KR20190105477A - Rental car service apparatus and vehicle searching service method - Google Patents

Abstract

Disclosed are a rental car service device and a vehicle search service method in the device. In the method, a first step of generating a learning model for detecting a vehicle corresponding to a natural language keyword by performing machine learning for a plurality of data sets as a data set composed of the natural language keyword and vehicle information corresponding thereto is performed. Thereafter, a second step is performed. In the second step, using the learning model, AI-based vehicle search for searching for the vehicle corresponding to the natural language keyword input from a customer terminal is performed. The searched vehicle information and vehicle option information corresponding to the natural language keyword used in the vehicle search are provided to the customer terminal. A customer searches for a desired vehicle among the searched vehicles based on the searched vehicle information and the vehicle option information corresponding to the natural language keyword used for the vehicle search.

Description

Car rental service device and vehicle search service method in the device {RENTAL CAR SERVICE APPARATUS AND VEHICLE SEARCHING SERVICE METHOD}

The present invention relates to a car rental service apparatus and a vehicle search service method therefor.

Recently, due to the advantages of short-term lease or initial cost incurred when purchasing a vehicle for travel in another city, long-term rental car service has become popular due to the ease of handling costs and the cost savings of corporations and individual operators. have.

However, in the case of a general car rental service, a person who rents a vehicle, that is, a customer visits a car rental company or a location to be rented, prepares a car lease agreement according to a form provided by the car rental company, and immediately acquires a vehicle, Alternatively, the customer calls the rental car company, checks the lease period of the vehicle, the type of the leased vehicle, or the fee according to the lease period of the vehicle, and if there is a vehicle to be leased, the vehicle is leased by signing a rental contract.

Recently, car rental service has been provided for online vehicles through wired and wireless Internet. In this case, the customer can access the system for the rental car service and record the type of car, region, date, rental period, and whether the driver is included in the contract. Search for availability and select the car model, make a reservation, visit the car rental company on the day of the reservation, or take over the car rented at a location agreed with each other.

However, in the case of the conventional online car rental service, the vehicle search is limited to the type of vehicle, the price range, and the fuel type, so that it is not easy to search for the vehicle desired by the customer, and the vehicle is recommended through the sales person offline. There is a problem in that it does not provide a vehicle search function of the form.

SUMMARY OF THE INVENTION The present invention provides a rental car service apparatus and a vehicle search service method in the apparatus for allowing a customer to search for and select a vehicle suitable for a desired use.

Vehicle search service method according to an aspect of the present invention,

A method for providing a vehicle search by a rental car service apparatus, the method comprising: generating a learning model for detecting a vehicle corresponding to a natural language keyword by machine learning a plurality of data sets as a data set comprising natural language keywords and corresponding vehicle information; And vehicle information based on the searched vehicle information and vehicle option information corresponding to the natural language keyword used for the vehicle search by performing an AI-based vehicle search for searching for a vehicle corresponding to the natural language keyword inputted from a customer terminal using the learning model. Providing the customer terminal with the customer to search for the vehicle desired by the customer based on the searched vehicle information and the vehicle option information corresponding to the natural language keyword used for the vehicle search. .

Here, the vehicle option information corresponding to the natural language keyword used for the vehicle search is obtained corresponding to the natural language keyword at the time of AI-based vehicle search using the learning model.

The searching of the vehicle may be performed by mixing a vehicle direct search provided by searching and providing a vehicle according to a keyword directly related to the vehicle.

Also, keywords directly associated with the vehicle are keywords corresponding to the manufacturer of the vehicle, the type of the vehicle, the name of the vehicle, and the fuel used by the vehicle.

Also, the natural language keyword is a keyword not directly related to the vehicle.

