Seat recommendation method and device

Abstract

To provide a seat recommendation method and device for recommending group seats for a plurality of people based on representative NR information, and also to provide a seat recommendation method and device for determining a group type and recommending a group seat suitable for the group type. A seat recommendation method for a seat recommendation device connected to a computer network includes a step of determining a group type based on NR (Name Record) information of a representative, the NR information including information on the representative and accompanying persons; The method includes the steps of: deriving all group seats that can currently be recommended using group seat pattern information and seat information; calculating a recommendation value corresponding to the group type for each of the derived group seats; and recommending a predetermined number of group seats to a representative based on the calculated result value, wherein the group seat pattern information includes shape information of the group seats, and the seat information includes seat map information of all seats and information on currently occupied seats.

Description

[Technical field]

[0001] The present invention relates to a method and device for recommending seats, and more particularly to a method and device for recommending seats for a group of multiple people based on name record (NR) information of a representative. [Background technology]

[0002] Currently, many people can purchase tickets with reserved seats for real world such as airplanes, theaters, concert halls, sports stadiums, trains, and virtual world such as the metaverse via the Internet. In this case, seats must be reserved at the same time as or after purchasing the ticket. The seat reservation can have different prices depending on the location. For example, airlines currently have four major seating classes: First, Business / Prestige, Premium Economy, and Economy. Airlines operate aircraft seating systems with a mix of two or three classes, or only Economy class (especially in the case of low-cost airlines), depending on the circumstances of the route and aircraft they operate.

[0003] Recently, with the advent of the low-cost airline business model on the market, passengers have been able to travel by air at a low cost, but they are also coming to realize that there are many inconveniences involved in flying for several hours, and there is now a demand for more comfortable seats, even if it means paying a fee when reserving seats in advance. After an airline ticket is issued, a user can purchase or reserve a seat on a desired flight via the Internet. Current seat reservation systems simply distinguish between unselected and selected seats and display them to the user, allowing the user to purchase or reserve a seat that is not currently selected. In such seat reservation systems, if there are fellow passengers, the user must purchase or reserve a seat while taking into consideration the seats of the fellow passengers. In particular, depending on the seat reservation situation, fellow passengers may not be able to sit next to each other, but may have to sit far apart, which is inconvenient in many cases. Therefore, there is a need for research into technology that can automatically recommend preferred seats taking into account a user's gender, age, number of passengers, etc. Summary of the Invention [Problem to be solved by the invention]

[0004] An object of the present invention is to provide a seat recommendation method and device for recommending group seats for multiple people based on representative NR information. Another object of the present invention is to provide a seat recommendation method and device capable of determining a group type based on NR information and recommending a group seat suitable for the group type. Another object of the present invention is to provide a seat recommendation method and device for deriving all group seats that can currently be recommended according to a group type, calculating recommendation values ​​for the derived group seats, and recommending the group seats. Furthermore, the present invention provides a seat recommendation method and device that adjusts variable values ​​used in calculating recommendation values ​​through analysis of recommended group seat information based on recommendation values ​​and group seat information selected (or not selected) by a representative. [Means for solving the problem]

[0005] In order to achieve the above object, according to the present invention, a seat recommendation method for a seat recommendation device connected to a computer network is disclosed, which includes a step of determining a group type based on NR (Name record) information of a representative, the NR information including the representative and accompanying person information, a step of deriving all group seats that can currently be recommended using group seat pattern information and seat information, a step of calculating a recommendation value corresponding to the group type for each of the derived group seats, and a step of recommending a predetermined number of group seats to the representative based on the calculated result value.

[0006] Also disclosed is a seat recommendation device connected to a computer network, the seat recommendation device including: a group type determination unit that determines a group type based on a representative's NR (Name record) information, the NR information including the representative and accompanying person information; a group pattern database in which group seat pattern information is stored; a recommendable seat derivation unit that derives all group seats that can currently be recommended using the group seat pattern information and seat information; a recommendation value calculation unit that calculates a recommendation value for each of the derived group seats; a group seat recommendation unit that recommends a predetermined number of group seats based on the calculated result values; and a control unit that controls the receiving unit, the group type determination unit, the group pattern database, the air seat database, the recommendable seat derivation unit, the recommendation value calculation unit, and the group seat recommendation unit.

