Method for providing customized answer reflecting travel propensity on basis of user input augmentation and electronic device performing same

Abstract

A method by which an electronic device provides a customized answer reflecting travel propensity on the basis of user input augmentation, according to one embodiment of the present application, is characterized by comprising the steps of: receiving a first input including a requirement related to travel from a user; determining the type of the requirement on the basis of keyword information corresponding to a pre-stored requirement type; generating an additional question on the basis of the type of the requirement; receiving a second input as an answer to the generated additional question; and providing a customized answer by determining detailed information included in the first input and the second input. According to one embodiment of the present invention, it is possible to provide a customized answer with high accuracy by generating and providing an additional question to further obtain information needed in order to generate an answer.

Description

A method for providing customized answers reflecting travel preferences based on user input augmentation and an electronic device for performing the same

[0001] The present application relates to a method for providing customized answers reflecting travel preferences based on user input augmentation and an electronic device for performing the same. Specifically, the present application relates to a method for providing customized answers reflecting travel preferences based on user input augmentation through additional questions corresponding to user input, and an electronic device for performing the same.

[0002]

[0003] With the spread of solo and spontaneous travel cultures, more people are seeking "personalized trips." A customized trip requires extensive preparation, such as searching for destinations and arranging transportation, accommodations, places to visit, nearby attractions, and travel routes that fit the itinerary. Consequently, there is a problem in that it is not easy to embark on a customized trip that reflects one's personal preferences.

[0004] Although travel recommendation services already exist, it takes a long time to provide customized services, and the probability of purchasing travel products is low due to dissatisfaction with the quality of recommendations.

[0005] Therefore, there is a need for a service that recommends customized trips based on the user's travel preferences using AI for personalized tourism recommendations.

[0006]

[0007] The problem that the present invention aims to solve is to provide a method for providing customized answers to user queries based on the user's travel preferences.

[0008] In addition, the problem that the present invention aims to solve is to provide a method for providing highly accurate customized answers by increasing user input through additional questions corresponding to user input.

[0009] The problems that the present invention aims to solve are not limited to those described above, and problems not mentioned will be clearly understood by those skilled in the art from this specification and the attached drawings.

[0010]

[0011] A method for an electronic device according to an embodiment of the present invention to provide a customized answer reflecting travel tendencies based on user input augmentation may include: receiving a first input containing travel-related requirements from a user; determining the type of the requirements based on keyword information corresponding to a pre-stored type of requirements; generating an additional question based on the type of requirements; receiving a second input as an answer to the generated additional question; and determining detailed information included in the first input and the second input to provide a customized answer.

[0012] An electronic device that provides a customized answer reflecting travel tendencies based on user input augmentation according to one embodiment of the present invention includes a communication unit, a processor, and a memory, and the memory may store instructions such that, at execution, the processor receives a first input including travel-related requirements from a user, determines the type of the requirements based on pre-stored requirements type information, generates an additional question based on the type of the requirements, receives a second input as an answer to the generated additional question, and determines detailed information included in the first input and the second input to provide a customized answer.

[0013] The means for solving the problem of the present invention are not limited to the means for solving the problem described above, and unmentioned means for solving the problem will be clearly understood by those skilled in the art from this specification and the attached drawings.

[0014]

[0015] According to one embodiment of the present invention, a method for providing a customized answer reflecting travel tendencies based on user input augmentation and an electronic device for performing the same can be provided, which can provide a customized answer with high accuracy by generating and providing additional questions to further acquire information necessary to generate an answer.

[0016]

[0017] FIG. 1 is a block diagram briefly illustrating the configuration of an electronic device according to one embodiment of the present application.

[0018] FIG. 2 is a block diagram briefly illustrating the configuration of a processor according to one embodiment of the present application.

[0019] FIG. 3 is a diagram illustrating requirement characteristic information including detailed information by type of requirement according to one embodiment of the present application.

[0020] FIG. 4 is a drawing for explaining a method for determining a user's influence tendency according to one embodiment of the present application.

[0021] FIG. 5 is a drawing for explaining a method for determining a user's influence tendency according to one embodiment of the present application.

[0022] FIG. 6 is a flowchart illustrating a method for providing a customized answer that reflects travel tendencies based on user input augmentation according to one embodiment of the present application.

[0023] FIG. 7 is a diagram illustrating a UI that provides a customized answer reflecting travel tendencies according to one embodiment of the present application.

