KR102410460B1 - Method, apparatus and system for providing beauty shop reservation platform service based on artificial intelligence - Google Patents

Abstract

A method, apparatus and system for providing an artificial intelligence-based beauty shop reservation platform service are disclosed. The artificial intelligence-based beauty shop reservation platform service providing apparatus according to an embodiment of the present invention receives a beauty shop reservation request from a first user terminal and forms a first list including location information of beauty shops that can be reserved, Using the location information of the beauty shops included in the first list and the user's real-time location information, the beauty shops included in the first list are rearranged in the order closest to the user to form the first modified list, and the modified first list Transmits to the first user terminal, receives a selection reservation request for the first beauty shop among the beauty shops included in the modified first list from the first user terminal, and uses the user's real-time location information to allow the user to select the first beauty shop Calculates the time required to arrive at Forms the shortest route information for arriving at the first beauty shop from the location, and transmits the reservation completion guide and the shortest route information to the first user terminal.

Description

Method, device and system for providing AI-based beauty shop reservation platform service

The following embodiments provide a method of providing an artificial intelligence-based beauty shop reservation platform service that can arrange and provide information on beauty shops that can be reserved using the user's location information in a near order, and can make a reservation for the selected beauty shop to the user; It relates to devices and systems.

As a background art related to embodiments, Korean Patent Application Laid-Open No. KR 10-2018-0081934 A discloses a beauty shop reservation brokerage service system and method. Specifically, the preceding literature provides support for users who want to use a beauty shop to receive a discount according to the use of the beauty store by paying points when consulting for a reservation at the beauty shop, while at the same time providing active counseling from customers about the beauty shop. Initiate a beauty shop reservation brokerage service system and method to induce and support beauty shops to attract customers.

Through this, the prior literature supports the beauty shop to conduct advertisements without having to spend continuous advertising expenses, and at the same time pays the points provided as a reward for reservation consultation only to customers who have made a reservation consultation, so that the user can make a payment at the desired beauty shop. By supporting the use of the points for cost discounts, it is possible to induce active reservation consultations of users with minimal cost, as well as to secure the maximum number of valid customers who receive reservation consultations for beauty shops where reservation consultations are important. It provides the effect of further increasing the advertising efficiency compared to the uniform advertising method.

In addition, Korean Patent Laid-Open Publication No. KR 10-2014-0056869 A discloses a beauty shop management system using an information communication network and a kiosk and a recording medium thereof. Specifically, the prior literature describes a beauty shop management server and personal portable terminal (smartphone (mobile), ultrabook, tablet PC, etc.) by installing a kiosk that communicates with an information communication network (wired/wireless internet, etc.) in each beauty shop. ), a beauty shop management system using an information communication network and kiosk that allows you to collectively use beauty-related services such as reception/reservation/payment/education and additional services such as shopping/education/gallery/phototalk/contents. and a recording medium thereof.

Through this, the prior literature has the effect of enabling various services tailored to the convenience and eye level of consumers.

However, prior literatures provide an artificial intelligence-based beauty shop reservation platform service providing method, device, and Do not start the system.

Embodiments intend to arrange and provide information on beauty shops that can be reserved using the user's location information in a near order, and to make a reservation for the beauty shop selected by the user.

Embodiments intend to transmit a user review request to a user terminal after the user uses the beauty shop.

Embodiments intend to automatically perform payment after the user uses the beauty shop.

An AI-based beauty shop reservation platform service providing method according to an embodiment of the present invention comprises the steps of: receiving a beauty shop reservation request from a first user terminal, wherein the beauty shop reservation request includes real-time location information of the user; forming a first list including location information of beauty shops that can be reserved; forming a modified first list by rearranging the beauty shops included in the first list in the order closest to the user by using the location information of the beauty shops included in the first list and the real-time location information of the user; transmitting the modified first list to the first user terminal; receiving a selection reservation request for a first beauty shop among beauty shops included in the first modified list from the first user terminal; calculating a time required for the user to arrive at the first beauty shop by using the user's real-time location information; transmitting the selection reservation request to a second user terminal used in the first beauty shop in consideration of the required time; receiving a reservation completion guide from the second user terminal; forming shortest route information for arriving at the first beauty shop from the user's current location; and transmitting the reservation completion guide and the shortest route information to the first user terminal.

In one embodiment, using the real-time location information of the first user terminal calculating the estimated time for the user to arrive at the first beauty shop; transmitting the estimated time to the second user terminal; forming a user arrival notification signal when the user is located within a predetermined distance from the first beauty shop using real-time location information of the first user terminal; transmitting the user arrival notification signal to the second user terminal; using the real-time location information of the first user terminal to form and transmit a user review request to the first user terminal when the user deviates from the first beauty shop by a predetermined distance or more; receiving a review response to the user review request from the first user terminal; transmitting a preset point to the first user terminal in response to receiving the review response; and classifying and storing the review response by item.