Car rental service apparatus according to another aspect of the present invention,

As a data set composed of natural language keywords and corresponding vehicle information, a learning model for detecting a vehicle corresponding to the natural language keyword is generated by machine learning a plurality of data sets, and then the corresponding training model is used to correspond to the natural language keyword. A machine learning unit which detects a vehicle and provides vehicle option information corresponding to the natural language keyword used in the vehicle search; When a natural language keyword is input by a customer, an AI-based vehicle search for searching for a vehicle corresponding to the natural language keyword using the learning model is performed through the machine learning unit, and the vehicle learning unit searches for the vehicle from the machine learning unit. A search unit configured to receive vehicle option information corresponding to a natural language keyword and provide the searched vehicle information and vehicle option information corresponding to the natural language keyword used in the vehicle search to the customer terminal; And receiving the natural language keyword of the customer through a customer terminal connected through a network, controlling the search unit to perform a vehicle search to obtain vehicle option information corresponding to the searched vehicle information and the natural language keyword used for the vehicle search. And a control unit provided to the terminal to control the customer to search for a desired vehicle among the searched vehicles based on the searched vehicle information and vehicle option information corresponding to the natural language keyword used for the vehicle search.

In addition, the estimator for generating a quotation for the vehicle selected by the customer of the searched vehicle through the search unit; And an electronic contract unit that performs an electronic contract for the vehicle lease requested by the customer.

In addition, the vehicle option information corresponding to the natural language keyword used for the vehicle search is obtained by the machine learning unit corresponding to the natural language keyword at the time of searching for an AI-based vehicle using the learning model.

The search unit further performs a direct vehicle search by using a keyword directly related to the vehicle, and the search unit performs a hybrid search combining the AI-based vehicle search and the direct vehicle search.

In addition, the search unit performs a vehicle search based on the personalized information of the customer, the personalized information of the customer includes the location information and the preferred vehicle information of the customer.

In addition, the estimator transmits the history of the information of the vehicle for which the quotation is requested to the machine learning unit, and the machine learning unit further performs machine learning using the information of the vehicle for which the quotation is requested.

According to the present invention, since the vehicle can be searched using natural language keywords not directly related to the vehicle, it is possible to provide a wide range of rental vehicles and a vehicle search service in which a customer feels.

In addition, by providing the vehicle option information corresponding to the natural language keyword used in the search, an accurate search for the vehicle desired by the customer can be performed.

1 is a diagram illustrating a schematic example of using a rental car service apparatus according to an embodiment of the present invention.
FIG. 2 is a detailed block diagram of a rental car service apparatus according to an exemplary embodiment of the present invention shown in FIG. 1.
3 is a schematic flowchart of a vehicle search service method in a rental car service according to an exemplary embodiment of the present invention.
4 is a detailed flowchart of a vehicle search and searched vehicle information providing process illustrated in FIG. 3.
5 is a diagram illustrating an example of an AI-based vehicle search in a vehicle search service method according to an exemplary embodiment of the present invention.
FIG. 6 is a view illustrating schematic contents of a search vehicle information screen displayed on a customer terminal in a vehicle search service method according to an exemplary embodiment of the present invention.
FIG. 7 is a diagram illustrating one specific example of the search vehicle information screen of FIG. 6.
8 is a diagram illustrating an example of vehicle preference content provided for each vehicle searched according to the vehicle search service method according to an exemplary embodiment of the present invention.
FIG. 9 is a diagram illustrating an example of content comparison content provided for each vehicle searched according to the vehicle search service method according to an exemplary embodiment of the present invention.

DETAILED DESCRIPTION Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those skilled in the art may easily implement the present invention. As those skilled in the art would realize, the described embodiments may be modified in various different ways, all without departing from the spirit or scope of the present invention. In the drawings, parts irrelevant to the description are omitted in order to clearly describe the present invention, and like reference numerals designate like parts throughout the specification.

Throughout the specification, when a part is said to "include" a certain component, it means that it can further include other components, without excluding other components unless specifically stated otherwise. In addition, the terms “… unit”, “… unit”, “module”, etc. described in the specification mean a unit that processes at least one function or operation, which may be implemented by hardware or software or a combination of hardware and software. have.

Hereinafter, a method of estimating a service in a car rental service and a car rental service apparatus providing the method will be described with reference to the accompanying drawings.

1 is a diagram illustrating a schematic example of using a rental car service apparatus according to an embodiment of the present invention.

Referring to FIG. 1, a rental car service apparatus 100 according to an exemplary embodiment of the present invention is connected to a customer terminal 300 through a network 200 and also connected to various external servers 400 through a network 200. Connected. At this time, the various external servers 400 may be servers providing various documents required for credit check of the customer who rents the vehicle.

