KR20230106963A - Device, method and computer program for converting ndc schema of airline data - Google Patents

Abstract

The present disclosure is directed to converting a new distribution capability (NDC) schema of aviation data. It relates to devices, methods and computer programs. In one embodiment, the conversion device receives a conversion request for converting the flight data of the source NDC schema and the source NDC schema from the first device to the target NDC schema, and transmits the converted target NDC schema to at least one of the first device and the second device. a communication module configured to transmit aviation data of an NDC schema; A first transformation module configured to, in response to a transformation request, transform aviation data of a source NDC schema into first tree-structured data; a second conversion module, configured to convert the first tree-structured data into second tree-structured data; and a third conversion module configured to convert the second tree structure data into flight data of the target NDC schema.

Description

Apparatus, method and computer program for converting NDC schema of aviation data {DEVICE, METHOD AND COMPUTER PROGRAM FOR CONVERTING NDC SCHEMA OF AIRLINE DATA}

The present disclosure is directed to converting a new distribution capability (NDC) schema of aviation data. It relates to devices, methods and computer programs. More specifically, the present disclosure utilizes a rule-based algorithm and/or a tree-to-tree translation function based on an artificial neural network model to enable communication between different NDC schemas. It relates to an apparatus, method, and computer program. .

Unless otherwise stated herein, the subject matter described in this section is not prior art to the claims in this application and is not to be considered prior art by reason of being described in this section.

New distribution capability (NDC), established as a standard by the International Air Transport Association (IATA) in 2015, is an XML/JSON-based standard protocol built for next-generation airline ticket reservations. The conventionally used global distribution system (GDS) has several technical limitations, such as the fact that the system is somewhat outdated, its scalability is low, and limited information expression in text format is possible. In addition, a small number of GDSs monopolized the entire airline distribution market, causing economic and industrial problems such as excessive reservation and ticketing fees.

If the aviation distribution structure is improved with the introduction of the new technology standard, NDC, social welfare will be increased, and customer satisfaction and additional revenue from travel agencies will be expected through the provision of various additional services and contents based on the expanded protocol. In addition, the cost structure can be improved by avoiding excessive GDS fees through direct transactions between travel agencies and airlines.

Thanks to these advantages, despite the situation where the demand for NDC introduction by airlines and travel agencies is increasing, the air service technology developed based on NDC is still insignificant, and the existing GDS-based air service technology is mostly the situation. For example, Prior Patent Document 1 (Korean Registered Patent No. 10-2007995) on "Airline ticket service method and device providing such air ticket service" and Prior Patent Document 2 (Korea Registered Patent Document) on "Heuristic Airline Inquiry System and Method for Providing It" Patent No. 10-1558324) is a service provided based on GDS, and it is difficult to apply it directly to NDC. This is because the introduction of NDC requires one-to-one interworking with individual airlines, unlike GDS.

KR 10-2007995 B1 KR 10-1558324 B1

The present disclosure is for converting the NDC schema of aviation data It relates to devices, methods and computer programs. Specifically, in the present invention, the cost and time required for service construction and maintenance are solved by solving the problem of airline individual interworking required for NDC introduction by enabling communication between different NDC schemas with a simple setting through a tree-to-tree translation function. can save

In one embodiment, a conversion device for converting an NDC schema of aviation data is described. The conversion device receives a conversion request for converting the aviation data of the source NDC schema and the source NDC schema from the first device to the target NDC schema, and the converted aviation data of the target NDC schema in at least one of the first device and the second device. It may include a communication module configured to transmit. The conversion device may include a first conversion module configured to convert aviation data of a source NDC schema into first tree structure data in response to a conversion request; a second conversion module, configured to convert the first tree-structured data into second tree-structured data; and a third conversion module configured to convert the second tree structure data into flight data of the target NDC schema.

In one example, the source NDC schema and the target NDC schema may be XML or JSON based data formats.

In one example, the conversion request may include a request to convert a source NDC schema of a first NDC version to a target NDC schema of a second NDC version. In another example, the conversion request may include a request for converting the source NDC schema into an NDC schema used in the second device.

In one example, the second transformation module may be based at least in part on a rule-based algorithm. In another example, the second transform module may be based at least in part on an artificial neural network model comprising a tree encoder and a tree decoder. Here, the tree encoder may encode the first tree structure data into a context vector. Also, the tree decoder may decode the context vector into second tree structure data.

