can also be implemented only through software solutions, such as installing the described system on an existing server or mobile device.

[0099] Similarly, it should be noted that, in order to simplify the presentation of the disclosure in this specification and thus help the understanding of one or more embodiments of the invention, in the foregoing description of the embodiments of this specification, sometimes multiple features are merged into one embodiment, drawing or description thereof. However, this disclosure method does not mean that the features required by the subject matter of this specification are more than those mentioned in the claims. In fact, the features of the embodiments are less than all the features of the individual embodiments disclosed above.

[0100] In some embodiments, numbers are used to describe components and the quantity of attributes. It should be understood that such numbers used in the description of embodiments are, in some examples, modified by the modifiers "about", "approximately", or "substantially". Unless otherwise stated, "about", "approximately", or "substantially" indicate that the stated number allows for a variation of ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may vary according to the characteristics required by individual embodiments. In some embodiments, numerical parameters should take into account the specified significant digits and adopt the method of retaining general digits. Although the numerical ranges and parameters used in some embodiments of this specification to confirm the breadth of their scope are approximate values, in specific embodiments, such numerical settings are as precise as possible within the feasible range.

[0101] For each patent, patent application, patent application publication, and other materials cited in this specification, such as articles, books, specifications, publications, documents, etc., their entire contents are hereby incorporated into this specification by reference. Except for the application history documents that are inconsistent with or conflict with the content of this specification, and also except for the documents that limit the broadest scope of the claims of this specification (currently or subsequently attached to this specification). It should be noted that if there are inconsistencies or conflicts between the descriptions, definitions, and / or uses of terms in the supplementary materials of this specification and the content described in this specification, the descriptions, definitions, and / or uses of terms in this specification shall prevail.

[0102] Finally, it should be understood that the embodiments described in this specification are only used to illustrate the principles of the embodiments of this specification. Other variations may also fall within the scope of this specification. Therefore, by way of example and not limitation, alternative configurations of the embodiments of this specification may be considered to be consistent with the teachings of this specification. Accordingly, the embodiments of this specification are not limited to the embodiments explicitly introduced and described in this specification.

Claims

1. A data processing method, characterized in that, The method includes: Obtaining freight rate data and at least one freight rate processing task; the freight rate data includes preprocessed ATPCO freight rate data; the freight rate processing task is constructed based on the joint task composition dimensions of airline, fare definition number, and freight rate restriction rule number; For each freight rate processing task: determining the combined freight rate related to the freight rate processing task based on the freight rate data; obtaining the freight rate restriction rule number for constructing the freight rate processing task; based on the freight rate restriction rule number, using a second pre-designed calculation rule to determine the target identifier corresponding to the freight rate restriction rule number; designating the target identifier as the index corresponding to the combined freight rate; Transmitting at least one combined freight rate and at least one index related to the at least one freight rate processing task to a local storage device; Obtaining freight rate retrieval data and determining a planned itinerary based on the freight rate retrieval data; Obtaining flight information and its related data adapted to the planned itinerary, and determining the calculated freight rate corresponding to the planned itinerary based on the flight information and its related data using a freight rate calculation rule; Determining the combined freight rate in the combined freight rate-index dataset composed of the combined freight rate and the index that matches the calculated freight rate, obtaining the index corresponding to the combined freight rate that matches the calculated freight rate, determining the freight rate restriction rule number corresponding to the index based on a third pre-designed calculation rule, using the freight rate restriction rule corresponding to the freight rate restriction rule number as the constraint for the calculated freight rate, and obtaining the determination of whether the calculated freight rate meets the display condition; wherein, the constraint corresponding to the calculated freight rate is used to determine whether the calculated freight rate meets the display condition; Performing the display or hiding operation of the calculated freight rate based on the determination; 2. The method according to claim 1, characterized in that The determining the combined freight rate related to the freight rate processing task based on the freight rate data includes: Obtaining relevant calculation data from the freight rate data based on the task composition dimension; Determining the combined freight rate related to the freight rate processing task using a first pre-designed calculation rule based on the relevant calculation data; wherein, the first pre-designed calculation rule includes the ATPCO calculation rule; 3. A data processing device, characterized in that, Includes: A first acquisition module for obtaining freight rate data and at least one freight rate processing task; the freight rate data includes preprocessed ATPCO freight rate data; the freight rate processing task is constructed based on the joint task composition dimensions of airline, fare definition number, and freight rate restriction rule number; A first processing module for, for each freight rate processing task, determining the combined freight rate related to the freight rate processing task based on the freight rate data; obtaining the freight rate restriction rule number for constructing the freight rate processing task; based on the freight rate restriction rule number, using a second pre-designed calculation rule to determine the target identifier corresponding to the freight rate restriction rule number; designating the target identifier as the index corresponding to the combined freight rate; A transmission module for transmitting at least one combined freight rate and at least one index related to the at least one freight rate processing task to a local storage device; A second acquisition module for obtaining freight rate retrieval data and determining a planned itinerary based on the freight rate retrieval data; A second determination module, configured to obtain flight information and its related data adapted to the planned itinerary, and determine a calculated fare corresponding to the planned itinerary by using a fare calculation rule based on the flight information and its related data; A third determination module, configured to determine a combined fare in a combined fare-index dataset formed by the combined fare and the index that matches the calculated fare, obtain an index corresponding to the combined fare that matches the calculated fare, determine a fare restriction rule number corresponding to the index based on a third preset calculation rule, use the fare restriction rule corresponding to the fare restriction rule number as a constraint for the calculated fare, and obtain a determination of whether the calculated fare meets a display condition; wherein, the constraint corresponding to the calculated fare is used to determine whether the calculated fare meets the display condition; An execution module, configured to execute a display or concealment operation of the calculated fare based on the determination.

4. A data processing system, characterized in that, Comprising: A memory, a processor, and a computer program stored on the memory and executable on the processor, wherein when the computer program is executed by the processor, the steps of the method according to any one of claims 1 to 2 are implemented.

5. A computer-readable storage medium, characterized in that, A computer program is stored on the storage medium, and when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 2 are implemented.

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