Here, the network 200 refers to a connection structure capable of exchanging information between each node such as a plurality of terminals and servers connected to the network 200. An example of such a network 200 is 3GPP (3rd Generation Partnership). Project network, Long Term Evolution (LTE) network, 5th Generation Partnership Project (5GPP) network, Local Area Network (LAN), Wireless Local Area Network (WLAN), Wide Area Network (WAN), Personal Area Network (PAN) , Bluetooth networks, etc., but are not limited thereto.

The customer terminal 300 accesses the rental car service device 100 through the network 200 to search for a desired vehicle by the customer, and generates a quote of the searched vehicle to perform an electronic contract for the vehicle for which the quotation is generated. It is a terminal. In detail, the customer terminal 300 inputs a keyword for vehicle search and provides the keyword to the rental car service apparatus 100, receives and displays vehicle information corresponding to the keyword from the rental car service apparatus 100, and the rental car service apparatus. Request the quotation generation for the displayed vehicle, receive and display the generated quotation information, and also request the rental car service apparatus 100 for a contract for the vehicle that is to be rented, and the rental car service apparatus 100. After receiving and displaying the contract contents from the contract, the contract contents are electronically signed and provided to the rental service apparatus 100. The customer terminal 300 may be a terminal or a computer that can access the rental car service apparatus 100 through the corresponding network 200. Here, the terminal or the computer may be, for example, a wireless communication device, a notebook computer, a desktop, a personal computer, or the like equipped with a wired / wireless internet-based web browser. The wireless communication device may be a personal communication system (PCS), a global system for mobile communications (GSM), a personal digital cellular (PDC), a personal handyphone system (PHS), a personal digital assistant (PDA), or an international mobile telecommunication (IMT)-. 2000, Code Division Multiple Access (CDMA) -2000, W-Code Division Multiple Access (W-CDMA), Wireless Broadband Internet (WBRO) terminals, smartphones, smartpads, tablet PCs It may include all kinds of handheld based wireless communication device such as.

The rental car service apparatus 100 provides a vehicle search function through the customer terminal 300. In an embodiment of the present invention, artificial intelligence (AI) based vehicle search is supported. For example, natural language keywords are based on deep learning technology, which is a machine learning technology built on Artificial Neural Network (ANN) to enable computers to learn on their own like humans using various data. Learning about a corresponding vehicle search may be performed, and vehicle information searched using a natural language keyword input from the customer terminal 300 may be provided to the customer terminal 300 using the learning result.

In particular, in the exemplary embodiment of the present invention, a natural language keyword that is not related to the vehicle to be searched is not a keyword that is directly related to the vehicle such as a specification of the vehicle, a name of the vehicle, a manufacturer of the vehicle, fuel used in the vehicle, and the like. A learning model may be used to enable a vehicle search for a natural language keyword, such as a keyword, for example, a vehicle use or a customer use.

Therefore, in the embodiment of the present invention, when the customer inputs a natural language keyword indicating a use, such as "for family weekend outing" or "commuting", that the customer wants to use through the customer terminal 300, Through the learning model already learned on the basis of artificial intelligence, the vehicle corresponding to the natural language keyword input by the customer is searched and provided to the customer terminal 300.

In addition, the car rental service apparatus 100 according to an embodiment of the present invention searches for vehicle option information corresponding to the natural language keyword used in the search when searching for a vehicle based on artificial intelligence using the natural language keyword input by the customer. Can be provided with

In addition, the rental car service apparatus 100 may generate an estimate of the vehicle selected by the customer terminal 300 and provide the quotation to the customer terminal 300. The vehicle estimate at this time may also be generated in more detail using information such as vehicle-related options selected by the customer terminal 300, period-based rent, lease conditions, vehicle insurance, and the like.

In addition, the rental car service apparatus 100 performs an electronic contract for a vehicle for which a quotation is generated by the selection of the customer terminal 300. The rental car service device 100 may receive various documents from various external servers 400 for credit examination of a customer who rents a vehicle and use the same in an electronic contract.