[0007] Also disclosed is a seat recommendation method for a seat recommendation device connected to a computer network, the method including the steps of: deriving all group seats that can currently be recommended to correspond to a group type based on NR information of a representative, the NR information including the representative and accompanying person information; calculating a recommendation value for each of all derived group seats using position values ​​and pattern values ​​for the derived group seats; recommending a predetermined number of group seats based on the calculated result values; receiving group seat information selected by a representative; comparing the group seat information selected by the representative with the recommended group seat information; and adjusting at least one of the position value and the pattern value based on the comparison result.

[0008] Also disclosed is a seat recommendation device connected to a computer network, the seat recommendation device including: a recommendable seat derivation unit that derives all group seats that can currently be recommended to correspond to a group type based on NR information of a representative, the NR information including the representative and accompanying person information; a recommendation value calculation unit that calculates a recommendation value for each of all derived group seats using a position value and a pattern value for the derived group seats; a group seat recommendation unit that recommends a predetermined number of group seats based on the calculated result values; a receiving unit that receives group seat information selected by the representative; a gap analysis unit that compares the group seat information selected by the representative with the recommended group seat information and adjusts at least one of the position value and the pattern value based on the comparison result; and a control unit that controls the recommendable seat derivation unit, the recommendation value calculation unit, the receiving unit, and the gap analysis unit. Effect of the Invention

[0009] According to the seat recommendation method and device of the present invention, it is possible to determine the passenger type of a group based on the representative's NR information and recommend a group seat suitable for the passenger type. In addition, by deriving all group seats that can currently be recommended according to the group type and calculating recommendation values ​​for the derived group seats to recommend the group seats, it is possible to improve the convenience of seat selection for customers. Furthermore, by adjusting the variable values ​​used in calculating the recommendation value through analysis of the group sheet information recommended based on the recommendation value and the group sheet information selected by the representative, it is possible to recommend a group sheet that reflects the needs of the customer. [Brief description of the drawings]

[0010] [Figure 1] 1 is a block diagram showing a seat recommendation system according to an embodiment of the present invention. [Diagram 2] FIG. 2 is a block diagram of the seat recommendation device shown in FIG. [Diagram 3] 4 is a flowchart illustrating a seat recommendation method according to an embodiment of the present invention. [Figure 4] FIG. 2 is a diagram for explaining a group passenger type according to an embodiment of the present invention. [Diagram 5] FIG. 1 is a diagram for explaining an example of determining passenger types based on PNR information according to one embodiment of the present invention. [Figure 6] 11 is a diagram illustrating a method for calculating a recommendation value and determining a recommendation order according to an embodiment of the present invention; [Figure 7] 13 is a diagram illustrating a group seat selection process for a representative reservation in a recommendation value calculation for a group seat according to an embodiment of the present invention. FIG. [Figure 8] FIG. 11 is a diagram comparing recommendation values ​​according to a group seat recommendation model and actual seat reservation purchase data according to an embodiment of the present invention. [Figure 9]FIG. 11 is a diagram comparing recommendation values ​​according to a group seat recommendation model and actual seat reservation purchase data according to an embodiment of the present invention. [Figure 10] 11 is a diagram illustrating a method for calculating recommendation values ​​and determining recommendation rankings for seats in a performance hall such as a theater according to an embodiment of the present invention. [Figure 11] FIG. 13 is a diagram showing a group sheet pattern according to an embodiment of the present invention. [Figure 12] 11 is a diagram illustrating a process for selecting a group seat for a representative reservation in a performance venue such as a play according to an embodiment of the present invention. [Figure 13] 11 is a diagram illustrating a group seat selection process for a representative reservation in a sports stadium seating according to an embodiment of the present invention. FIG. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] The seat recommendation method and device of the present invention will be described below with reference to the drawings. As used herein, singular expressions include plural expressions unless the context clearly indicates otherwise. In this specification, terms such as "comprise" or "include" should not be interpreted as including all of the multiple components or multiple steps described in the specification, and should be interpreted as including some components or some steps not included, or including additional components or steps. The seat recommendation method and apparatus of the present invention can be applied to seat recommendation in performance venues such as theaters where seat reservation is required, airplanes, sports stadiums, trains, etc. In addition, the seat recommendation method and device of the present invention can be applied not only to seat recommendation in the real world, but also to seat recommendation in a virtual world such as the Metaverse, where each seat has a different location and requires seat assignment.