In another embodiment, a conversion method for converting an NDC schema of flight data is described. The conversion method may receive, from the first device, a conversion request for converting aviation data of a source NDC schema and a source NDC schema into a target NDC schema. In addition, the conversion method may include converting aviation data of a source NDC schema into first tree structure data in response to a conversion request; converting the first tree structure data into second tree structure data; and converting the second tree structure data into aviation data of a target NDC schema. The conversion method may further include transmitting the converted aviation data of the target NDC schema to at least one of the first device and the second device.

In one example, the source NDC schema and the target NDC schema may be XML or JSON based data formats.

In one example, receiving the conversion request may include receiving a request to convert the source NDC schema of the first NDC version to the target NDC schema of the second NDC version. In another example, receiving the conversion request may include receiving a request for converting the source NDC schema into an NDC schema used in the second device.

In one example, converting the first tree-structured data to the second tree-structured data may be based at least in part on a rule-based algorithm. In another example, transforming the first tree-structured data into the second tree-structured data comprises encoding the first tree-structured data into a context vector based at least in part on an artificial neural network model comprising a tree encoder and a tree decoder. and decoding the context vector into second tree structure data.

In another embodiment, a computer program stored in a computer readable recording medium is described for converting an NDC schema of aviation data. The computer program, when executed, causes the computing device to receive, from the first device, a conversion request for converting aviation data of the source NDC schema and the source NDC schema into the target NDC schema; In response to the conversion request, converting aviation data of the source NDC schema into first tree structure data; converting the first tree-structured data into second tree-structured data; converting the second tree structure data into aviation data of a target NDC schema; and one or more computer executable instructions for executing an operation of transmitting the converted flight data of the target NDC schema to at least one of the first device and the second device.

In one example, receiving the conversion request may include receiving a request to convert the source NDC schema of the first NDC version to the target NDC schema of the second NDC version. In another example, receiving the conversion request may include receiving a request for converting the source NDC schema into an NDC schema used in the second device.

In one example, the operation of converting the first tree-structured data into the second tree-structured data may be based at least in part on a rule-based algorithm. In another example, converting the first tree-structured data into the second tree-structured data comprises encoding the first tree-structured data into a context vector based at least in part on an artificial neural network model comprising a tree encoder and a tree decoder. It may include an operation of decoding the operation and the context vector into the second tree structure data.

The above brief summary and description of effects are merely illustrative and are not intended to limit the technical details intended in the present disclosure. In addition to the foregoing exemplary embodiments and technical features, additional embodiments and technical features may be understood by referring to the following detailed description and accompanying drawings.

The features of the present disclosure described above and other additional features will be described in detail below with reference to the accompanying drawings. These drawings illustrate only a few embodiments according to the present disclosure and should not be considered as limiting the scope of the spirit of the present disclosure. The technical idea of the present disclosure will be described in more detail and detail using the accompanying drawings.
1 is a diagram schematically illustrating the function of an NDC aggregator.
2 is a block diagram illustrating a conversion apparatus for converting an NDC schema of aviation data, according to at least some embodiments of the present disclosure.
3 is a diagram illustrating a tree structure, in accordance with at least some embodiments of the present disclosure.
4 is a diagram illustrating conversion between tree-structured aerial data, in accordance with at least some embodiments of the present disclosure.
5 is a diagram illustrating an artificial neural network model of a second transformation module in more detail, according to at least some embodiments of the present disclosure.
6 is a flow diagram illustrating an example process for converting an NDC schema of aviation data, in accordance with at least some embodiments of the present disclosure.
7 illustrates an example computer program product that may be used to transform an NDC schema of air data, in accordance with at least some embodiments of the present disclosure.

Hereinafter, with reference to the accompanying drawings, embodiments and embodiments of the present disclosure will be described in detail so that those skilled in the art can easily practice them. However, this disclosure may be embodied in many different forms and is not limited to the embodiments and examples set forth herein.

This disclosure is generally for converting the NDC schema of aviation data Devices, methods and computer programs are presented. More specifically, the present disclosure uses a rule-based algorithm and/or an artificial neural network model including a tree encoder and a tree decoder to automatically and quickly transform a tree-structured XML or JSON-based source NDC schema into a tree structure of a target NDC schema. A device, method, and computer program capable of converting efficiently are described.