As an embodiment, when the user is located within a predetermined distance from the first beauty shop using real-time location information of the first user terminal, a coupon list including information of coupons usable in the first beauty shop is generated as the second 1 transmitting to a user terminal; performing a first payment of the estimated cost of using the first beauty shop by applying a first coupon having the highest discount rate among the coupons in the coupon list; receiving service information provided by the user from the first beauty shop from the second user terminal when the user deviates from the first beauty shop by a predetermined distance or more using real-time location information of the first user terminal; forming a second payment history according to the use of the first beauty shop using the service information and the first coupon and transmitting it to the first user terminal; receiving an approval request for the second payment details from the first user terminal; and transmitting the second payment details to a card company server to perform a second payment.

In one embodiment, the beauty shop reservation request, further comprising the movement route information of the user, receiving and storing advertisement information of a plurality of beauty shops; extracting a predetermined number of second beauty shop information located within a predetermined distance from the moving path of the user by using the moving path information; extracting a third beauty shop matching the service item information extracted from the selection reservation request from among the second beauty shops; and transmitting advertisement information of the third beauty shop to the first user terminal.

In an embodiment, the method may further include: obtaining a user's residence history of the user through the moving route information; calculating an average staying time of the user by checking a residence time for each user based on the user's residence history; setting a reference value according to the length of the average residence time of the user; calculating a minimum time within the allowable range of the user as a value obtained by subtracting the reference value from the average residence time of the user; calculating a maximum time of the user permissible range as a value obtained by adding the reference value to the average residence time of the user; and setting the user permissible range based on the minimum time of the user permissible range and the maximum time of the user permissible range.

An apparatus according to an embodiment may be controlled by a computer program stored in a medium to execute the method of any one of the above-described methods in combination with hardware.

The embodiments can improve user convenience by providing information for a user's beauty shop reservation, save time required for payment through automatic payment after using the beauty shop, and collect user reviews after using the beauty shop. It has the effect of increasing the advertising effectiveness of the beauty shops in the store.

1 is a view for explaining an artificial intelligence-based beauty shop reservation platform service providing system according to an embodiment.
2 is a diagram for explaining a server according to an embodiment.
3 is a diagram for explaining learning of a neural network according to an embodiment.
4 is a flowchart of a method of providing an AI-based beauty shop reservation platform service according to an embodiment.
5 is an exemplary diagram of a configuration of an apparatus according to an embodiment.

Hereinafter, embodiments will be described in detail with reference to the accompanying drawings. However, since various changes may be made to the embodiments, the scope of the patent application is not limited or limited by these embodiments. It should be understood that all modifications, equivalents and substitutes for the embodiments are included in the scope of the rights.

Specific structural or functional descriptions of the embodiments are disclosed for purposes of illustration only, and may be changed and implemented in various forms. Accordingly, the embodiments are not limited to the specific disclosure form, and the scope of the present specification includes changes, equivalents, or substitutes included in the technical spirit.

Although terms such as first or second may be used to describe various elements, these terms should be interpreted only for the purpose of distinguishing one element from another. For example, a first component may be termed a second component, and similarly, a second component may also be termed a first component.

When a component is referred to as being “connected to” another component, it may be directly connected or connected to the other component, but it should be understood that another component may exist in between.

The terms used in the examples are used for the purpose of description only, and should not be construed as limiting. The singular expression includes the plural expression unless the context clearly dictates otherwise. In this specification, terms such as "comprise" or "have" are intended to designate that a feature, number, step, operation, component, part, or a combination thereof described in the specification exists, but one or more other features It should be understood that this does not preclude the existence or addition of numbers, steps, operations, components, parts, or combinations thereof.

Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which the embodiment belongs. Terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with the meaning in the context of the related art, and should not be interpreted in an ideal or excessively formal meaning unless explicitly defined in the present application. does not

In addition, in the description with reference to the accompanying drawings, the same components are given the same reference numerals regardless of the reference numerals, and the overlapping description thereof will be omitted. In describing the embodiment, if it is determined that a detailed description of a related known technology may unnecessarily obscure the gist of the embodiment, the detailed description thereof will be omitted.

The embodiments may be implemented in various types of products, such as personal computers, laptop computers, tablet computers, smart phones, televisions, smart home appliances, intelligent cars, kiosks, wearable devices, and the like.

An artificial intelligence (AI) system is a computer system that implements human-level intelligence, and unlike the existing rule-based smart system, the machine learns and judges by itself. The more the AI system is used, the better the recognition rate and the more accurate understanding of user preferences, and the existing rule-based smart systems are gradually being replaced by deep learning-based AI systems.

Artificial intelligence technology consists of machine learning and element technologies using machine learning. Machine learning is an algorithm technology that categorizes/learns the characteristics of input data by itself, and element technology uses machine learning algorithms such as deep learning to simulate functions such as cognition and judgment of the human brain. It consists of technical fields such as understanding, reasoning/prediction, knowledge expression, and motion control.

The various fields where artificial intelligence technology is applied are as follows. Linguistic understanding is a technology for recognizing and applying/processing human language/text, and includes natural language processing, machine translation, dialogue system, question and answer, and speech recognition/synthesis. Visual understanding is a technology for recognizing and processing objects like human vision, and includes object recognition, object tracking, image search, human recognition, scene understanding, spatial understanding, image improvement, and the like. Inferential prediction is a technology for logically reasoning and predicting by judging information, and includes knowledge/probability-based reasoning, optimization prediction, preference-based planning, and recommendation. Knowledge expression is a technology that automatically processes human experience information into knowledge data, and includes knowledge construction (data generation/classification) and knowledge management (data utilization). Motion control is a technology for controlling autonomous driving of a vehicle and movement of a robot, and includes motion control (navigation, collision, driving), manipulation control (action control), and the like.