[0024]

[0025] The aforementioned objectives, features, and advantages of the present application will become more apparent from the following detailed description in conjunction with the accompanying drawings. However, as the present application is subject to various modifications and may have various embodiments, specific embodiments are illustrated in the drawings and described in detail below.

[0026] Throughout the specification, identical reference numbers generally represent identical components. Additionally, components with identical functions within the same scope of concept appearing in the drawings of each embodiment are described using the same reference numeral, and redundant descriptions thereof are omitted.

[0027] If it is determined that a detailed description of known functions or configurations related to this application could unnecessarily obscure the essence of this application, such detailed description is omitted. Furthermore, numbers used in the description of this specification (e.g., First, Second, etc.) are merely identifiers to distinguish one component from another.

[0028] Furthermore, the suffixes "module" and "part" for components used in the following embodiments are assigned or used interchangeably solely for the ease of drafting the specification, and do not inherently possess distinct meanings or roles.

[0029] In the following examples, singular expressions include plural expressions unless the context clearly indicates otherwise.

[0030] In the following embodiments, terms such as "include" or "have" mean that the features or components described in the specification are present, and do not preclude the possibility that one or more other features or components may be added.

[0031] In the drawings, the size of components may be exaggerated or reduced for convenience of explanation. For example, the size and thickness of each component shown in the drawings are arbitrarily depicted for convenience of explanation, and the present invention is not necessarily limited to what is illustrated.

[0032] Where an embodiment can be implemented differently, the order of a particular process may be performed differently from the order described. For example, two processes described consecutively may be performed substantially simultaneously or proceed in the reverse order of the description.

[0033] In the following embodiments, when components are described as being connected, the case includes not only instances where the components are directly connected but also instances where components are indirectly connected by interposing them in between.

[0034] For example, when it is stated in this specification that components, etc. are electrically connected, it includes not only cases where the components, etc. are directly electrically connected, but also cases where components, etc. are interposed in between and are indirectly electrically connected.

[0035]

[0036] Hereinafter, with reference to FIGS. 1 to 6, a method for providing a customized answer reflecting travel tendencies based on user input augmentation according to the present application and an electronic device for performing the same will be described.

[0037]

[0038] FIG. 1 is a block diagram briefly illustrating the configuration of an electronic device according to one embodiment of the present application. Referring to FIG. 1, the electronic device (100) may include a communication unit (110), a processor (120), and a memory (130).

[0039]

[0040] The communication unit (110) can support the establishment of a direct (wired) communication channel or a wireless communication channel between the device (100) and an external device (e.g., a server), and the performance of communication through the established communication channel. The communication unit (110) may include one or more communication processors that operate independently of the processor (120) (e.g., an application processor) and support direct (e.g., wired) communication or wireless communication. According to one embodiment, the communication unit (110) may include a wireless communication module (e.g., a cellular communication module, a short-range wireless communication module, or a GNSS (global navigation satellite system) communication module) or a wired communication module (e.g., a LAN (local area network) communication module, or a power line communication module).

[0041]

[0042] The processor (120) can execute software to control at least one other component (e.g., a hardware or software component) of the device (100) connected to the processor (120) and can perform various data processing operations. According to one embodiment, as at least part of the data processing or operations, the processor (120) can store commands or data received from another component (e.g., a communication unit (110)) in volatile memory, process the commands or data stored in volatile memory, and store the resulting data in non-volatile memory. According to one embodiment, the processor (120) may include a main processor (e.g., a central processing unit or an application processor) or an auxiliary processor (e.g., a graphics processing unit, a neural processing unit (NPU), an image signal processor, a sensor hub processor, or a communication processor) that can be operated independently or together with it.

[0043] According to one embodiment, an auxiliary processor (e.g., a neural network processing unit) may include a hardware structure specialized for processing an artificial intelligence model. The artificial intelligence model may be generated through machine learning. Such learning may be performed, for example, on the electronic device (100) itself where the artificial intelligence is performed, or through a separate server. The learning algorithm may include, for example, supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning, but is not limited to the examples described above. The artificial intelligence model may include a plurality of artificial neural network layers. The artificial neural network may be a deep neural network (DNN), a convolutional neural network (CNN), a recurrent neural network (RNN), a restricted Boltzmann machine (RBM), a deep belief network (DBN), a bidirectional recurrent deep neural network (BRDNN), deep Q-networks, or a combination of two or more of the above, but is not limited to the examples described above. Artificial intelligence models may include software structures, either additionally or as a substitute, in addition to hardware structures.