Meanwhile, the rental car service apparatus 100 may be implemented as a computer that can access the terminal 300 or the external server 400 through the network 200. Here, the computer may be, for example, a medium-large computer, a desktop computer, or the like that can configure a server.

Hereinafter, the rental car service apparatus 100 according to an exemplary embodiment of the present invention will be described in more detail.

FIG. 2 is a detailed block diagram of a rental car service apparatus 100 according to an exemplary embodiment of the present invention shown in FIG. 1.

As shown in FIG. 2, the rental car service apparatus 100 according to an exemplary embodiment of the present invention includes a customer interface 110, a server interface 120, an information database (Database, DB) 130, and a machine learning unit 140. , A searcher 150, an estimator 160, an electronic contractor 170, and a manager 180. In this case, since the rental car service apparatus 100 illustrated in FIG. 2 is only one embodiment of the present invention, the present invention is not limitedly interpreted through FIG. 2 and is different from FIG. 2 according to various embodiments of the present disclosure. It may be configured.

The customer interface 110 provides an interface that allows the customer terminal 100 to access the car rental apparatus 100 through the network 200.

The server interface 120 provides an interface for allowing the car rental apparatus 100 to access the external server 400 through the network 200.

The information DB 130 stores and manages a variety of information used by the rental car service apparatus 100 to provide a rental car service including a vehicle search, vehicle quotation generation, vehicle electronic contract, and the like to a customer. The information DB 130 is a vehicle information DB 131 for storing information of a vehicle that can be rented to a customer, a customer information DB 132 for storing information of a customer registered as a member for using the rental car service, and Search information DB (133) for storing the vehicle search information searched on the basis of artificial intelligence using the natural language keywords entered, the information on the quotation for each option used to generate the vehicle quotation and the quotation information generated by requesting the vehicle quotation by the customer The quotation information DB 134 to store, the contract information DB 135, etc. which store the vehicle rental contract information serviced through this car rental service are included. In addition, the car rental apparatus 100 may additionally store and manage information necessary for providing the car rental service.

The machine learning unit 140 is a data set consisting of natural language keywords and vehicle information corresponding thereto, generates a corresponding learning model by machine learning a large amount of data, and searches a vehicle for the natural language keyword using the generated learning model. to provide. Here, machine learning is a field of artificial intelligence, which is a technology for predicting the future by analyzing massive data, and a technology for solving problems by acquiring information that is not input while the computer goes through a learning process. For machine learning, deep learning techniques using neural networks such as Convolutional Neural Network (CNN), Region with Convolutional Neural Network (R-CNN), and Long Short Term Memory (LSTM) may be used.

As described above, in the embodiment of the present invention, a keyword directly related to the vehicle as in the related art, for example, a keyword such as a manufacturer of the vehicle, a specification of the vehicle, a name of the vehicle, and a fuel used for the vehicle is used. Service to search for a vehicle, as well as machine learning to enable a vehicle search for natural language keywords such as "family weekend outing" and "commuting" that the customer wants not directly related to the vehicle. And generates a corresponding learning model, and similarly searches for a vehicle corresponding to the input natural language keyword using the learning model when a natural language keyword corresponding to a desired use is inputted by a customer not directly related to the vehicle. can do.

In an embodiment of the present invention, the machine learning unit 140 determines the vehicle option information to be used for the vehicle search based on the natural language keyword and searches the vehicle using the natural language keyword, and uses the determined vehicle option information to determine the vehicle. You can search for The machine learning unit 140 may provide vehicle option information corresponding to the natural language keyword used for the vehicle search to the search unit 150 when the searched vehicle information is provided to the search unit 150.

The search unit 150 displays a screen for searching a vehicle to the customer terminal 300 through the customer interface 110, and inputs a natural language keyword for searching for a desired vehicle through the customer terminal 300. The natural language keyword is transmitted to the machine learning unit 140, the vehicle information retrieved corresponding to the natural language keyword input from the machine learning unit 140 is received and provided to the customer terminal 300 and the customer terminal 300 or the customer. The vehicle information retrieved corresponding to the stored information is stored in the search information DB 133. In this case, the searcher 150 may receive the vehicle option information corresponding to the natural language keyword used for the vehicle search from the machine learning unit 140 and provide the searched vehicle information to the customer terminal 300.