In general, in order to apply a machine learning algorithm to real life, learning is performed in a trial and error method due to the characteristics of the basic methodology of machine learning. In particular, deep learning requires hundreds of thousands of iterations. It is impossible to execute this in the actual physical external environment, so instead, the actual physical external environment is implemented in a virtual computer on the computer, and learning is performed through simulation.

1 is a view for explaining an artificial intelligence-based beauty shop reservation platform service providing system according to an embodiment.

As shown in FIG. 1 , the AI-based beauty shop reservation platform service providing system 100 may include a plurality of user terminals 110 - 1 , ... , a server 120 , and a database 130 . According to an embodiment, the database 130 is illustrated as being configured separately from the server 120 , but the present invention is not limited thereto, and the database 130 may be provided in the server 120 . For example, the server 120 may include a plurality of artificial intelligence for performing a machine learning algorithm. According to an embodiment, the plurality of user terminals 110 - 1 , ... the server 120 and the database 130 may be connected to each other through a network N to communicate with each other.

A plurality of user terminals (110-1, ..., 110-n) are used by users who reserve a beauty shop through the artificial intelligence-based beauty shop reservation platform service providing system 100 and want to use the beauty shop. It may include a first user terminal (for example, 110-1) and a second user terminal (for example, 110-n) used by beauty shops registered to the AI-based beauty shop reservation platform service. . For example, the first user terminal 110-1 may form real-time location information of the user, including a global positioning system (GPS), and the like.

The server 120 may receive a beauty shop reservation request from the 　 first 　 user terminal 110 - 1 . According to an embodiment, the server 120 may receive a beauty shop reservation request from the first user terminal 110-1 used by a user who wants to use the beauty shop through the network N. For example, the beauty shop reservation request may include, but is not limited to, the user's real-time location information, movement route information, service item information, and the like.

The server 120 may form a first list including location information of beauty shops that can be reserved. According to an embodiment, the server 120 may form a first list including location information of beauty shops currently available for reservation among beauty shops subscribed to the AI-based beauty shop reservation platform service.

The server 120 uses the location information of the beauty shops included in the first list and the user's real-time location information to rearrange the beauty shops included in the first list in the order closest to the user to form the modified first list. can According to an embodiment, 　 server 120 includes location information (eg,   1 latitude and 1   longitude) of beauty shops included in the first   list and real-time location information of the user (eg,   2   latitude and 2nd longitude) to calculate the distance between the user's current location and the beauty shops included in the 1st list, and rearrange the beauty shops included in the 1st list in the order closest to the user using the calculated distance. Thus, the first revised list can be formed. For example, the server 120 may calculate the distance between the beauty shops included in the first list and the user's current location by using Equation 1 below.

[Equation 　1]

The server 120 may transmit the first revised list to the first user terminal. According to an embodiment, the 　 server 120 may transmit the formed first 　 list to the first 　 user terminal 110 - 1 through the network N.

The first 　 user terminal 110-1 receives a selection reservation request for the first 　 beauty shop, which is a specific beauty shop that is desired to be used among the beauty shops included in the first revised 　 list, from the user who has confirmed the 　 revised 1 　 list, and receives the server ( 120) can be transmitted.

The server 120 may receive a selection reservation request for the first beauty shop among the beauty shops included in the first revised list from the 　 first 　 user terminal. According to an embodiment, the server 120 may receive a selection reservation request for the first beauty shop among the beauty shops included in the first revised list from the first user terminal 110-1 through the network N. have.

The server 120 may calculate the required time required for the user to arrive at the first beauty shop by using the real-time location information of the user. According to an embodiment, the server 120 may calculate the distance between the first beauty shop and the user's current location using Equation 1, and the user's moving speed (for example, , 1 minute/100 m) to calculate the required time. For example, the server 120 may calculate the required time using Equation 2 below.

[Equation 　2]

The server 120 may transmit a selection reservation request to the second user terminal used in the first beauty shop in consideration of the required time. According to an exemplary embodiment, the server 120 transmits a selection reservation request along with the time required for the user to arrive at the first beauty shop to the second user terminal 110-n through the network N to the first The beauty shop can prepare in advance so that the service can be provided according to the arrival time of the user.

The second 　 user terminal 110-n may receive a reservation completion guide from the first 　 beauty shop user who has confirmed the 　 selection reservation request and transmit it to the server 120 . For example, the 　 reservation completion guide may include information on necessary preparations for using the first beauty shop, 　 usage fees, and the like.

The server 120 may receive a reservation completion guide from the second user terminal. According to an embodiment, the server 120 may receive a reservation completion notification from the second user terminal 110-n through the network N.

The server 120 may form the shortest route information for arriving at the first beauty shop from the user's current location. According to an embodiment, the server 120 may form the shortest path information for arriving at the first beauty shop from the user's current location by using the real-time location information of the user. For example, the server 120 uses a map application to display the user's current location and the location of the first beauty shop, and image the shortest path information from the user's current location to the first beauty shop. can be displayed in the map application.