[0044] The processor (120) can receive input from a user that includes travel-related requirements. Specifically, the processor (120) can receive input from the user through chat that analyzes the other party's text (or voice) and provides a response via conversational artificial intelligence. For example, the user's input may include travel-related requirements such as input for recommending travel destinations, input for recommending travel itineraries, input for receiving directions, etc.

[0045] The processor (120) can determine the type of requirement based on keyword information corresponding to a pre-stored requirement type. Specifically, the processor (120) can extract at least one keyword included in the user's input. Then, the processor (120) can determine the type of requirement by comparing the extracted keyword with the pre-stored keyword. For example, the requirement type may be a place recommendation type, a schedule creation type, a route finding type, an other information inquiry type, etc., and a keyword may be matched and pre-stored for each requirement type.

[0046] Meanwhile, the processor (120) can generate similar keywords similar to the keywords included in the user's input. And, the processor (120) can determine the type of the user input requirement using the keywords similar to the keywords included in the user input.

[0047] The processor (120) can generate additional questions based on the type of requirement. Specifically, the processor (120) can identify detailed elements corresponding to the previously determined type of requirement. Then, the processor (120) can identify detailed elements included in the user input and determine missing detailed elements that are not included in the user input among the detailed elements corresponding to the type of requirement. When missing detailed elements are determined, the processor (120) can generate additional questions based on the missing detailed elements. At this time, the requirement type may be a place recommendation type, a schedule creation type, a route finding type, an other information inquiry type, etc., and requirement characteristic information including detailed elements corresponding to each requirement type may be stored in advance.

[0048] The processor (120) can receive additional input as an answer to an additional question. Specifically, the processor (120) can provide the additional question in a chat format and receive an answer to the additional question.

[0049] The processor (120) can determine the user's travel tendency based on the results of the user's travel tendency test. Specifically, the processor (120) can provide questions to determine the user's travel tendency and receive answers to them. The processor (120) can determine the user's travel tendency based on the received answers.

[0050] Additionally, the processor (120) may determine the user's travel tendency based on the user's platform log data. Specifically, the processor (120) may determine the user's travel tendency based on the wishlist modification log, input query log, and detail page entry log included in the platform log data.

[0051] The processor (120) can provide a customized answer by determining the details included in the user's inputs and the user's travel tendencies. Specifically, the processor (120) can extract details from the user's inputs (e.g., user inputs received in the form of chat). Then, the processor (120) can determine the details corresponding to the extracted details. Then, the processor (120) can generate and provide a customized answer based on the details and the user's travel tendencies according to a predetermined weight.

[0052]

[0053] The memory (130) can store various data used by at least one component (e.g., processor (120)) of the electronic device (100). The data may include, for example, input data or output data for software and related instructions. The memory (130) may include volatile memory or non-volatile memory.

[0054] Memory (130) can store keyword information corresponding to each requirement type.

[0055] The memory (130) may include requirement characteristic information including detailed elements corresponding to each of the requirement types.

[0056]

[0057] FIG. 2 is a block diagram briefly illustrating the configuration of a processor according to one embodiment of the present application. FIG. 2 will be described in more detail with reference to FIG. 3 to 5. FIG. 3 is a diagram illustrating requirement characteristic information including detailed information by type of requirement according to one embodiment of the present application. FIG. 4 is a diagram illustrating a method for determining a user's influence tendency according to one embodiment of the present application. FIG. 5 is a diagram illustrating a method for determining a user's influence tendency according to one embodiment of the present application.

[0058]

[0059] Referring to FIG. 2, the processor (120) may include a requirement type determination unit (121), an additional question generation unit (123), a travel tendency determination unit (125), and a customized answer providing unit (127). The requirement type determination unit (121), the additional question generation unit (123), the travel tendency determination unit (125), and the customized answer providing unit (127) may be composed of at least one artificial intelligence model trained to perform the operations described in this specification, and each of the components may be composed of different artificial intelligence models.

[0060]

[0061] The requirement type determination unit (121) can determine the type of requirement of user input. The type of requirement is intended to distinguish the type of information the user wants to know through search, and may include, for example, a place recommendation type, a schedule creation type, a route finding type, or other information inquiry type.