In detail, the search unit 150 may allow a customer to select a vehicle of a desired use by using vehicle option information corresponding to a natural language keyword used to search for a vehicle based on artificial intelligence. In particular, the searcher 150 searches for and provides the vehicle corresponding to the natural language keyword inputted by the customer from among a plurality of options together with the vehicle information searched using the natural language keyword inputted by the customer. Additional vehicle option information that served as an important search element may be provided. For example, if the natural language keyword entered by the customer is "for four family weekend outings," the passenger capacity option of the vehicle is an important factor because the vehicle searched by the natural language keyword must be four or more vehicles. Since the trunk capacity option for loading luggage corresponding to the person will be an important factor, it can be provided so that the customer can recognize it as important vehicle option information searched based on natural language keywords entered by the customer when selecting a vehicle to rent. To this end, the searcher 150 uses the vehicle information searched by the machine learning unit 140 and the vehicle option information corresponding to the natural language keyword used in the vehicle search provided together with the vehicle learning unit 140. .

In addition, the searcher 150 may store the vehicle option information provided from the machine learning unit 140 in the search information DB 133 corresponding to the searched vehicle information. In addition, the vehicle searched by the machine learning unit 140 may be one or more vehicles.

In addition, the search unit 150 may provide a search service that enables direct search of the vehicle using keywords directly related to the vehicle as well as the artificial intelligence-based search as described above.

In addition, the searcher 150 may search for the vehicle according to the personalized information of the customer input or selected by the customer and provide the vehicle to the customer terminal 300. Here, the personalized information of the customer may include the customer's residential location information, preferred vehicle information, and the like.

In addition, the search unit 150 may combine the AI-based search and the direct vehicle search to enable a mixed search. For example, in the direct vehicle search, the vehicle search range may be defined by a search keyword that is directly related to the vehicle, and then an AI-based search may be performed by inputting a natural language keyword among the vehicles within the limited range. Alternatively, after the search based on a natural language keyword based on artificial intelligence, a search may be performed through a direct vehicle search within the result.

In addition, the search unit 150 may further provide a virtual test guide, a comparison of specifications, an expert review, a user review, and the like for each searched vehicle.

The estimator 160 provides the client terminal 300 with a screen for generating a quotation for the vehicle selected by the customer among the searched vehicles provided to the customer terminal 300 through the searcher 150, and the customer terminal 300. When a variety of option information and the like for input of the quotation is generated or selected through), a quotation for the corresponding vehicle is generated and provided to the customer terminal 300.

The estimator 160 stores and manages the history and quotation information on the vehicle information requested by the customer in the quotation information DB 134 among the vehicles searched through the searcher 150, and the machine learning unit 140. ) May reflect the history of the quote information stored in the quote information DB 134 at the time of machine learning to perform the learning. For example, it may be reflected as vehicle preference information, gender preference information, and preference information for each age group to be reflected in an AI-based search. In addition, such information may also be provided as vehicle-specific information searched by the searcher 150.

The electronic contract unit 170 allows the customer to respond to the quotation for the vehicle generated by the estimator 160 to perform the electronic contract for the vehicle, and at this time, the external server 400 Credit screening documents can be obtained for use in electronic contracts.

The controller 180 controls the searcher 150, the estimator 160, and the electronic contractor 170 to provide a vehicle search service based on AI as well as a vehicle search directly to the customer terminal 300. It enables the selection of natural language keywords based on a customer input for a vehicle searched based on intelligence, and also performs a lease contract according to an electronic contract for a vehicle selected by the customer.

As described above, according to an exemplary embodiment of the present invention, since the vehicle can be searched using natural language keywords not directly related to the vehicle, the vehicle search service can be provided in a wide selection of rental vehicles and in the form of a customer experience. .

In addition, when the customer selects to generate a quotation from the searched vehicles, the selection may be performed by focusing on the vehicle option information corresponding to the natural language keyword input by the customer.

Hereinafter, a search service method in a rental car service according to an embodiment of the present invention will be described in detail with reference to the accompanying drawings.