The server 120 may transmit the reservation completion guide and the shortest route information to the first user terminal. According to one embodiment, 　 server 120 is the first 　 user terminal 110-1 through the network (N), the second 　 received from the user terminal 110-n through the reservation completion guide and map application formed using the shortest Route information can be transmitted.

The server 120 may calculate an expected time for the user to arrive at the first beauty shop by using the real-time location information of the first user terminal. According to an embodiment, the server 120 may calculate the estimated time for the user to arrive at the first beauty shop from the current location by using the real-time location information of the first user terminal 110-1.

The server 120 may transmit the estimated time to the second user terminal. According to an embodiment, the server 120 may transmit the calculated estimated time to the second user terminal 110-n through the network N.

The server 120 may form a user arrival notification signal when the user is located within a predetermined distance from the first beauty shop using real-time location information of the first user terminal. According to one embodiment, the server 120 uses the real-time location information of the first user terminal 110-1 to allow the user to be located within a predetermined distance (eg, 500m, 300m, 100m, etc.) from the first beauty shop. In this case, a user arrival notification signal may be formed.

The server 120 may transmit a 　 user arrival notification signal to the second 　 user terminal. According to an embodiment, the server 120 may transmit the formed user arrival notification signal to the second user terminal 110-n through the network N.

The server 120 may form a user review request and transmit it to the first user terminal when the user deviates from the first beauty shop by a predetermined distance or more using real-time location information of the first user terminal. According to one embodiment, the server 120 uses the real-time location information of the first user terminal 110-1 when the user deviates from the first beauty shop by a predetermined distance (eg, 500m, 1km, etc.) By determining that the user has finished using the first beauty shop, a user review request may be formed and transmitted to the first user terminal 110-1.

After receiving the user review request from the server 120 , the first user terminal 110 - 1 may receive a review response according to the user review request from the user and transmit it to the server 120 through the network N.

The server 120 may transmit a preset point to the first user terminal according to the reception of the review response. According to an embodiment, when the server 120 receives a review response from the first user terminal 110-1, it pays a preset point as a reward for participating in the review and sends it to the first user terminal 110-1. can send

The server 120 may classify and store 　review responses by item. According to an embodiment, the server 120 may receive the review response from the first user terminal 110-1, classify the review response by item and store it. For example, the server 120 may classify and store the received review response by item using a machine learning algorithm such as deep learning.

The server 120, when the user is located within a predetermined distance from the first beauty shop by using real-time location information of the first user terminal, returns a coupon list including information of coupons usable in the first beauty shop to the first user terminal. can send According to one embodiment, the server 120 uses the real-time location information of the first user terminal 110-1 when the user is located within a predetermined distance (eg, 300m, 100m, etc.) from the first beauty shop. 1 　 A coupon list including information on coupons usable in the beauty shop may be transmitted to the first 　 user terminal 110 - 1 through the network N.

The server 120 may perform the first payment of the estimated cost of using the first beauty shop by applying the first coupon having the highest discount rate among the coupons in the coupon list. According to an embodiment, the server 120 may perform the first payment of the estimated cost of using the first beauty shop by applying the first coupon having the highest discount rate among the coupons available in the first beauty shop. For example, 　 1 　 payment corresponds to a temporary payment, so information on the payment request is not transmitted to the card company server, etc., and the 　 server 120 can perform a formal payment after the user's first beauty shop use is completed. have. Therefore, it is possible to prevent a situation in which the user does not appear after making a reservation for the first beauty shop (no-show).

The server 120 uses real-time location information of the first user terminal to receive the service information provided by the user from the first beauty shop from the second user terminal when the user deviates from the first beauty shop by a predetermined distance or more. . According to one embodiment, the server 120 uses the real-time location information of the first user terminal 110-1 when the user deviates from the first beauty shop by a predetermined distance (eg, 50m, 100m, etc.) The user may receive service information provided by the first beauty shop from the second user terminal 110-n used in the 1　 beauty shop through the network N.

The server 120 may use the service information and the first coupon to form the second payment details according to the use of the first beauty shop and transmit it to the first user terminal. According to one embodiment, the server 120 forms a second payment history according to the user's use of the first beauty shop by using the service information provided by the user from the first beauty shop and the first coupon with the highest discount rate, This may be transmitted to the first 　 user terminal 110-1 through the network N.

The first 　 user terminal 110-1 may receive the second 　 payment details from the 　 server 120, receive the user's approval request for this, and transmit the approval request to the server 120 through the network N. .

The server 120 may receive an approval request for the second payment details from the first user terminal. According to an embodiment, the server 120 may receive an approval request for the second payment details from the first user terminal 110-1 through the network N.

The server 120 may transmit the second payment details to the card company server to perform the second payment. According to an embodiment, the 　 server 120 may transmit the second 　 payment details to the card company server through the network N to perform the second 　 payment.