[0012] In this specification, the representative refers to the representative of a group and may include the representative booker of tickets for a performance venue such as a theater, an airplane, a sports stadium, a train, etc., a representative participant in a virtual world, etc. In this specification, the representative's name record (NR) information may include the representative and accompanying person information in the case of ticket reservations or participation in a specific game, etc. For example, the name record (NR) information may include an airline ticket PNR (Passenger name record). In this specification, the term "accompanying person" refers to a member who forms a group together with the representative when recommending a group seat, and may include fellow passengers, accompanying visitors, accompanying participants, etc. In the present specification, the group type may refer to a group type determined based on name record (NR) information. The group type may include a group passenger type, a group participant type, a group spectator type, etc. In the following embodiment, airplane seat recommendation will be described as an example of seat recommendation of the present invention, but the present invention is not limited thereto.

[0013] FIG. 1 is a block diagram showing an airplane seat recommendation system of the present invention. As shown, the airplane seat recommendation system may include a user terminal 100, a seat recommendation device 200, a travel agency server 300, and an airline server 350. Here, the user may include a primary reservation person in a PNR (Passenger name record). Below, an example will be described in which the seat recommendation device 200 is connected to a travel agency server 300 or an airline server 350 to recommend seats. However, if the seat recommendation device 200 is an entity that provides seats, it can recommend seats even if it is not connected to the travel agency server 300 or the airline server 350. The user terminal 100, the seat recommendation device 200, the travel agency server 300, and the airline server 350 may be connected to each other via a computer network.

[0014] The user can directly access the airplane seat advance purchase or reservation page via the user terminal 100, or can access the airplane seat advance purchase or reservation page via the travel agency server 300 or the airline server 350. In addition, when an airline ticket is purchased through a travel agency or an airline, the seat recommendation device 200 can receive airline ticket reservation information from the travel agency server 300 or the airline server 350. An example of the airline ticket reservation information is PNR (Passenger name record). PNR (Passenger name record) information is information related to an airline ticket reservation, and can include passenger names, fellow passenger names, passenger passport information, departure information, return information, etc.

[0015] Below, a PNR (Passenger name record) will be described as an example of airline ticket reservation information. The seat recommendation device 200 can determine a group passenger type based on PNR information, and derive all currently available group seats corresponding to the determined passenger type. The seat recommendation device 200 can then calculate a recommendation value for each derivable group seat and determine a ranking. Then, the seat recommendation device 200 can recommend a predetermined number of group seats to the main reservation user based on the ranking result. FIG. 2 is a block diagram of the seat recommendation device shown in FIG. As shown, the seat recommendation device 200 may include a receiving unit 210, a passenger type determination unit 215, a group pattern database (DB) 220, a recommendable seat derivation unit 225, an air seat database (DB) 230, a recommendation value calculation unit 235, a group seat recommendation unit 240, a seat assignment unit 245, a gap analysis unit 250, and a control unit 260.