1 is a diagram schematically illustrating the function of an NDC aggregator. An NDC aggregator is also called an intermediate aggregator, and refers to a service that aggregates different NDC standards of each airline and provides them as one standard. In order to introduce NDC, one-to-one linkage between travel agencies and airlines is basically required. However, if there is no NDC aggregator as shown in FIG. 1 (a), each travel agency needs to work individually with hundreds of airlines due to the NDC customization of each airline. In addition, IATA releases several new NDC versions each year, and upgrades are required after a certain period of validity. On the other hand, if there is an NDC aggregator as shown in FIG. 1 (b), it is possible to reduce the cost and time for individual interworking with a plurality of airlines by enabling communication between different NDC schemas, and to upgrade the NDC version. maintenance costs can be minimized. In the present invention, in order to provide an NDC aggregator solution, a conversion device, a conversion method, and a computer program for converting the NDC schema of aviation data are implemented.

2 is a block diagram illustrating a conversion apparatus 200 for converting an NDC schema of aviation data, according to at least some embodiments of the present disclosure. The exemplary conversion device 200 may include a communication module 210, a first conversion module 220, a second conversion module 230, a third conversion module 240, and an NDC database (DB) 250. there is. In some examples, the conversion device 200 may be a stand-alone server, a web server, and any other computing device having a data transmission/reception function, a data identification function, and a data processing function, and two or more computing devices may be connected and used through a network. .

The communication module 210 may receive flight data of the source NDC schema and a conversion request for converting the source NDC schema into a target NDC schema from the first device. In addition, as will be described later, the communication module 210 passes through the first conversion module 220, the second conversion module 230, and the third conversion module 240 of the conversion device 200 according to the conversion request to source NDC. When aviation data of the schema is converted into aviation data of the target NDC schema, the converted aviation data of the target NDC schema may be transmitted to at least one of the first device and the second device.

The present invention is generally intended to provide an NDC aggregator solution, where the first device is an airline service provider device (eg, a travel agency device), the second device may be an airline device, and conversely, when the first device is an airline device The second device may be an air service provider device (eg, a travel agency device). Here, the air service provider device may refer to any entity that provides flight-related service technology on an NDC basis other than an airline device, such as a travel agency device. In some examples, the first device and the second device are a desktop computer, laptop computer, smartphone, tablet computer, cell phone, personal digital assistant (PDA), special purpose device, or convergence device that includes any of the functions small form factor portable (mobile) electronic devices such as, but are not limited to.

In one example, the source NDC schema and the target NDC schema may be XML or JSON based data formats. When XML or JSON-based data format is used as a protocol, it has higher scalability compared to the TTY/EDIFACT protocol, which is an interface method used in GDS, a traditional air distribution system. Accordingly, the NDC can provide not only simple schedules and fares, but also various additional service information such as in-flight meals, seat assignments, and baggage based on an extended protocol.

Aviation data of the source NDC schema may generally refer to all data related to aviation composed of NDC schemas that require conversion. For example, the flight data of the source NDC schema may include personal information of each air passenger, such as passport information and contact information, as well as data related to flight schedule or ticket inquiry, reservation, and ticketing. The aviation data of the target NDC schema is generally the aviation data of the NDC schema that is the conversion target. The NDC version of the aviation data of the source NDC schema is updated, or the aviation data in a form converted to be suitable for the NDC schema used in a specific device. can be referred to

In some examples, the NDC schema used by each air service provider device (eg, travel agency device) may be provided by the conversion device 200 (eg, the NDC aggregator device). In addition, the NDC schema used by each airline device may be a customized NDC version valid for each airline. In this regard, it will be described in more detail in the following embodiments.