3 is a schematic flowchart of a search service method in a rental car service according to an exemplary embodiment of the present invention.

Referring to FIG. 3, first, a rental car service apparatus 100 according to an exemplary embodiment of the present invention may support a natural language keyword and its corresponding keyword in order to support a vehicle search using an artificial intelligence-based natural language keyword according to an exemplary embodiment of the present invention. As a data set composed of vehicle information, a corresponding learning model is generated by machine learning a large amount of data (S100).

Thereafter, the rental car service according to the embodiment of the present invention is started, and the natural language keyword desired by the customer is input through the customer terminal 300 connected to the rental car service device 100 through the network 200. In operation S110, the input natural language keyword is received by the rental car service apparatus 100. For example, a customer may perform a vehicle search by inputting a natural language keyword corresponding to a desired purpose of the customer, for example, a natural language keyword “for weekend outings of four family members” on the vehicle search screen displayed on the customer terminal 300. Can be.

Here, in the car rental service apparatus 100 according to an embodiment of the present invention, in addition to the AI-based vehicle search as described above, a keyword directly related to the vehicle by the customer on the vehicle search screen, for example, the manufacturer of the vehicle and the vehicle type. In addition, the vehicle may be directly searched by selecting a keyword of the vehicle name.

Next, the rental car service apparatus 100 performs a vehicle search using a natural language keyword transmitted from the customer terminal 300 (S120). In detail, when the natural language keyword is transmitted from the customer terminal 300, the rental car service apparatus 100 searches for a vehicle corresponding to the natural language keyword input using the learning model generated by the machine learning in step S100. .

Thereafter, the rental car service apparatus 100 provides the customer terminal 300 with information of the vehicle searched on the basis of artificial intelligence (S130). At this time, the vehicle information retrieved corresponding to the natural language keyword may be provided to the customer terminal 300 together with the vehicle option information corresponding to the natural language keyword used for the vehicle search. As such, the rental car service apparatus 100 according to an exemplary embodiment of the present invention provides vehicle option information corresponding to a natural language keyword with respect to the searched vehicle to the customer terminal 300, based on the vehicle option information used in the vehicle search. Vehicle selection can be performed. In addition, the information of the searched and provided vehicle may be one or more vehicle information.

Accordingly, the customer terminal 300 displays the vehicle information and the vehicle option information corresponding to the natural language keyword used for the vehicle search provided in the step S130 to the customer, and at least one vehicle selected by the customer. Request a quote to the rental car service apparatus 100 (S140).

The car rental service apparatus 100 receives various option information for generating a quote from the customer terminal 300 according to a request for a quote from a customer, and generates a quote for at least one vehicle for which a quote is requested in step S140. In operation S150, the generated vehicle quotation information is provided to the customer terminal 300 (S160).

The customer views the at least one vehicle quotation information displayed through the customer terminal 300, selects a desired vehicle, and requests the vehicle rental contract from the car rental service apparatus 100 (S170). At this time, the customer may repeat the process from the AI-based vehicle search step (S110), or from the vehicle request request step (S140) to search for a variety of vehicles or request a quote of the various vehicles.

The customer may repeatedly perform the above process once or several times using the customer terminal 300 to select a vehicle to be finally leased and request a rental contract from the car rental apparatus 100.

When the vehicle rental contract is requested from the customer terminal 300 as described above, the car rental service apparatus 100 first determines from the external server 400 through the network 200 to determine whether the customer who has requested the vehicle rental contract can be contracted. Collecting documents required for the credit review of the customer (S180), and performs the vehicle lease contract requested by the customer through the electronic contract (S190).

4 is a detailed flowchart of a vehicle search and searched vehicle information providing process illustrated in FIG. 3. The vehicle search and the searched vehicle information providing process may be performed by the rental car service apparatus 100, specifically, the searcher 160 described with reference to FIG. 2.