[0016] The seat recommendation device 200 may be hardware such as a microprocessor, an electronic circuit, software such as a program, or firmware executed by the hardware. The seat recommendation device 200 may be implemented by a combination of hardware and software. The receiving unit 210 can receive a PNR of a user (e.g., a representative reservation person) from the travel agency server 300 or the airline server 350. Through the PNR, the passenger's name, fellow passenger's name, passenger passport information, departure information, return information, etc. can be confirmed. In addition, the receiving unit 210 can receive purchase statistics data by seat. Meanwhile, the PNR information can be received, but can also be generated by the seat recommendation device 200 itself.

[0017] The receiving unit 210 can receive the group seat information selected by the representative reservation. The passenger type determination unit 215 may determine a group passenger type based on the PNR information. The passenger type determination unit 215 is an example of a group type determination unit that determines a group type. Group seat pattern information is stored in the group pattern database (DB) 220. The group seat pattern information may include shape information of the group seats. The shape of the group seats may be a square type, an L-shape, an I-shape, and the like. Seat information may be stored in the air seat database (DB) 230. The seat information may include seat map information of the entire airplane and currently occupied seat information. The recommendable sheet deriving unit 225 can derive all group sheets that can currently be recommended using the group sheet pattern information and the sheet information. The recommendation value calculation unit 235 may calculate a recommendation value for each of the derived group seats. The recommendation value may be calculated using a position value and a pattern value of each seat included in the group seat. A method of calculating the recommendation value will be described later.

[0018] The group sheet recommendation unit 240 can recommend a predetermined number of group seats to the representative reservation user based on the calculated recommendation value. The seat assignment unit 245 can assign a group seat for the PNR based on the group seat information selected by the representative reservation user. The gap analysis unit 250 may compare the group seat information selected by the representative reservation user with the recommended group seat information, and adjust at least one of the position value and the pattern value based on the comparison result. The control unit 260 can generally control the receiving unit 210, the passenger type determination unit 215, the group pattern database (DB) 220, the recommendable seat derivation unit 225, the air seat database (DB) 230, the recommendation value calculation unit 235, the group seat recommendation unit 240, the seat assignment unit 245, and the gap analysis unit 250.

[0019] FIG. 3 is a flow chart illustrating an airplane seat recommendation method according to an embodiment of the present invention. The receiving unit 210 can receive the PNR information of the representative reservation holder from the travel agency server 300 or the airline server 350 (S310). The passenger type determination unit 215 can determine the passenger type of the group based on the PNR information (S320). FIG. 4 is a diagram for explaining passenger types according to the present invention. As shown in the figure, passenger types can be classified into a care type, a couple type, a community type, etc. In the example shown in the figure, passenger types are classified into three types, but passenger types may be classified into more or fewer types. Passenger type can be one of several passenger types if it meets predefined conditions. For example, if there is a physically vulnerable person in the PNR of the main reservation person (Carer), it can be classified as a care type. For example, passengers such as infants (2 years old and under), children (5 years old and under), and elderly people (65 years old and over) can be classified as physically vulnerable.

[0020] For example, if the PNR contains an even number of adults (2, 4, 6, or 8), an equal number of men and women, and the age difference between the men and women is 10 years or less, it can be classified as a Couple Type. That is, group passenger types can be categorized into one or more group passenger types based on the number of passengers, gender, age, number of members, etc. For example, group passenger types can be categorized from 1 person type to 9 person type based on the number of members. Group passenger types can also be categorized into multiple group passenger types based on gender, age, number of members, etc. FIG. 5 is a diagram for explaining an example of determining passenger types based on PNR information according to an embodiment of the present invention. Group passenger types may be categorized into one or more group passenger types based on criteria such as number of passengers, gender, age, number of members, etc. For example, it may be determined whether or not a care type is present based on age, and whether or not a couple is present based on number / gender. As shown in the figure, a representative reservation person can reserve an airline ticket including fellow passengers. When the airline ticket reservation is completed, a PNR 410 for the representative reservation person can be generated. In addition, since the PNR includes a child, the passenger type determination unit 215 can determine the passenger type as a care type 420.