In one embodiment, the conversion request may include a request to convert a source NDC schema of a first NDC version to a target NDC schema of a second NDC version. There may be a plurality of NDC versions (eg, NDC 17.2, 18.1, 18.2, 19.1, 19.2, 20.1, 20.2, 21.1, etc.) that can be certified by IATA. Since IATA releases one or more new versions each year and is valid for a certain period after release, each air service provider device or airline device needs to upgrade the NDC version of the source NDC schema in use. In addition, for service use and provision, the NDC version used by each air service provider device is converted to the NDC version used by a specific airline device, or conversely, the NDC version used by a specific airline device is converted to each air service provider device. You need to convert to the NDC version. Accordingly, a request for converting the source NDC schema of the first NDC version to the target NDC schema of the second NDC version may include converting the converted flight data of the target NDC schema into an NDC version for actual use in the receiving device. can

In another embodiment, the conversion request may include a request for converting the source NDC schema into an NDC schema used in the second device. Since the NDC can be partially customized for each airline, each air service provider device may require maintenance even after interworking of the NDC version for communication between the target airline device and the NDC schema. That is, in order to use and provide services, the NDC schema used by each air service provider device is converted into the NDC schema used by a specific airline device, or conversely, the NDC schema used by a specific airline device is converted to each air service provider device. You need to convert to NDC schema. Accordingly, the request for converting the source NDC schema to the NDC schema used in the second device may include converting to an NDC schema customized in a specific NDC version and actually used in the second device.

In order to convert aviation data of a source NDC schema into aviation data of a target NDC schema, the conversion device 200 may undergo three conversion processes including three conversion modules 220 , 230 , and 240 . First, the first conversion module 220 may convert aviation data of a source NDC schema into first tree structure data in response to a conversion request. Here, the first tree-structured data is tree-structured aviation data of the source NDC schema. In one example, the first conversion module 220 may be implemented using various algorithms, and at least some of them may be developed using open sources.

Next, the second conversion module 230 may convert the first tree structure data into second tree structure data different from the first tree structure data. Here, the second tree-structured data is tree-structured aviation data of the target NDC schema. Conversion between the tree structure and the tree structure data in the second conversion module 230 will be described in more detail below with reference to FIGS. 3 to 5 .

Finally, the third conversion module 240 may convert the second tree structure data into aviation data of a target NDC schema. In one example, the third conversion module 240 may be implemented using various algorithms, and at least some of them may be developed using open sources.

The conversion device 200 stores the NDC schema of each NDC version, the NDC schema provided by the conversion device 200, and/or the NDC version actually used by each air service provider device or airline device and its customized form. It may include the configured NDC database 250. The NDC schema received from IATA, the conversion device 200 and/or each airline device and stored in the NDC database 250 may be updated and stored upon request or periodically/real-time. Accordingly, the conversion device 200 can quickly and efficiently process a conversion process of converting an NDC schema stored in the NDC database 250 into a target NDC schema.

3 is a diagram illustrating a tree structure, in accordance with at least some embodiments of the present disclosure. In general, a tree structure may include one or more nodes (eg, N1-N11) and edges connecting nodes to nodes. The top node N1 of the tree is referred to as the root node. Among the nodes directly connected to the edge, the upper node is called the parent node, and the lower node is called the child node. For example, node N2 becomes the parent node of nodes N4-N6, and nodes N7-N8 become node N3 becomes a child node of If a node has no child nodes, i.e. if its degree is 0, it is called a leaf node. In the tree of Fig. 3, the leaf nodes are N4, N6, N7, N9, N10 and N11. Assuming that the level of the root node is 0 (L0), the level increases by 1 each time you go down one layer. For example, nodes N2 and N3 are level 1 (L1), nodes N4-N8 are level 2 (L2), and nodes N9-N11 are level 3.

If you understand the basic tree structure, you can represent aviation data in a tree-structured NDC schema. As an example, FIG. 4 is a diagram illustrating conversion between tree-structured aerial data, in accordance with at least some embodiments of the present disclosure. Figure 4 (a) illustrates part of the tree structure data of NDC version 18.1, Figure 4 (b) illustrates part of the tree structure data of NDC version 21.1.

Referring to FIG. 4(a), tree structure data of NDC version 18.1 may include an OrderItem node as a parent node and two child nodes Passport and Passenger. The Passport node again has Nation, City, and No as child nodes, and each node may have a corresponding instance value. The Passenger node again has Email, City, ID, and Phone as child nodes, and each node can have a corresponding instance value. Here, the tree structure is not limited to a binary tree and may include three or more subtrees.