The server 120 may receive and store advertisement information of a plurality of beauty shops. According to an embodiment, the server 120 receives the advertisement information of the beauty shops from the second user terminal 110-n used by the beauty shops through the network N, and stores the advertisement information in the database 130. can be controlled

The server 120 may extract information on a predetermined number of second beauty shops located within a predetermined distance from the user's movement path by using the movement path information. According to an embodiment, the server 120 uses the movement path information of the first user terminal 110-1 to a predetermined number (eg, 50m, 30m, etc.) located within a predetermined distance (eg, 50m, 30m, etc.) from the user's movement path. For example, 5 pieces, 10 pieces, etc.) of the second beauty shop information can be extracted.

The server 120 may extract a third beauty shop matching the service item information extracted from the selection reservation request among the second beauty shops. According to an embodiment, the server 120 may extract a third beauty shop that matches the service item information extracted from the selection reservation request received from the first user terminal 110-1 among the second beauty shops.

The server 120 may transmit advertisement information of the third beauty shop to the first user terminal. According to an embodiment, the server 120 may retrieve the extracted advertisement information of the third beauty shop from the database 130 and transmit it to the first user terminal 110-1 through the network N. That is, the server 120 extracts only beauty shops related to the service that the user wants to be provided from among the beauty shops located near the user, and transmits advertisements of the beauty shops to the first user terminal 110-1 to the user. can provide helpful information to make a reservation for beauty shops, and can improve the advertising effectiveness of beauty shops that have entered stores.

The server 120 obtains the user's stay history through the movement route information included in the beauty shop reservation request, and checks the residence time for each user based on the user's stay history, and calculates the average residence time of the user, , a standard value is set according to the length of the user's average stay time, the minimum time within the user's allowable range is calculated by subtracting the standard value from the user's average stay time, and the standard value is added to the user's average stay time , the maximum time of the user permissible range may be calculated, and the user permissible range may be set based on the minimum time of the user permissible range and the maximum time of the user permissible range.

The server 120 may obtain the user's stay history from the movement route information. According to an embodiment, the server 120 may extract the user's stay history from the moving route information by using a machine learning algorithm such as deep learning. For example, the server 120 may extract places where the user's latitude and longitude do not change for a certain period of time or more from the movement route information as the user's stay history.

The network N may perform wireless or wired communication between a plurality of user terminals 110-1, ..., the server 120, the database 130, etc. For example, the network may be a long-term (LTE) evolution), LTE-A (LTE Advanced), CDMA (code division multiple access), WCDMA (wideband CDMA), WiBro (Wireless BroadBand), WiFi (wireless fidelity), Bluetooth (Bluetooth), near field communication (NFC), GPS (Global Positioning System) or GNSS (global navigation satellite system) may be configured to perform wireless communication, etc. For example, the network (N) is a universal serial bus (USB), HDMI (high definition multimedia interface) , RS-232 (recommended standard 232) or POTS (plain old telephone service) may be configured to perform wired communication.

The database 130 may store various data. Data stored in the database 130 is data obtained, processed, or used by at least one component of the plurality of user terminals 110-1, ... server 120, and is software (eg, a program ) The database 130 may include volatile and/or non-volatile memory. In one embodiment, the database 130 may include the beauty The shop reservation request and selection reservation request, the reservation completion guide received from the second user terminal 110-n, the first list formed in the server 120, the first modified list, shortest path information, and the like may be stored.

In the present invention, artificial intelligence (AI) refers to a technology that imitates human learning ability, reasoning ability, perceptual ability, etc., and implements it with a computer, and concepts such as machine learning and symbolic logic may include Machine Learning (ML) is an algorithm technology that classifies or learns characteristics of input data by itself. Artificial intelligence technology is an algorithm of machine learning that can analyze input data, learn the results of the analysis, and make judgments or predictions based on the results of the learning. In addition, technologies that use machine learning algorithms to simulate functions such as cognition and judgment of the human brain can also be understood as a category of artificial intelligence. For example, technical fields such as verbal comprehension, visual comprehension, reasoning/prediction, knowledge expression, and motion control may be included.

Machine learning may refer to the processing of training a neural network model using the experience of processing data. With machine learning, computer software could mean improving its own data processing capabilities. The neural network model is constructed by modeling the correlation between data, and the correlation may be expressed by a plurality of parameters. A neural network model extracts and analyzes features from given data to derive correlations between data, and repeating this process to optimize parameters of a neural network model can be called machine learning. For example, the neural network model may learn a mapping (correlation) between an input and an output with respect to data given as an input/output pair. Alternatively, the neural network model may learn the relationship by deriving regularity between the given data even when only input data is given.

The artificial intelligence learning model or neural network model may be designed to implement a human brain structure on a computer, and may include a plurality of network nodes that simulate neurons of a human neural network and have weights. A plurality of network nodes may have a connection relationship with each other by simulating a synaptic activity of a neuron through which a neuron sends and receives a signal through a synapse. In the AI learning model, a plurality of network nodes can exchange data according to a convolutional connection relationship while being located in layers of different depths. The artificial intelligence learning model may be, for example, an artificial neural network model, a convolutional neural network model, or the like. As an embodiment, the AI learning model may be machine-learned according to a method such as supervised learning, unsupervised learning, reinforcement learning, or the like. Machine learning algorithms for performing machine learning include decision trees, Bayesian networks, support vector machines, artificial neural networks, and Ada-boost. , Perceptron, Genetic Programming, Clustering, etc. may be used.