Referring to FIG. 4, when a vehicle search is requested by inputting a natural language keyword for a desired use by a customer through a search screen displayed on the customer terminal 300, a natural language keyword is included from the customer terminal 300. The search request is received by the rental car service apparatus 100 (S200). Referring to the example of FIG. 5, a customer selects an AI-based vehicle search tab (AI vehicle recommendation) 11 on a vehicle search screen displayed on the customer terminal 300, and then selects a natural language keyword corresponding to a desired purpose. For example, a vehicle search may be performed by inputting the keyword “for weekend outings of a family of four” 12.

According to the vehicle search request, the natural language keyword input by the customer is checked (S210), and the vehicle search corresponding to the natural language keyword is performed using the learning model generated by machine learning (S220).

Thereafter, the searched vehicle information and the vehicle option information corresponding to the natural language keyword used in the search are obtained (S230). In this case, the searched vehicle information and the vehicle option information corresponding to the natural language keyword used in the search may be stored in the search information DB 133.

Thereafter, a search vehicle information screen reflecting the obtained vehicle option information is configured (S240), and displayed on the customer terminal 300 (S250). Here, an example of the search vehicle information screen displayed on the customer terminal 300 to view the vehicle search result requested by the customer is illustrated in FIG. 6. Referring to FIG. 6, the search vehicle information screen 500 displayed on the customer terminal 300 corresponds to a search term input area 510 for a vehicle search, vehicle option information reflected at the search, that is, a natural language keyword used at the search. There is a vehicle option information display area 520, a search result list display area 530 which displays a search result, that is, searched vehicle information. One specific example of such a search vehicle information screen is shown in FIG. In particular, in an embodiment of the present invention, vehicle option information used in the search by the natural language keyword input by the customer may be provided for reference in selecting the vehicle in which the customer is searched. For example, in the example of FIG. 7, when a customer searches for a vehicle for a weekend outing of a family of four, the passengers and trunk trunks are displayed so that the customer may select the searched vehicle. By being provided with the vehicle option information that is important for this desired application, it is possible to select the vehicle that is more accurate and desired.

In the example of FIG. 7, the customer checks the searched vehicle information displayed on the search result list display area 530 by referring to the vehicle option information corresponding to the natural language keyword used in the search displayed on the vehicle option information display area 520. The vehicle of this desired use can be selected.

Accordingly, the customer selects a desired vehicle from among the searched vehicles by referring to the search vehicle information screen 500 displayed on the customer terminal 300, in particular, the vehicle option information reflected at the time of search, and selects the “quote quote” button 540. You can request a quote for the selected vehicle.

On the other hand, in the search service method according to an embodiment of the present invention, by additionally providing a variety of content corresponding to the searched vehicle displayed on the customer terminal 300, the customer checks the various content provided by the searched quantity to select the desired vehicle To be used. Referring to the example shown in FIG. 7, according to the embodiment of the present invention, the car-only company benefits 531, vehicle preferences 532, virtual test rides 533, comparison of specifications 534, and expert reviews 535 for each vehicle found. ), User reviews 536 and the like.

First, the benefit 531 content of the car rental company displays content providing various benefit information provided by the car rental company providing a search service method according to an exemplary embodiment of the present invention.

As shown in FIG. 8, the vehicle preference 532 content provides vehicle preference related content such as 'total vehicle sales ranking', 'competition vehicle sales ranking', 'gender preference', 'age preference' and the like.

The virtual test ride 533 content is a content that allows the user to experience the virtual test ride in the front and rear seats in the form of a 360-degree virtual reality image registered for the searched vehicle.

As shown in FIG. 9, the content comparison 534 content provides specification information for each vehicle that can compare specifications of a vehicle corresponding to the retrieved vehicle, for example, a competitor vehicle of the same class. In this case, the specifications corresponding to the vehicle option information corresponding to the natural language keyword used in the search displayed on the vehicle option information display area 520 may be displayed on the specification comparison item. In the example of FIG. 9, since the vehicle option information corresponding to the natural language keyword of 'for weekend outing of four family members' is 'boarding number' and 'trunk capacity', as shown in FIG. Vehicle option information for, i.e., 'boarding number' and 'trunk capacity' information may be displayed together.

The expert review 535 content is content that displays vehicle expert review contents registered by a car rental company.

The user review 536 content is content that displays various reviews provided by users for the found vehicle.