Referring to FIG. 4(b), tree structure data of NDC version 21.1 may include an OrderOfferItem node as a parent node and two child nodes Passenger and DeliveryTo. The Passenger node again has Contact and Info as child nodes, and each node can again have multiple child nodes and corresponding instance values. Also, the DeliveryTo node may have a plurality of child nodes (Street, City, Postal) and corresponding instance values. Here, the tree structure is not limited to a binary tree and may include three or more subtrees.

It should be noted that although the tree structure data of NDC version 18.1 in FIG. 4(a) and the tree structure data of NDC version 21.1 in FIG. that it is different. For example, the OrderItem node of FIG. 4(a) and the OrderOfferItem node of FIG. 4(b) may be matched because names and data are similar, but the detailed tree structures and instance values are different. Even in the case of contact information of the same passenger, in FIG. In b), in the tree structure of [OrderOfferItem node]-[Passenger node]-[Contact node], it is divided into [Prefix node], [AreaNo node], and [LocalNo node], respectively +1, 240, 361-xxxx as instance values. are leaving

For conversion between tree-structured data using the Tree-to-Tree translation function, matching between nodes representing similar data and conversion between tree-structured NDC schema instance values must be performed smoothly. Since the tree-structured NDC schema does not deviate from the format defined in the tree structure, conversion between NDC schemas is not only efficient, but also has excellent performance. It is the function of the second conversion module 230 included in the conversion device 200 to enable such conversion between tree-structured data.

In one example, the second transformation module 230 may be based at least in part on a rules-based algorithm. In the case of using the rule-based algorithm, matching must be performed between similar nodes, for example, nodes whose names are at least partially overlapping. In addition, for example, based on several rules, the instance value of the source NDC schema (eg, NDC version 18.1 in FIG. It must be able to convert to an instance value of the type.

In another example, the second transformation module 230 may be based at least in part on an artificial neural network model. In this regard, FIG. 5 is a diagram illustrating an artificial neural network model of the second transformation module 230 in more detail, according to at least some embodiments of the present disclosure. The artificial neural network-based second transformation module 230 may be implemented in various ways according to the design of a deep learning architecture, and at least a part thereof may be developed using a deep learning framework published as an open source. In addition, the artificial neural network-based second transformation module 230 may be trained by applying a deep learning technique. For example, the artificial neural network-based second transformation module 230 may be trained using one tree-structured data and a set of tree-structured data corresponding to different tree-structures.

The artificial neural network-based second transformation module 230 may include a tree encoder 510 and a tree decoder 520. The tree encoder 510 may encode the first tree structure data into a context vector. Also, the tree decoder 520 may decode the context vector into second tree structure data. Specifically, as shown in FIG. 5 , the tree encoder 510 may generate a context vector (eg, [x ₀ , x ₁ , ..., x _n ]) from the input. Here, the input may be aviation data (ie, first tree-structured data) of a tree-structured source NDC schema. The tree decoder 520 may output tree-structured aerial data (ie, second tree-structured data) of the target NDC schema based on the context vector.

5 schematically illustrates that the artificial neural network-based second transformation module 230 includes a tree encoder 510 and a tree decoder 520, but in addition, for example, a tree encoder 510 and / or a tree decoder ( 520) To implement the artificial neural network-based second transformation module 230, such as an embedding layer (not shown) or a plurality of long short term memory (LSTM) units (not shown) that can be placed in each input unit Essential components may be further included.

As described above, the artificial neural network-based second transformation module 230 according to the present disclosure is more efficient than the case of manually checking correspondence between tree structures or using a rule-based algorithm when learning data is accumulated and model performance is improved. , and errors can be significantly reduced.

In addition, the second transformation module 230 may use a rule-based algorithm or a tree-to-tree artificial neural network model alone, or may appropriately combine the two methods and use the most efficient method.

In FIGS. 1 to 5, an example of using a conversion applied with a Tree-to-Tree translation function between an NDC schema of an airline device and an NDC schema of an airline service provider device (eg, a travel agency device) from the viewpoint of an NDC aggregator solution has been mainly described. , Of course, the conversion device 200 according to the present invention can be used in all situations in which two entities providing aviation-related service descriptions based on NDC use different NDC schemas.