Among them, CNN is a type of multilayer perceptrons designed to use minimal preprocessing. CNN consists of one or several convolutional layers and general artificial neural network layers on top of it, and additionally utilizes weights and pooling layers. Thanks to this structure, CNN can fully utilize the input data of the two-dimensional structure. Compared with other deep learning structures, CNN shows good performance in both video and audio fields. CNNs can also be trained through standard back-passing. CNNs are easier to train than other feed-forward neural network techniques and have the advantage of using fewer parameters.

Convolutional networks are neural networks that contain sets of nodes with bound parameters. The increasing size of available training data and the availability of computational power, coupled with advances in algorithms such as piecewise linear units and dropout training, have greatly improved many computer vision tasks. For huge data sets, such as those available for many tasks today, overfitting is not important, and increasing the size of the network improves test accuracy. Optimal use of computing resources becomes a limiting factor. To this end, a distributed, scalable implementation of deep neural networks may be used.

2 is a diagram for explaining a server according to an embodiment.

As shown in FIG. 2 , server 120 may include one or more processors 122 , one or more memories 124 and/or transceivers 126 . As an embodiment, at least one of these components of the server 120 may be omitted, or another component may be added to the server 120 . Additionally or alternatively, some components may be integrated and implemented, or may be implemented as a singular or a plurality of entities. At least some of the components inside and outside the server 120 are connected to each other through a bus, general purpose input/output (GPIO), serial peripheral interface (SPI), or mobile industry processor interface (MIPI), etc. Data and/or signals may be exchanged.

The one or more processors 122 may control at least one component of the server 120 connected to the processor 122 by driving software (eg, an instruction, a program, etc.). In addition, the processor 122 may perform various operations, processing, data generation, processing, etc. related to the present invention. In addition, the processor 122 may load data or the like from, or store to, one or more memories 124 .

One or more processors 122, 　 through the transmitter 126, a plurality of user terminals (110-1, ..., 110-n) 　 any one of the user terminal 1 　 the user terminal 110-1, beauty shop reservation request from can receive According to an embodiment, the 　 beauty shop reservation request may include, but is not limited to, the user's real-time location information, movement route information, 　 service item information, and the like.

The one or more processors 122 may form a first list including location information of beauty shops that can be reserved. According to an embodiment, the processor 122 may form a first list including location information of beauty shops that can currently be reserved among the beauty shops subscribed to the AI-based beauty shop reservation platform service.

The one or more processors 122 rearrange the beauty shops included in the first list in the order closest to the user by using the location information of the beauty shops included in the first list and the user's real-time location information to create the revised first list. can be formed According to an embodiment, 　 server 120 includes location information (eg,   1 latitude and 1   longitude) of beauty shops included in the first   list and real-time location information of the user (eg,   2   latitude and 2nd longitude) to calculate the distance between the user's current location and the beauty shops included in the 1st list, and rearrange the beauty shops included in the 1st list in the order closest to the user using the calculated distance. Thus, the first revised list can be formed.

The one or more processors 122 may transmit the first revised list to the first user terminal. According to an embodiment, the processor 122 may transmit the formed first modified list to the first user terminal 110 - 1 through the transceiver 126 .

The one or more processors 122 may receive a selection reservation request for the first beauty shop among the beauty shops included in the first revised list from the 　 first 　 user terminal. According to an embodiment, the processor 122 may receive a selection reservation request for the first beauty shop among the beauty shops included in the first revised list from the first user terminal 110-1 through the transceiver 126. have.

The one or more processors 122 may calculate the time required for the user to arrive at the first beauty shop by using the real-time location information of the user. According to an embodiment, the processor 122 may calculate the distance between the first beauty shop and the user's current location using Equation 1, and the user's moving speed (for example, , 1 minute/100 m) to calculate the required time.

The one or more processors 122 may transmit a selection reservation request to the second user terminal used in the first beauty shop in consideration of the required time. According to an embodiment, the processor 122 transmits a selection reservation request together with the time required for the user to arrive at the first beauty shop to the second user terminal 110-n through the transceiver 126 to transmit the first The beauty shop can prepare in advance so that the service can be provided according to the arrival time of the user.

The one or more processors 122 may receive a reservation completion guide from the second user terminal. According to an embodiment, the processor 122 may receive a reservation completion notification from the second user terminal 110-n through the transceiver 126 .

The one or more processors 122 may form shortest path information for arriving at the first beauty shop from the user's current location. According to an embodiment, the processor 122 may form the shortest path information for arriving at the first beauty shop from the user's current location by using the real-time location information of the user.

The one or more processors 122 may transmit a reservation completion guide and shortest route information to the first user terminal. According to an embodiment, the processor 122 is the first user terminal 110-1 through the transceiver N, and the reservation completion guide received from the second user terminal 110-n and the shortest formed using the map application. Route information can be transmitted.

The one or more memories 124 may store various data. Data stored in the memory 124 is data acquired, processed, or used by at least one component of the server 120, and may include software (eg, commands, programs, etc.). Memory 124 may include volatile and/or non-volatile memory. In the present invention, 　commands or programs are software stored in the memory 124, and various functions are applied so that the operating system, applications and/or applications for controlling the resources of the server 120 can utilize the resources of the server 120. It may include middleware provided to .

