KR-102961940-B1 - System and Method for Multi-selection Smart Integrated Service Based on AI Voice and Location/Traffic Information Linkage, and Computer-Readable Recording Medium Having Recorded Thereon a Program for Executing the Same

KR102961940B1KR 102961940 B1KR102961940 B1KR 102961940B1KR-102961940-B1

Abstract

The present invention relates to a multi-selection integrated reservation order system and method, and a program stored on a computer-readable recording medium to perform the same. That is, the multi-selection integrated reservation order system is characterized by receiving multi-selection reservation order information for at least two industry categories from a user terminal, generating user recommendation information using the multi-selection reservation order information, transmitting the user recommendation information to the user terminal, receiving user selection information from the user terminal, generating scheduling information by performing schedule and movement path configuration using the user selection information, generating reservation order information using the scheduling information, extracting discount information based on the reservation order information, generating multi-selection reservation order information by performing final reservation order confirmation and payment using the discount information, transmitting the multi-selection reservation order information to the user terminal, receiving real-time location information from the user terminal, generating movement path information using the multi-selection reservation order information and the real-time location information, and transmitting the movement path information to the user terminal.

Inventors

손민우

Assignees

주식회사 우성다인패스

Dates

Publication Date: 20260512
Application Date: 20250520

Claims (20)