6 is a flow diagram illustrating an example process 600 for converting an NDC schema of aviation data, in accordance with at least some embodiments of the present disclosure. For example, process 600 may be performed under the control of a computing device, such as conversion device 200 of FIG. 2 . Process 600 illustrated in FIG. 6 may include one or more actions, functions or actions as illustrated by blocks 610 , 620 , 630 , 640 and/or 650 .

The various blocks are not intended to be limited to the described embodiments. For example, those skilled in the art will recognize, given the subject processes disclosed herein, that the functions performed in the processes and methods may be implemented in a different order. Meanwhile, the schematic operations illustrated in FIG. 6 are provided only as examples, and some of the operations may be optional, combined with fewer operations, or extended with additional operations without departing from the essence of the disclosed embodiment. can

Process 600 may begin at block S610 with receiving air data of the source NDC schema and a conversion request. In block S610, the computing device may receive aviation data of the source NDC schema and a conversion request for converting the source NDC schema into the target NDC schema from the first device. Here, the source NDC schema and the target NDC schema may be XML or JSON-based data formats. In one example, a computing device may receive a request to convert a source NDC schema of a first NDC version to a target NDC schema of a second NDC version. In another example, the computing device may receive a request to convert the source NDC schema to the NDC schema used in the second device.

Process 600 may continue from block S610 to block S620 of converting aviation data in the source NDC schema into first tree structured data. In block S620, the computing device may convert aviation data of the source NDC schema into first tree structure data in response to the conversion request received from the first device.

Process 600 may continue from block S620 to block S630 in which the first tree structure data is converted to second tree structure data. In block S630, the computing device may convert the first tree structure data into second tree structure data different from the first tree structure data. In one example, the computing device may convert the first tree-structured data to the second tree-structured data based at least in part on a rules-based algorithm. In another example, a computing device may encode a first tree structure data into a context vector and decode the context vector into a second tree structure data based at least in part on an artificial neural network model that includes a tree encoder and a tree decoder. . In another example, the computing device may convert the first tree-structured data into the second tree-structured data by appropriately combining a rule-based algorithm and an artificial neural network model.

Process 600 may continue from block S630 to block S640 of converting the second tree structure data into aviation data of the target NDC schema. In block S640, the computing device may convert the second tree structure data into aviation data of the target NDC schema. In one example, the target NDC schema may be a different NDC version than the source NDC schema. In another example, the target NDC schema may be an NDC schema used in the second device.

Process 600 may continue from block S640 to block S650 of transmitting air data of the converted target NDC schema. In block S650, the computing device may transmit the converted aviation data of the target NDC schema to at least one of the first device and the second device as needed. For example, the computing device transmits aviation data of the converted target NDC schema to a first device that has requested an upgrade of the NDC version, or transmits aviation data of the converted target NDC schema directly to a second device with which the first device wishes to communicate to provide aviation services. Aviation data can be transmitted.

As such, according to the present invention, by using rule-based algorithms and artificial neural network models individually or in combination, automatic conversion between tree-structured XML or JSON-based NDC schemas is possible, enabling fast and efficient interworking and customization necessary for NDC introduction. , updates, etc.

7 depicts an example computer program product 700 that may be used to transform an NDC schema of air data, in accordance with at least some embodiments of the present disclosure. Example computer program product 700 is provided using, for example, a signal bearing medium 702 . In some embodiments, signal bearing medium 702 of one or more computer program products 700 may include computer readable medium 706 , recordable medium 708 and/or communication medium 710 .

Instructions 704 included in signal bearing medium 702 may be executed by a computing device, such as, for example, conversion device 200 illustrated in FIG. 1 . When executed, the instructions 704 may cause the computing device to perform a process for converting the NDC schema of aviation data.

The command 704 may include at least one command for receiving a conversion request for converting aviation data of the source NDC schema and the source NDC schema into the target NDC schema from the first device. The command 704 may include at least one command for converting aviation data of a source NDC schema into first tree structure data in response to a conversion request; at least one instruction for converting the first tree-structured data into second tree-structured data; and at least one command for converting the second tree structure data into aviation data of a target NDC schema. Instructions 704 may include at least one instruction for transmitting the converted aviation data of the target NDC schema to at least one of the first device and the second device. Here, the source NDC schema and the target NDC schema may be XML or JSON-based data formats.