The one or more memories 124 include the above-described first 　 user terminal 110-1 received from the beauty shop reservation request and selection reservation request, 　 second 　 information received from the user terminal 110-n, 　 server 120 It is possible to store the first list formed in 　, the first modified list, 　 shortest path information, and the like. Also, the one or more memories 124 may store instructions that, when executed by the one or more processors 122, cause the one or more processors 122 to perform an operation.

As an embodiment, the server 120 may further include a transceiver 126 . The transceiver 126 may perform wireless or wired communication between the multiple user terminals 110-1, ..., 110-n, the server 120, the database 130, and/or other devices. For example, the transmitter 126 is an enhanced Mobile Broadband (eMBB), Ultra Reliable Low-Latency Communications (URLLC), Massive Machine Type Communications (MMTC), long-term evolution (LTE), LTE Advance (LTE-A), UMTS (Universal Mobile Telecommunications System), GSM (Global System for Mobile communications), CDMA (code division multiple access), WCDMA (wideband CDMA), WiBro (Wireless Broadband), WiFi (wireless fidelity), 　Bluetooth, NFC ( Near field communication), GPS (Global Positioning System) 　 or GNSS (global navigation satellite system) 　 can perform wireless communication according to the method. For example, the transmitter 126 may perform wired communication according to a method such as 　USB (universal serial bus), HDMI (high definition multimedia interface), RS-232 (recommended standard232) or POTS (plain old telephone service). have.

In one embodiment, one or more processors 122 control the transceiver 126 to obtain information from a plurality of user terminals 110-1, ..., 110-n, the server 120 and the database 130. have. Information obtained from a plurality of user terminals 110 - 1 , ..., 110 -n, server 120 , and database 130 may be stored in one or more memories 124 .

As an embodiment, the server 120 may be a device of various types. For example, the server 120 may be a portable communication device, a computer device, or a device according to a combination of one or more of the above devices. The server 120 of the present invention is not limited to the above-described devices.

Various embodiments of the server 120 according to the present invention may be combined with each other. Each embodiment may be combined according to the number of cases, and the embodiment of the server 120 made in combination also falls within the scope of the present invention. In addition, the above-described internal/external components of the server 120 according to the present invention may be added, changed, replaced, or deleted according to an embodiment. In addition, the above-described internal/external components of the server 120 may be implemented as hardware components.

3 is a diagram for explaining learning of a neural network according to an embodiment.

As shown in Fig. 3, the learning apparatus may train the neural network 123 to itemize the review responses received from the plurality of user terminals 110-1, ... In addition, the learning apparatus may move the user The neural network 123 may be trained in order to extract the user's stay history from the route information, according to an embodiment, but the learning apparatus may be a separate entity different from the server 120, but is not limited thereto.

The neural network 123 includes an input layer 121 to which training samples are input and an output layer 125 to output training outputs, and may be learned based on a difference between the training outputs and labels. Here, the labels may be defined based on items corresponding to the review response, and may be defined based on the user's stay history corresponding to the moving route information. The neural network 123 is connected to a group of a plurality of nodes, and is defined by weights between the connected nodes and an activation function that activates the nodes.

The learning apparatus may train the neural network 123 using a Gradient Decent (GD) technique or a Stochastic Gradient Descent (SGD) technique. The learning apparatus may use a loss function designed by the outputs and labels of the neural network.

The learning apparatus may calculate the training error using a predefined loss function. The loss function may be predefined with labels, outputs and parameters as input variables, where the parameters may be set by weights in the neural network 123 . For example, the loss function may be designed in a Mean Square Error (MSE) form, an entropy form, or the like, and various techniques or methods may be employed in an embodiment in which the loss function is designed.

The learning apparatus may find weights affecting the training error by using a backpropagation technique. Here, the weights are relationships between nodes in the neural network 123 . The learning apparatus may use the SGD technique using labels and outputs to optimize the weights found through the backpropagation technique. For example, the learning apparatus may update the weights of the loss function defined based on the labels, outputs, and weights using the SGD technique.

According to an embodiment, the learning apparatus extracts first objects from the review response, obtains first labels that are items corresponding to the first objects, and applies the first objects as a first neural network to the first object The first training outputs may be generated, and the first neural network may be trained based on the first training outputs and the first labels.

The learning apparatus extracts second objects from the movement path information, obtains second labels that are user residence details corresponding to the second objects, and applies the second objects to the second neural network to correspond to the second objects The second training outputs may be generated, and the second neural network may be trained based on the second training outputs and the second labels.

According to an embodiment, the learning apparatus may generate the first training feature vectors based on constituent features, location features, and pattern features of the review response. Various methods may be employed for extracting the feature.

According to an embodiment, the learning apparatus may generate the second training feature vectors based on constituent features, length features, and pattern features of the movement path information. Various methods may be employed for extracting the feature.

According to an embodiment, the learning apparatus may obtain training outputs by applying the first training feature vectors to the neural network 123 . The learning apparatus may train the review item extraction algorithm of the neural network 123 based on the training outputs and the first labels. The learning apparatus may learn the review item extraction algorithm of the neural network 123 by calculating the training errors corresponding to the training outputs, and optimizing the connection relationship of nodes in the neural network 123 to minimize the training errors. . The server 120 may extract items from the review response using the first neural network that has been trained. For example, the extracted items may include, but is not limited to, friendliness, store cleanliness, service satisfaction, and the like.