[0021] Also, one PNR can be mapped to multiple group passenger types. For example, the PNR shown in Figure 5 can be mapped to both the Care type and the Family type. The recommendable seat deriving unit 225 can derive all group seats that can currently be recommended using the group seat pattern information and the seat information (S330). The group seat pattern information can include shape information of the group seats. The shape of the group seats can be a square type, an L-shape, an I-shape, etc. And, the seat information can include seat map information of the entire seats in the airplane and information on the currently occupied seats. The recommendation value calculation unit 235 may calculate a recommendation value for each of the derived group seats (S340). The recommendation value calculation unit 235 may calculate a recommendation value using a position value and a pattern value of each seat included in each derived group seat.

[0022] The variables that determine the position value include a variable D that represents the value of the distance to the exit in the vertical direction of the seat, a variable WMA that represents the value of the horizontal position of the seat being a window seat, an aisle seat, or a middle seat, a variable LMR that represents the value of the horizontal position of the seat being in the right block, the center block, or the left block, etc. The variables that determine the pattern value include a variable S that represents the value of the area per seat, a variable US that represents the value of the degree of separation between seats from other passengers, etc. In addition, when calculating the recommendation value, a variable P that represents a value based on the price per seat can be used.

[0023] The recommendation value may be calculated according to the following Equation 1. The following Equation 1 is an example of using variables when calculating the recommendation value, and the present invention is not limited thereto. [Formula 1] TIFF0007605442000001.tif9128Here, V is the recommendation value, D is a variable that represents the value of the distance from the seat to the exit in the vertical direction, WMA is a variable that represents the value of the horizontal position of the seat whether it is a window seat, an aisle seat, or a middle seat, LMR is a variable that represents the value of the horizontal position of the seat whether it belongs to the right block, center block, or left block, S is a variable that represents the value of the area per seat, B is a variable that represents the value of the degree of proximity to the same passenger, US is a variable that represents the value of the degree of seat separation from other passengers, and P is a variable that represents the value of the price per seat. The above formula 1 is an example of calculating the recommendation value V. Therefore, the recommendation value V may be calculated by using only some or modifying the variables shown in the formula 1, rather than using all of them. For example, the recommendation value V may be calculated using a formula in which the recommendation value V is proportional to at least one of D, WMA, LMR, S, B, and US, and inversely proportional to P. The variables may be initially determined based on actual seat reservation purchase data.

[0024] FIG. 6 is a diagram illustrating a method for calculating recommendation values ​​and determining recommendation rankings according to an embodiment of the present invention. The pattern value can be calculated by multiplying B and US, where initial B values ​​can be assigned as follows: adjacent seats in the same row horizontally = 1, seats across the aisle in the same row = 0.5, diagonal seats between the front and back rows = 0.1, and seats in front and back = 0. Also, US can be calculated by the following Equation 2. [Formula 2] TIFF0007605442000002.tif11138Here, a block refers to a group of seats that are adjacent to each other and arranged consecutively. For example, 2A, 2B, and 2C may be arranged in one block, and 2D, 2E, and 2F may be arranged in another block.

[0025] A location value can then be calculated from the product of D, WMA, LMR, and S. An initial D value can be assigned with the first column having the closest distance to the exit = 1, then the second column = 0.75, ... The initial S value can be assigned as 1 for a normal seat and 2.32 for a wide seat such as a 2D seat. The initial value of the WMA can be set differently depending on whether the seat is a window seat, a middle seat, or an aisle seat. Also, the initial value of the LMR can be assigned differently depending on whether the lateral position of the seat belongs to the right block, the center block, or the left block. Then, different P values ​​can be assigned depending on the price per seat. A total recommendation value can be calculated by substituting the assigned variable values ​​into Equation 1. Then, the recommendation ranking of the group sheet can be determined according to the calculated recommendation value.