In one example, the at least one instruction for receiving a conversion request may include at least one instruction for receiving a request to convert a source NDC schema of a first NDC version to a target NDC schema of a second NDC version. In another example, the at least one command for receiving the conversion request may include at least one command for receiving a request for converting the source NDC schema into the NDC schema used in the second device.

In one example, the at least one instruction to transform the first tree structure data into the second tree structure data may be based at least in part on a rule based algorithm. In another example, the at least one instruction for transforming the first tree-structured data into the second tree-structured data is based at least in part on an artificial neural network model comprising a tree encoder and a tree decoder to convert the first tree-structured data into a context vector. It may include at least one instruction for encoding and at least one instruction for decoding the context vector into the second tree structure data.

The above description of the present application is for illustrative purposes, and those skilled in the art will understand that it can be easily modified into other specific forms without changing the technical spirit or essential features of the present application. Therefore, it should be understood that the embodiments described above are illustrative in all respects and not restrictive. For example, each component described as a single type may be implemented in a distributed manner, and similarly, components described as distributed may also be implemented in a combined form.

In the above, the object to be claimed in the present disclosure has been specifically examined. The subject matter claimed in this disclosure is not limited in scope to the specific implementations described above. For example, in some implementations it may be in the form of hardware operatively used on a device or combination of devices, in other implementations it may be implemented in the form of software and/or firmware, and in still other implementations it may be in the form of a signal bearing medium; It may include one or more items, such as storage media. Here, the storage medium, such as a CD-ROM, a computer disk, a flash memory, etc., when executed by a computing device, such as a computing system, a computing platform, or other system, may cause the corresponding processor to execute according to the implementation described above. can be saved. Such computing devices may include one or more processing units or processors, a display, one or more input/output devices such as a keyboard and/or mouse, and one or more memories such as static random access memory, dynamic random access memory, flash memory and/or hard drives. can include

On the other hand, whether to implement the system as hardware or software is generally a design choice that represents a cost-effectiveness trade-off. In this disclosure, there are various means (eg, hardware, software, and/or firmware) that can be influenced by processes, systems, and other technologies, with preferred means being used by processes and/or systems and/or other technologies. will change depending on the context. For example, if the implementer determines that speed and correctness are most important, the implementer may choose a primarily hardware and/or firmware means; if flexibility is most important, the implementer may choose a primarily software implementation; Or, alternatively, implementers may choose any combination of hardware, software and/or firmware.

In the foregoing detailed description, various embodiments of devices and/or processes have been described using block diagrams, flow diagrams, and/or other examples. Such block diagrams, flow diagrams, and/or other examples may include one or more functions and/or operations, and each function and/or operation in a block diagram, flow diagram, and/or other example may be hardware, software, firmware, or or any combination thereof, individually or collectively. In one embodiment, some portions of the subject matter described in this disclosure may be implemented via application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), digital signal processors (DSPs), or other forms of integration. In contrast, some aspects of embodiments of the present disclosure are directed to one or more computer programs running on one or more computers (eg, one or more programs running on one or more computer systems), one or more programs running on one or more processors (eg, one or more programs running on one or more computer systems). for example, one or more programs running on one or more microprocessors), firmware, or substantially any combination thereof, which may be implemented in whole or in part equivalently on an integrated circuit, writing code for software and/or firmware. and/or design of the circuit is within the skill of those skilled in the art in light of this disclosure. Further, those skilled in the art will understand that the mechanisms of the present disclosure may be distributed in various forms of program product, and the examples of the present disclosure apply regardless of the specific type of signal bearing medium used to actually perform the distribution. will understand

While certain exemplary techniques have been described and illustrated herein using a variety of methods and systems, those skilled in the art will appreciate the possibility of various other modifications or equivalent substitutions without departing from the claimed subject matter. Additionally, many modifications may be made to adapt a particular situation to the teachings of claimed subject matter without departing from the central concept described herein. Thus, it is intended that the claimed subject matter is not limited to the specific examples disclosed, but that such claimed subject matter may also include all implementations falling within the scope of the appended claims and their equivalents.