[0062] The requirement type determination unit (121) may be composed of an artificial intelligence model trained to determine the type of user input requirement based on conversation log data of multiple users. Specifically, the requirement type determination unit (121) may be composed of an artificial intelligence model trained to determine the type of user input requirement by classifying the conversation log data of multiple users by type of requirement and then labeling the text tags of the requirement per conversation for learning inference and identification tasks within a small language model (sLLM).

[0063] The requirement type determination unit (121) can extract at least one keyword included in the user input. Then, it can determine the requirement type by comparing the extracted keyword with keyword information corresponding to a previously stored requirement type. For example, when input such as “recommend a restaurant that serves delicious tiger shrimp” is received from a user, the requirement type determination unit (121) can extract keywords such as “tiger shrimp,” “delicious,” and “restaurant,” and can determine the “place recommendation type” corresponding to “tiger shrimp,” “delicious,” and “restaurant” as the requirement type of the user input.

[0064] In addition, the requirement type determination unit (121) can increase the accuracy in determining the requirement type by extracting at least one keyword included in the user input and generating similar keywords similar to the extracted keyword. For example, when input such as “recommend a restaurant that serves delicious tiger shrimp” is received from a user, the requirement type determination unit (121) can extract keywords such as “tiger shrimp,” “delicious,” and “restaurant,” and generate similar keywords such as “famous restaurant” and “dining place,” and determine the requirement type based on the keywords and similar keywords.

[0065]

[0066] The additional question generation unit (123) can generate additional questions based on the type of requirements of the user input. The additional questions may be questions intended to elicit answers that include additional detailed elements for determining the user's requirements. Since the requirements are determined by considering the answers to the additional questions rather than determining the requirements based only on the received user input, the accuracy of the answers can be increased.

[0067] The additional question generation unit (123) may be composed of an artificial intelligence model trained to determine the specific elements that must be obtained to generate a customized answer based on conversation log data of multiple users.

[0068] The additional question generation unit (123) can generate additional questions based on detailed elements not included in the input among detailed elements corresponding to the requirement type of the received input.

[0069] Specifically, the additional question generation unit (123) can identify detailed elements corresponding to the previously determined requirement type based on the requirement characteristic information. As shown in FIG. 3, the requirement characteristic information may include detailed elements corresponding to the requirement type. Referring to FIG. 3, the detailed elements of the place recommendation type may include the time of visit, type of companion, location, menu information, parking availability, waiting conditions, emotional characteristics, etc.

[0070] Additionally, the additional question generation unit (123) can extract detailed information included in the user input and determine detailed elements corresponding to the extracted detailed information. Specifically, the detailed information may refer to search conditions, and the detailed element may be a higher-level concept of the search conditions. For example, if the input is “Recommend a restaurant that serves delicious tiger prawns,” the detailed information may be “tiger prawns,” and the detailed element may be “menu information” corresponding to tiger prawns.

[0071] Additionally, the additional question generation unit (123) can determine missing detailed elements that are not included in the user input among the detailed elements corresponding to the type of requirement. For example, the input “Recommend a restaurant that serves delicious tiger prawns” includes a detailed element called “menu information,” but does not include detailed elements such as the time of visit, type of companion, location, and parking availability, so these can be determined as missing detailed elements.

[0072] Additionally, the additional question generation unit (123) can generate additional questions based on missing details. If there are multiple missing details, the additional question generation unit (123) can generate additional questions based on at least one missing detail with a higher priority based on the priority of the missing details, or generate additional questions based on missing details corresponding to essential details. For example, if the missing details are the time of visit, type of companion, location, parking availability, etc., the additional question generation unit (123) can generate additional questions such as “Do you have a desired time and region?” to obtain detailed information corresponding to “time of visit” and “location.”

[0073]

[0074] The travel tendency judgment unit (125) may be composed of an artificial intelligence model trained to determine the travel tendency of a user based on the results of travel tendency tests of multiple users and / or platform log data, etc.

[0075] The travel tendency determination unit (125) can determine the user's travel tendency based on the user's travel tendency test results and / or platform log data. Specifically, referring to FIGS. 4 and 5, the travel tendency determination unit (125) can receive traveler tendency data based on the travel tendency test results and traveler tendency data based on platform log data. Based on the travel tendency data, the travel tendency determination unit (125) can generate a prompt according to the traveler tendency characteristics and input it into an artificial intelligence model corresponding to the requirement type. If the user's platform log data does not exist, the user's travel tendency can be determined based on the travel tendency test results.