[0026] The group seat recommending unit 240 can recommend a predetermined number of group seats to the representative reservation user based on the calculated recommendation value (S350). The representative reservation person can select the recommended group seat if the recommended group seat is preferable, and can select another group seat if the recommended group seat is not preferable. The receiving unit 210 can receive the group seat information selected by the representative reservation user (S360). The gap analysis unit 250 may compare the group seat information selected by the representative reservation user with the recommended group seat information (S370), and adjust at least one of the position value and the pattern value based on the comparison result (S380).

[0027] FIG. 7 is a diagram for explaining a group seat selection process of a representative reservation user in the calculation of a recommendation value for a group seat according to the present invention. The recommendation value calculation unit 235 can calculate a recommendation value as shown by reference numeral 710 for each of all the derived current recommendable group sheets. The group sheet recommendation unit 240 can recommend a predetermined number of group seats to the representative reservation user based on the recommendation ranking as shown by reference numeral 720. That is, the group sheet recommendation unit 240 can display the screen 720 displaying the predetermined number of group seats. In this case, the recommended group sheets of the predetermined number can be displayed together with recommendation values, recommendation rankings, etc. In addition, price information of the recommended group seats can be additionally displayed on the screen 720 displaying the predetermined number of group seats.

[0028] In this case, if the representative reservation person prefers the recommended group seats as shown by reference numeral 730, he or she can select one of the recommended group seats. The gap analysis unit 250 may compare and analyze whether the recommended group seats of a certain number as shown by reference numeral 740 match those selected by the representative reservation user. Based on the analysis result, the gap analysis unit 250 may update the formula 1. More specifically, the gap analysis unit 250 may update at least one of the variables applied to the formula 1.

[0029] 8 and 9 are diagrams comparing recommendation values ​​according to the group seat recommendation model of the present invention with actual seat reservation purchase data. The Alpha Air Seat initial model data is a normalized value of the recommendation value calculated by Equation 1 when the variables in Equation 1 are assigned initial values, and the actual data is a normalized value of the seat purchase probability calculated from actual seat reservation purchase data. As can be seen in Figure 9, the initial model data of the Alpha Air Seat is quite similar to the actual data. However, there are some gaps in some seats. The gap analysis unit 250 may adjust the value assigned to at least one of D, WMA, LMR, S, B, and US based on the difference between the calculated recommendation value and the purchase probability that the actual representative reservation user selects and purchases a group seat. In addition, the initial values ​​assigned to the variables D, WMA, LMR, S, B, US, and P used in Equation 1 may be applied differently depending on the passenger type.

[0030] FIG. 10 is a diagram for explaining a method for calculating recommendation values ​​and determining recommendation rankings for seats in a performance hall such as a theater according to the present invention. In FIG. 10, the recommendation value calculation formula can be applied similarly to that in FIG. 6. However, the distance D here can mean the distance to the stage. FIG. 11 shows a group sheet pattern of the present invention. As shown in the figure, there are various group seat patterns depending on the total number of group members. The group patterns can be classified into I-shape, L-shape, and square-shape. FIG. 12 is a diagram for explaining the process of selecting a group seat by a representative reservation person in the case of seats at a performance hall such as a play according to the present invention, and FIG. 13 is a diagram for explaining the process of selecting a group seat by a representative reservation person in the case of seats at a sports stadium according to the present invention. The same explanation as for FIG. 7 can be applied to FIGS. 12 and 13.

[0031] Therefore, the recommendation value calculation unit 235 calculates a recommendation value for each of all currently recommendable group seats that have been derived, and the group sheet recommendation unit 240 can recommend a predetermined number of group seats to the representative reservation user based on the recommendation ranking. In this case, if the representative reservation person prefers one of the recommended group seats, he or she can select one of the recommended group seats. The gap analysis unit 250 can analyze the result as to whether the recommended predetermined number of group seats are the ones selected by the representative reservation user. As described above, the method and device for recommending airplane seats according to an embodiment of the present invention can determine a group passenger type based on PNR information and recommend a group seat suitable for the passenger type.