Throughout the present disclosure, when a part is said to be "connected" to another part, this includes not only the case of being "directly connected" but also the case of being "electrically connected" with another element in between. do. In addition, throughout the present disclosure, when a member is said to be located “on” another member, this includes not only a case in which a member is in contact with another member, but also a case where another member exists between the two members. Furthermore, throughout the present disclosure, when a part “includes” a certain component, it means that it may further include other components without excluding other components unless otherwise stated. As used in this disclosure, the terms "about," "substantially," and the like are used at or approximating that number when manufacturing and material tolerances inherent in the stated meaning are given, and are intended to assist in the understanding of this disclosure. Accurate or absolute figures are used to prevent undue exploitation by unscrupulous infringers of the stated disclosure.

The scope of the present disclosure is indicated by the following claims rather than the foregoing detailed description, and all changes or modifications derived from the meaning and scope of the claims and equivalent concepts thereof are construed as being included in the scope of the present application. It should be.

Claims (15)

A conversion device for converting a new distribution capability (NDC) schema of aviation data,
Aviation data of a source NDC schema and a conversion request for converting the source NDC schema into a target NDC schema are received from the first device, and the aviation data of the target NDC schema converted in at least one of the first device and the second device a communication module configured to transmit;
In response to the conversion request, a first conversion module configured to convert aviation data of the source NDC schema into first tree-structured data;
a second conversion module configured to convert the first tree-structured data into second tree-structured data; and
A third conversion module configured to convert the second tree structure data into aviation data of the target NDC schema.
Conversion device comprising a. According to claim 1,
The source NDC schema and the target NDC schema are XML or JSON-based data formats, conversion device. According to claim 1,
The conversion request includes a request for converting a source NDC schema of a first NDC version into a target NDC schema of a second NDC version. According to claim 1,
The conversion request includes a request for converting the source NDC schema into an NDC schema used in the second device. According to claim 1,
wherein the second transformation module is based at least in part on a rule-based algorithm. According to claim 1,
the second transform module is based at least in part on an artificial neural network model comprising a tree encoder and a tree decoder;
The tree encoder encodes the first tree structure data into a context vector,
Wherein the tree decoder decodes the context vector into the second tree structure data. As a conversion method for converting the NDC schema of aviation data,
Receiving aviation data of a source NDC schema and a conversion request for converting the source NDC schema into a target NDC schema from a first device;
In response to the conversion request, converting aviation data of the source NDC schema into first tree structure data;
converting the first tree structure data into second tree structure data;
converting the second tree structure data into aviation data of the target NDC schema; and
Transmitting converted aviation data of the target NDC schema to at least one of the first device and the second device.
Conversion method including. According to claim 7,
The source NDC schema and the target NDC schema are XML or JSON-based data formats, conversion method. According to claim 7,
Receiving the conversion request comprises receiving a request for converting a source NDC schema of a first NDC version to a target NDC schema of a second NDC version. According to claim 7,
Receiving the conversion request comprises receiving a request for converting the source NDC schema into an NDC schema used in a second device. According to claim 7,
wherein the converting of the first tree-structured data to the second tree-structured data is based at least in part on a rules-based algorithm. According to claim 7,
Converting the first tree structure data into the second tree structure data,
Based at least in part on an artificial neural network model comprising a tree encoder and a tree decoder,
encoding the first tree structure data into a context vector; and
And decoding the context vector into the second tree structure data. A computer program stored on a computer-readable recording medium to convert the NDC schema of aviation data, which, when executed, causes a computing device to:
Receiving flight data of a source NDC schema and a conversion request for converting the source NDC schema into a target NDC schema from the first device;
converting aviation data of the source NDC schema into first tree structure data in response to the conversion request;
converting the first tree-structured data into second tree-structured data;
converting the second tree structure data into aviation data of the target NDC schema; and
Transmitting converted aviation data of the target NDC schema to at least one of the first device and the second device.
A computer program stored on a computer-readable recording medium, including one or more computer-executable instructions for enabling execution. According to claim 13,
The computer program stored on a computer readable recording medium, wherein the converting of the first tree-structured data into the second tree-structured data is based at least in part on a rule-based algorithm. According to claim 13
The operation of converting the first tree structure data into the second tree structure data,
Based at least in part on an artificial neural network model comprising a tree encoder and a tree decoder,
encoding the first tree structure data into a context vector; and
A computer program stored in a computer readable recording medium comprising an operation of decoding the context vector into the second tree structure data.

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