In a multi-selection integrated reservation order system, One or more processors; and When executed by the above-mentioned one or more processors, the system includes one or more memories in which instructions are stored to cause the above-mentioned one or more processors to perform operations, and The above one or more processors, Receive multi-selection information for at least two or more industry categories from a user terminal, and User recommendation information is generated using the above multi-selection information, and The above user recommendation information is transmitted to the above user terminal, and Receiving user selection information from the above user terminal, By performing schedule and movement path configuration using the above user selection information, scheduling information is generated, and Multi-selection reservation order information is generated using the above scheduling information, and The above multi-selection reservation order information is transmitted to the user terminal, and Receive real-time location information from the above user terminal, and Movement path information is generated using the above multi-selection reservation order information and the above real-time location information, and The above movement path information is transmitted to the user terminal, and The above one or more processors, When generating the above user recommendation information, The final recommendation score is calculated by multiplying user preference, user similarity, review score, and real-time accessibility information by their respective weights, and Generating the above user recommendation information using the above final recommendation score, Multi-selection integrated reservation order system.
In Article 1, The above one or more processors, When receiving the above multi-selection reservation order information, Receiving major category selection information for any one of the above at least two industry categories, and Using the above major category selection information, the artificial intelligence model automatically generates medium category recommendation information, and Receives medium category selection information for any one of the above medium category recommendation information, and The above medium-category selection information is input into the above artificial intelligence model to generate small-category recommendation information, and Receive subcategory selection information for any one of the above subcategory recommendation information, and Receiving the above major category selection information, the above medium category selection information, and the above minor category selection information as the above multi-selection reservation order information, Multi-selection integrated reservation order system.
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In Article 1, The above one or more processors, When generating the above reservation order information, Receive reservation order availability time information and business hour information of the first franchise store based on the above reservation order information, and The probability of a successful reservation order at the first franchise store is calculated using the reservation order availability time information and business time information of the first franchise store, and If the probability of a reservation order success at the first franchise store is below a first threshold, the reservation order availability time information and business hour information of the second franchise store are received, and The probability of a successful reservation order at the second franchisee is calculated using the reservation order availability time information and business hour information of the second franchisee. If the probability of a reservation order success of the second merchant is greater than or equal to the first threshold, the reservation order information for the second merchant is generated as the reservation order information. Multi-selection integrated reservation order system.
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In Article 1, The above one or more processors, Receive review data, and The above review data is analyzed using an artificial intelligence model to analyze at least one of sentiment, keywords, and entities, and The above analysis results are scored to generate quantitative data, and Calculating the review score using the above quantified data, Multi-selection integrated reservation order system.
In Article 1, The above one or more processors, Calculate the estimated time of arrival using the above real-time location information and the above movement path information, and By comparing the above estimated arrival time and the reservation order time, an alarm signal is generated if it is delayed by more than a second threshold compared to the above reservation order time, and Transmitting the above alarm signal to a merchant terminal according to the above multi-selection reservation order information, Multi-selection integrated reservation order system.
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One or more processors; and A multi-selection integrated reservation ordering method performed in a multi-selection integrated reservation ordering system comprising one or more memories storing instructions to be executed by one or more processors, wherein A step of receiving multi-selection information for at least two or more industry categories from a user terminal by the above-mentioned one or more processors; A step of generating user recommendation information using the multi-selection information by the above one or more processors; A step of transmitting the user recommendation information to the user terminal by the above one or more processors; A step of receiving user selection information from the user terminal by the above one or more processors; A step of generating scheduling information by performing schedule and movement path configuration using the user selection information by the above one or more processors; A step of generating multi-selection reservation order information using the scheduling information by the above one or more processors; A step of transmitting the multi-selection reservation order information to the user terminal by the above one or more processors; A step of receiving real-time location information from the user terminal by the above one or more processors; A step of generating movement path information using the multi-selection reservation order information and the real-time location information by the above one or more processors; and The method includes the step of transmitting the movement path information to the user terminal by the above one or more processors, The step of generating the above movement path information is, Calculate the cost index by multiplying the total travel distance, waiting time, and reservation success probability by their respective weights, and A step of searching for an optimal path to determine the order of visits such that the above cost index is minimized, Multi-selection integrated reservation ordering method.
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In Paragraph 12, The step of receiving the above-mentioned multi-selection reservation order information is, A method comprising the step of receiving a natural language sentence input via voice through a user terminal, analyzing the natural language sentence using Natural Language Processing (NLP) technology, and automatically extracting multi-selection reservation order information including at least two industry categories. Multi-selection integrated reservation order method.
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In Paragraph 12, After the step of transmitting the above-mentioned multi-selection reservation order information to the user terminal, the step of calculating the user's recommended departure time based on the estimated arrival time and the reservation order time by the one or more processors; and The method further includes the step of sending a departure notification message to a user terminal at the time of the departure recommendation by the above one or more processors, and A multi-selection integrated reservation ordering method that further includes the step of calculating the recommended departure time, the step of recalculating the recommended departure time based on the real-time location information and real-time traffic condition changes, and sending an additional notification message.
A computer-readable recording medium having a program to be executed on a computer comprising: one or more processors; and one or more memories in which instructions are stored that cause the one or more processors to perform operations when executed by the one or more processors, wherein A step of receiving multi-selection reservation order information for at least two or more industry categories from a user terminal by the above-mentioned one or more processors; A step of generating user recommendation information using the multi-selection reservation order information by the above one or more processors; A step of transmitting the user recommendation information to the user terminal by the above one or more processors; A step of receiving user selection information from the user terminal by the above one or more processors; A step of generating scheduling information by performing schedule and movement path configuration using the user selection information by the above one or more processors; A step of generating multi-selection reservation order information using the scheduling information by the above one or more processors; A step of transmitting the multi-selection reservation order information to the user terminal by the above one or more processors; A step of receiving real-time location information from the user terminal by the above one or more processors; A step of generating movement path information using the multi-selection reservation order information and the real-time location information by the above one or more processors; and The method includes the step of transmitting the movement path information to the user terminal by the above one or more processors, The program recorded on the above-mentioned recording medium is, In performing the step of generating the above user recommendation information, the one or more processors calculate, for each of the plurality of recommendation candidates, a personal preference score based on the user's past usage history and explicit preference, a user similarity score reflecting the preference of a group of other users clustered as having similar behavioral patterns to the user, a quantitative sentiment score derived by analyzing text reviews of the recommendation candidates using an artificial intelligence model, and a real-time accessibility score that combines the estimated time of arrival (ETA) between the user's current real-time location and the recommendation candidate's location and the current availability of reservation orders; The final recommendation score is calculated by applying predefined weights to each of the scores calculated above and summing them; A computer-readable recording medium having a program recorded thereon, characterized by generating user recommendation information sorted in order of highest to lowest calculated final recommendation scores.
In Paragraph 18, A computer-readable recording medium on which the above program is recorded is, A computer-readable recording medium having a program recorded thereon, characterized in that, in performing the step of receiving the above-mentioned multi-selection reservation order information, the one or more processors receive a multi-selection reservation order request in the form of natural language input as voice from a user terminal; and perform machine learning-based natural language processing (NLP) on the received natural language utterance to extract multi-selection information including at least two or more industry categories, specific details of services for each category, and desired reservation order conditions specified or implied by the user.
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Description