As such, the user may search and select a vehicle that he / she desires more accurately through various contents provided for each vehicle.

The embodiments of the present invention described above are not only implemented through the apparatus and the method, but may be implemented through a program for realizing a function corresponding to the configuration of the embodiments of the present invention or a recording medium on which the program is recorded.

Although the embodiments of the present invention have been described in detail above, the scope of the present invention is not limited thereto, and various modifications and improvements of those skilled in the art using the basic concepts of the present invention defined in the following claims are also provided. It belongs to the scope of rights.

Claims (11)

A method for a rental car service device to service a vehicle search,
Generating a learning model for detecting a vehicle corresponding to the natural language keyword by machine learning a plurality of data sets as a data set consisting of the natural language keyword and vehicle information corresponding thereto; And
By using the learning model, the vehicle-based vehicle search is performed to search for a vehicle corresponding to a natural language keyword input from a customer terminal, and the vehicle information and vehicle option information corresponding to the natural language keyword used for vehicle search are recalled. Providing the customer terminal to search for the desired vehicle among the searched vehicles based on the searched vehicle information and vehicle option information corresponding to the natural language keyword used for the vehicle search.
Vehicle search service method comprising a. The method of claim 1,
Vehicle option information corresponding to the natural language keyword used for the vehicle search is obtained corresponding to the natural language keyword at the time of AI-based vehicle search using the learning model.
Vehicle search service method. The method of claim 1,
Searching for the vehicle may include:
Performing a mixture of direct vehicle search provided by searching and providing a vehicle according to a keyword directly related to the vehicle,
Vehicle search service method. The method of claim 3,
Keywords directly related to the vehicle are keywords corresponding to the manufacturer of the vehicle, the type of the vehicle, the name of the vehicle, and the fuel used by the vehicle.
Vehicle search service method. The method of claim 4, wherein
The natural language keyword is a keyword that is not directly associated with a vehicle.
Vehicle search service method. As a data set composed of natural language keywords and corresponding vehicle information, a learning model for detecting a vehicle corresponding to the natural language keyword is generated by machine learning a plurality of data sets, and then the corresponding training model is used to correspond to the natural language keyword. A machine learning unit which detects a vehicle and provides vehicle option information corresponding to the natural language keyword used in the vehicle search;
When a natural language keyword is input by a customer, an AI-based vehicle search for searching for a vehicle corresponding to the natural language keyword using the learning model is performed through the machine learning unit, and the vehicle learning unit searches for the vehicle from the machine learning unit. A search unit configured to receive vehicle option information corresponding to a natural language keyword and provide the searched vehicle information and vehicle option information corresponding to the natural language keyword used in the vehicle search to the customer terminal; And
The client terminal receives the natural language keyword of the customer through a client terminal connected through a network and controls the search unit to perform a vehicle search to obtain vehicle option information corresponding to the searched vehicle information and the natural language keyword used for the vehicle search. And a control unit for controlling the customer to search for a vehicle desired by the customer based on the searched vehicle information and vehicle option information corresponding to the natural language keyword used for the vehicle search.
Car rental service apparatus comprising a. The method of claim 6,
An estimator configured to generate an estimate for the vehicle selected by the customer among the searched vehicles through the search unit; And
Electronic contract that performs an electronic contract for the vehicle lease requested by the customer
The car rental apparatus further comprises. The method of claim 6,
Vehicle option information corresponding to the natural language keyword used for the vehicle search is obtained by the machine learning unit corresponding to the natural language keyword when searching for an AI-based vehicle using the learning model.
Car rental service device. The method of claim 6,
The search unit further performs a direct vehicle search using a keyword directly related to the vehicle,
The search unit performs a mixed search combining the AI-based vehicle search and the vehicle direct search,
Car rental service device. The method of claim 6,
The search unit performs a vehicle search based on the customer's personalized information,
The personalized information of the customer includes the customer's residential location information and preferred vehicle information,
Car rental service device. The method of claim 6,
The estimator transmits the history of the information of the vehicle for which the quotation is requested to the machine learning unit,
The machine learning unit performs machine learning by further using information of the vehicle for which the quotation is requested.
Car rental service device.

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