[0032] According to the present invention, all group seats that can currently be recommended are derived according to the group passenger type, and a recommendation value for each derived group seat is calculated to recommend the group seat, thereby making it possible to improve the convenience of seat selection for customers. In addition, by adjusting the variable values ​​used to calculate the recommendation value through analysis of the group seat information recommended based on the recommendation value and the group seat information selected by the representative reservation user, it is possible to recommend a group seat that reflects the needs of the customer. The above-mentioned seat recommendation method and device can be applied not only to the configurations and methods of the above-mentioned embodiments, but also to the above-mentioned embodiments, which can be configured by selectively combining all or part of each embodiment so that various modifications can be made.

Claims

1. A seat recommendation method in a seat recommendation device connected to a computer network, comprising: determining a group type based on the representative's name record (NR) information, the NR information including the representative and accompanying person information; deriving all group seats that can currently be recommended using the group seat pattern information and the seat information; Calculating a recommendation value corresponding to the group type for each of all the derived group sheets; recommending a predetermined number of group seats to a representative based on the calculated result value; The group seat pattern information includes shape information of the group seat, The seat information includes seat map information of all seats and currently occupied seat information, The step of calculating the recommendation value includes: calculated using position values ​​and pattern values ​​for the derived group sheet; The step of calculating the recommendation value includes: Using at least one of the following variables (D) representing the value of the distance to the exit in the vertical direction of the seat, (WMA) representing the value of the seat's horizontal position whether it is a window seat, an aisle seat, or a middle seat, (LMR) representing the value of the seat's horizontal position whether it belongs to the right block, center block, or left block, (S) representing the value of the area per seat, (B) representing the value of the degree of adjacent seating with a companion, and (US) representing the value of the degree of seat separation from others, and a variable (P) representing the value of the price per seat, The seat recommendation method is characterized in that the recommendation value is calculated by the following Equation 1: [Formula 1] (Here, V is a recommendation value, D is a variable representing the value of the distance from the seat to the exit in the vertical direction, WMA is a variable representing the value of the seat's horizontal position whether it is a window seat, an aisle seat, or a middle seat, LMR is a variable representing the value of the seat's horizontal position whether it belongs to the right block, center block, or left block, S is a variable representing the value of the area per seat, B is a variable representing the value of the degree of proximity to a companion, US is a variable representing the value of the degree of seat separation from others, and P is a variable representing the value of the price per seat.)

2. A seat recommendation device connected to a computer network, a group type determination unit for determining a group type based on a representative's name record (NR) information, the NR information including the representative and accompanying person information; a group pattern database in which group sheet pattern information is stored; a recommendable sheet deriving unit for deriving all group sheets that can be currently recommended using the group sheet pattern information and the sheet information; A recommendation value calculation unit that calculates a recommendation value for each of all the derived group sheets; a group sheet recommendation unit that recommends a predetermined number of group sheets based on the calculated result value; a control unit for controlling the receiving unit for receiving the NR information, the group type determining unit, the group pattern database, an air seat database in which the seat information is stored, the recommendable seat deriving unit, the recommendation value calculating unit, and the group seat recommending unit; The group seat pattern information includes shape information of the group seat, The seat information includes seat map information of all seats and currently occupied seat information, The recommendation value calculation unit is Calculating the recommendation value using the derived position value and pattern value for the group sheet; The recommendation value calculation unit is Using at least one of the following variables (D) representing the value of the distance to the exit in the vertical direction of the seat, (WMA) representing the value of the seat's horizontal position whether it is a window seat, an aisle seat, or a middle seat, (LMR) representing the value of the seat's horizontal position whether it belongs to the right block, center block, or left block, (S) representing the value of the area per seat, (B) representing the value of the degree of adjacent seating with a companion, and (US) representing the value of the degree of seat separation from others, and a variable (P) representing the value of the price per seat, The seat recommendation device calculates the recommendation value according to the following Equation 1. [Formula 1] (Here, V is a recommendation value, D is a variable representing the value of the distance from the seat to the exit in the vertical direction, WMA is a variable representing the value of the seat's horizontal position whether it is a window seat, an aisle seat, or a middle seat, LMR is a variable representing the value of the seat's horizontal position whether it belongs to the right block, center block, or left block, S is a variable representing the value of the area per seat, B is a variable representing the value of the degree of proximity to a companion, US is a variable representing the value of the degree of seat separation from others, and P is a variable representing the value of the price per seat.)