System and Method for Multi-selection Smart Integrated Service Based on AI Voice and Location/Traffic Information Linkage, and Computer-Readable Recording Medium Having Recorded Thereon a Program for Executing the Same The present invention relates to a multi-selection smart integrated service system based on AI voice and location/traffic information linkage, a method, and a computer-readable recording medium having a program for performing the same. More specifically, the invention relates to a technology that analyzes a user's real-time location information and traffic API (ETA) through AI-based voice commands, optimizes multiple reservations or orders based thereon, provides optimal merchant recommendations and schedules in real time, and supports the user's reservation or ordering experience more conveniently and efficiently by linking payment and point accumulation and usage. With the recent advancement of O2O (Online to Offline) services, there is an increasing demand among users to handle reservations, payments, and schedule checks for various outdoor activities (e.g., dining, beauty, healthcare, hobby classes, pets, etc.) on a single platform via smartphone or computer. However, existing reservation systems are generally limited to a single purpose, posing limitations to users simultaneously booking services from multiple merchants or managing multiple schedules in an integrated manner. For instance, if a user wishes to use a dining venue, a massage shop, and a pet shop consecutively, they must place separate reservation orders through their respective apps or websites, and optimization considering travel distance or time is not implemented. Furthermore, existing systems have limitations in utilizing voice-based interfaces and lack the functionality to optimize multi-selection reservation orders by reflecting the user's current location, real-time traffic conditions, preferences, and point accumulation history. Consequently, users end up spending excessive time and effort during the reservation process, and the service quality is often unsatisfactory. Therefore, there is a need for a system capable of handling a user's various schedules from reservation to payment in a single process. In other words, there is a growing need for a multi-selection smart integrated service system and method that automatically recommends multiple personalized reservations through voice recognition technology and AI-based data analysis, and provides the optimal choice by comprehensively considering factors such as schedule, location, transportation, and merchant service conditions. FIG. 1 is an exemplary diagram showing the configuration of a multi-selection smart integrated service system based on AI voice and location/traffic information linkage according to an embodiment of the present invention. FIG. 2 is an exemplary diagram showing the configuration of a server according to an embodiment of the present invention. FIG. 3 is a diagram illustrating the learning of a neural network according to an embodiment of the present invention. FIG. 4 is an illustrative diagram for explaining the overall configuration of a multi-selection reservation order system according to an embodiment of the present invention. FIG. 5 is a data flow diagram according to an embodiment of the present invention. FIG. 6 is an overall data processing flowchart according to an embodiment of the present invention. Figure 7 is a flowchart of recommendation data based on review analysis and sentiment analysis according to an embodiment of the present invention. FIG. 8 is a data flow diagram of an AI-based demand forecasting and business owner reminder system according to an embodiment of the present invention. FIG. 9 is a user behavior-based personalized marketing data flowchart according to an embodiment of the present invention. FIG. 10 is an overall flowchart according to an embodiment of the present invention. FIG. 11 is a flowchart of a data processing algorithm according to an embodiment of the present invention. FIG. 12 is an overall process diagram according to an embodiment of the present invention. FIG. 13 is a flowchart showing the procedure of a multi-selection smart integrated service method based on AI voice and location/traffic information linkage according to an embodiment of the present invention. Preferred embodiments of the present invention will be described below with reference to the attached drawings. However, the present invention is not limited to the embodiments described below, and various modifications and applications based on the technical concept of the present invention are possible. The terms and numbers used in the drawings are for the convenience of explanation and are merely relative naming conventions between components. In the present invention, 'multiple selection information' refers to an initial intention or choice that a user inputs into a system to use an integrated reservation order service, indicating an in