[0076]

[0077] The customized answer providing unit (127) may be composed of an artificial intelligence model trained to generate answers to be provided to the user according to the type of requirements of the user input. Specifically, the customized answer providing unit (127) may be composed of an artificial intelligence model trained to output results containing information to be provided to the user in response to the input according to the type of requirements of the user input.

[0078] The customized answer providing unit (127) can provide a customized answer based on the detailed information included in the user's inputs and the user's travel tendencies. Specifically, the customized answer providing unit (127) can extract the detailed information included in the user's inputs and determine the detailed elements corresponding to the detailed information. Then, the customized answer providing unit (127) can generate and provide a customized answer based on the detailed elements and the user's travel tendencies according to a predetermined weight.

[0079]

[0080] FIG. 6 is a flowchart illustrating a method for providing a customized answer reflecting travel tendencies based on user input augmentation according to one embodiment of the present application. The actions in FIG. 6 are not limited in order, and other actions may be performed between two adjacent actions. Additionally, at least some of the actions in FIG. 6 may be omitted. In the present invention, the expression that an electronic device (100) performs a specific action may mean that a processor (120) of the electronic device (100) performs a specific action, or that the processor (120) controls other hardware to perform a specific action.

[0081] FIG. 6 will be explained in more detail with reference to FIG. 7. FIG. 7 is a diagram illustrating a UI that provides a customized answer reflecting travel tendencies according to an embodiment of the present invention.

[0082]

[0083] Referring to FIG. 6, the electronic device (100) may receive a first input from a user that includes travel-related requirements (S100). Specifically, the electronic device (100) may receive input from the user through chat, which analyzes the other party's text (or voice) and provides a response through conversational artificial intelligence. For example, the user's input may include travel-related requirements such as input for recommending travel destinations, input for recommending travel itineraries, input for receiving directions, etc. For example, as shown in FIG. 7, the electronic device (100) may receive conversational input that is not in a fixed format, such as “I want a healing trip where I can enjoy leisure and admire the scenery.”

[0084]

[0085] The electronic device (100) can determine the type of requirement based on pre-stored requirement type information (S200). Specifically, the electronic device (100) can extract at least one keyword included in the user's input. Then, the electronic device (100) can determine the type of requirement by comparing the extracted keyword with the pre-stored keyword. For example, as shown in FIG. 7, when input such as “I want a healing trip where I can enjoy leisure and view the scenery” is received, the electronic device (100) can extract “travel” as a keyword and determine the type of requirement as “schedule creation type”.

[0086]

[0087] The electronic device (100) can generate additional questions based on the type of requirement (S300). Specifically, the electronic device (100) can identify detailed elements corresponding to the previously determined type of requirement. Then, the electronic device (100) can identify detailed elements included in the user input and determine missing detailed elements that are not included in the user input among the detailed elements corresponding to the type of requirement. When missing detailed elements are determined, the electronic device (100) can generate additional questions based on the missing detailed elements. For example, detailed elements corresponding to the requirement type of schedule creation include travel period, local departure / arrival time, type of companion, means of transportation used, desired places to visit, schedule fatigue, emotional characteristics, etc. As shown in FIG. 7, the electronic device (100) can determine missing details among the details corresponding to the schedule generation type that are not included in the user input ("I want a healing trip where I can enjoy leisure and view the scenery"), and generate and provide additional questions such as "Is there any specific food you must eat?" based on some of the missing details (e.g., places you want to visit).

[0088]

[0089] The electronic device (100) can receive a second input as an answer to an additional question (S400). Specifically, the electronic device (100) can provide the additional question in a chat format and receive an answer to the additional question. For example, as shown in FIG. 7, the electronic device (100) can receive an input such as “I really want to eat tiger prawns!” in response to the additional question.

[0090]

[0091] The electronic device (100) can determine the details included in the first input and the second input and provide a customized answer (S500). Specifically, the electronic device (100) can extract details of the user's inputs (e.g., user inputs received in the form of chat). Then, the electronic device (100) can determine the details corresponding to the extracted details. Then, the electronic device (100) can generate and provide a customized answer based on the details and the user's travel tendencies according to a predetermined weight. For example, as shown in FIG. 7, the electronic device (100) can determine details such as "leisure," "viewing the scenery," "healing trip," and "tiger shrimp" from the user's inputs and provide a customized answer.