3. A seat recommendation method in a seat recommendation device connected to a computer network, comprising: deriving all group sheets that can be currently recommended corresponding to a group type based on the representative's NR information, the NR information including the representative and accompanying person information; Calculating a recommendation value for each of the derived group sheets using a plurality of variables; recommending a number of group seats based on the calculated result values; receiving group sheet information selected by the representative; comparing the representative selected group sheet information with the recommended group sheet information; adjusting a value of at least one of the plurality of variables based on the comparison; The plurality of variables include at least one of a variable (D) representing a value according to the distance to an exit in the longitudinal direction of a seat, a variable (WMA) representing a value according to whether the lateral position of the seat is a window seat, an aisle seat, or a middle seat, a variable (LMR) representing a value according to whether the lateral position of the seat belongs to a right block, a center block, or a left block, a variable (S) representing a value according to the area per seat, a variable (B) representing a value according to the degree of adjacentness to a companion, and a variable (US) representing a value according to the degree of seat separation from others, and a variable (P) representing a value according to the price per seat, The method for recommending a seat, wherein the step of calculating the recommendation value comprises calculating the recommendation value according to the following Equation 1: [Formula 1] (Here, V is a recommendation value, D is a variable representing the value of the distance from the seat to the exit in the vertical direction, WMA is a variable representing the value of the seat's horizontal position whether it is a window seat, an aisle seat, or a middle seat, LMR is a variable representing the value of the seat's horizontal position whether it belongs to the right block, center block, or left block, S is a variable representing the value of the area per seat, B is a variable representing the value of the degree of proximity to a companion, US is a variable representing the value of the degree of seat separation from others, and P is a variable representing the value of the price per seat.)

4. A seat recommendation device connected to a computer network, a recommendable sheet deriving unit for deriving all group sheets currently recommendable in accordance with a group type based on the representative's NR information, the NR information including the representative and accompanying person information; a recommendation value calculation unit that calculates a recommendation value for each of all the derived group sheets using a plurality of variables; a group sheet recommendation unit that recommends a predetermined number of group sheets based on the calculated result value; a receiving unit for receiving group sheet information selected by the representative; a gap analysis unit that compares the group sheet information selected by the representative with the recommended group sheet information and adjusts a value of at least one of the plurality of variables based on the comparison result; a control unit that controls the recommendable seat derivation unit, the recommendation value calculation unit, the receiving unit, and the gap analysis unit, The plurality of variables include at least one of a variable (D) representing a value according to the distance to an exit in the longitudinal direction of a seat, a variable (WMA) representing a value according to whether the lateral position of the seat is a window seat, an aisle seat, or a middle seat, a variable (LMR) representing a value according to whether the lateral position of the seat belongs to a right block, a center block, or a left block, a variable (S) representing a value according to the area per seat, a variable (B) representing a value according to the degree of adjacentness to a companion, and a variable (US) representing a value according to the degree of seat separation from others, and a variable (P) representing a value according to the price per seat, The seat recommendation device, wherein the recommendation value calculation unit calculates the recommendation value according to the following Equation 1. [Formula 1] (Here, V is a recommendation value, D is a variable representing the value of the distance from the seat to the exit in the vertical direction, WMA is a variable representing the value of the seat's horizontal position whether it is a window seat, an aisle seat, or a middle seat, LMR is a variable representing the value of the seat's horizontal position whether it belongs to the right block, center block, or left block, S is a variable representing the value of the area per seat, B is a variable representing the value of the degree of proximity to a companion, US is a variable representing the value of the degree of seat separation from others, and P is a variable representing the value of the price per seat.)

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