[0092]

[0093] According to a method for providing a customized answer reflecting travel tendencies based on user input augmentation according to an embodiment of the present invention and an electronic device for performing the same, there is an advantage in that a customized answer with high accuracy can be provided by generating and providing additional questions to obtain additional information necessary to generate an answer.

[0094]

[0095] The features, structures, effects, etc. described in the embodiments above are included in at least one embodiment of the present invention and are not necessarily limited to only one embodiment. Furthermore, the features, structures, effects, etc. exemplified in each embodiment may be combined or modified and implemented in other embodiments by a person skilled in the art to which the embodiments belong. Accordingly, details regarding such combinations and modifications should be interpreted as being included within the scope of the present invention.

[0096] Furthermore, although the embodiments have been described above, this is merely illustrative and does not limit the invention. Those skilled in the art will understand that various modifications and applications not exemplified above are possible within the scope of the essential characteristics of the embodiments. In other words, each component specifically shown in the embodiments may be modified and implemented. Differences related to such modifications and applications should be interpreted as being included within the scope of the invention as defined in the appended claims.

Claims

1. A method in which an electronic device provides a customized response reflecting travel preferences based on user input augmentation, A step of receiving a first input from a user that includes requirements related to travel; A step of determining the type of the requirement based on keyword information corresponding to a pre-stored requirement type; A step of generating additional questions based on the type of the above requirements; A step of receiving a second input as an answer to a generated additional question; and A step of determining detailed information included in the first input and the second input and providing a customized answer; Method for providing user-customized answers.

2. In Paragraph 1, The step of determining the type of the requirement based on keyword information corresponding to the previously stored requirement type is: A step of extracting at least one keyword included in a received first input; and A step of determining the type of the requirement by comparing at least one extracted keyword with keyword information corresponding to the type of the requirement. Method for providing user-customized answers.

3. In Paragraph 2, The step of determining the type of the requirement based on keyword information corresponding to the previously stored requirement type is: The method further comprises the step of generating similar keywords to at least one extracted keyword. Method for providing user-customized answers.

4. In Paragraph 1, The type of the above requirement is, Including place recommendations, itinerary creation, directions, and other information inquiries Method for providing user-customized answers.

5. In Paragraph 1, A step of storing requirement characteristic information including detailed elements corresponding to each of the multiple types of requirements; further comprising Method for providing user-customized answers.

6. In Paragraph 5, The step of generating additional questions based on the type of the above requirements is, A step of identifying detailed elements corresponding to the type of the above requirement; A step of extracting at least one detail information included in the first input; A step of determining detailed elements corresponding to at least one detailed information; A step of determining a missing detailed element not included in the first input among the detailed elements corresponding to the type of the above requirement; and A step of generating additional questions based on the above-mentioned missing details; Method for providing user-customized answers.

7. In Paragraph 1, A step of determining the user's travel propensity based on the user's travel propensity test results; further comprising Method for providing user-customized answers.

8. In Paragraph 7, The step of determining the details included in the first input and the second input to provide a customized answer is: A step of extracting detailed elements included in the first input and the second input; A step of determining detailed information corresponding to extracted detailed elements; A step of providing the customized answer based on determined details and the travel preferences of the user. Method for providing user-customized answers.

9. In Paragraph 7, The step of determining the user's travel propensity based on the user's travel propensity test results is, The step of receiving platform log data of the above user; and A step of determining the user's travel propensity based on wishlist modification logs, input query logs, and detailed content page entry logs included in the platform log data. Method for providing user-customized answers.

10. In Paragraph 8, The step of providing the customized answer based on the details included in the first and second inputs and the user's travel preferences is: Providing the customized answer by assigning weights to the details included in the first and second inputs and to the user's travel tendencies. Method for providing user-customized answers.

11. A computer-readable recording medium having a program stored on it for executing a method according to any one of claims 1 through 10 on a computer.

12. An electronic device that provides a customized answer reflecting travel tendencies based on user input augmentation, Communications Department; processor; and Includes memory; The above memory, at the time of execution, the processor, Receive a first input from a user including travel-related requirements, and Determine the type of the above requirement based on pre-stored requirement type information, and Generate additional questions based on the type of the above requirements, and Receives a second input as an answer to the generated additional question, and An electronic device that stores instructions for determining details included in the first input and the second input to provide a customized answer.

Images