According to an embodiment, the learning apparatus may obtain training outputs by applying the second training feature vectors to the neural network 123 . The learning apparatus may train the user's stay history acquisition algorithm of the neural network 123 based on the training outputs and the second labels. The learning apparatus calculates training errors corresponding to the training outputs, and optimizes the connection relationship of nodes in the neural network 123 to minimize the training errors to learn the user stay history acquisition algorithm of the neural network 123. have. The server 120 may acquire the user's stay history from the movement route information by using the second neural network on which the learning has been completed.

4 is a flowchart of a method of providing an AI-based beauty shop reservation platform service according to an embodiment.

Although process steps, method steps, algorithms, etc. are described in a sequential order in the flowchart of FIG. 4 , such processes, methods, and algorithms may be configured to operate in any suitable order. In other words, the steps of the processes, methods, and algorithms described in various embodiments of the invention need not be performed in the order described herein. Also, although some steps are described as being performed asynchronously, in other embodiments some of these steps may be performed concurrently. Further, the exemplification of a process by description in the drawings does not imply that the exemplified process excludes other changes and modifications thereto, and that the exemplified process or any of its steps may be used in any of the various embodiments of the present invention. It is not meant to be essential to one or more, nor does it imply that the illustrated process is preferred.

As shown in FIG. 4 , in step S410 , a beauty shop reservation request is received. For example, referring to FIGS. 1 to 3 , the server 120 of the artificial intelligence-based beauty shop reservation platform service providing system 100 is a user who wants to use a beauty shop among a plurality of user terminals 110-1, ... A beauty shop reservation request can be received from the first user terminal (eg, 110-1) used by the may include, but is not limited to.

In step S420, a first list is formed. For example, referring to FIGS. 1 to 3 , the server 120 of the AI-based beauty shop reservation platform service providing system 100 is currently reserved among the beauty shops that have subscribed to the AI-based beauty shop reservation platform service. A first 　 list including location information of possible beauty shops can be formed.

In step S430, a modified first list is formed. For example, referring to FIGS. 1 to 3 , the server 120 of the artificial intelligence-based beauty shop reservation platform service providing system 100 provides the location information of the beauty shops included in the first 　 list and the real-time location information of the user. By using this, the beauty shops included in the first list can be rearranged in the order closest to the user to form the first revised list. According to an embodiment, 　 server 120 includes location information (eg,   1 latitude and 1   longitude) of beauty shops included in the first   list and real-time location information of the user (eg,   2   latitude and 2nd longitude) to calculate the distance between the user's current location and the beauty shops included in the 1st list, and rearrange the beauty shops included in the 1st list in the order closest to the user using the calculated distance. Thus, the first revised list can be formed.

In step S440, the first modified list is transmitted. For example, referring to FIGS. 1 to 3 , the server 120 of the artificial intelligence-based beauty shop reservation platform service providing system 100 sends the modified first list formed in step S430 to the first user through the network N. It can be transmitted to the terminal 110-1.

In step S450, a selection reservation request is received. For example, referring to FIGS. 1 to 3 , the server 120 of the artificial intelligence-based beauty shop reservation platform service providing system 100 is a beauty included in the first list modified from the first user terminal 110-1. A selection reservation request for the first beauty shop among the shops may be received. According to an embodiment, the server 120 may receive a selection reservation request for the first beauty shop among the beauty shops included in the first revised list from the first user terminal 110-1 through the network N. have.

In step S460, the required time is calculated. For example, referring to FIGS. 1 to 3 , the server 120 of the artificial intelligence-based beauty shop reservation platform service providing system 100 uses real-time location information of the user to take the user to arrive at the first beauty shop. The required time can be calculated. According to an embodiment, the server 120 may calculate the distance between the first beauty shop and the user's current location using Equation 1, and the user's moving speed (for example, , 1 minute/100 m) to calculate the required time.

In step S470, a selection reservation request is transmitted. For example, referring to FIGS. 1 to 3 , the server 120 of the artificial intelligence-based beauty shop reservation platform service providing system 100 considers the required time and the second user terminal 110 used in the first beauty shop. -n) to send a selective reservation request. According to an exemplary embodiment, the server 120 transmits a selection reservation request along with the time required for the user to arrive at the first beauty shop to the second user terminal 110-n through the network N to the first The beauty shop can prepare in advance so that the service can be provided according to the arrival time of the user.

In step S480, a reservation completion guide is received. For example, referring to FIGS. 1 to 3 , the server 120 of the artificial intelligence-based beauty shop reservation platform service providing system 100 completes the reservation from the second 　 user terminal 110-n through the network N You can receive guidance.

In step S490, shortest path information is formed. For example, referring to FIGS. 1 to 3 , the server 120 of the artificial intelligence-based beauty shop reservation platform service providing system 100 forms the shortest path information for arriving at the first beauty shop from the user's current location. can do. According to an embodiment, the server 120 may form the shortest path information for arriving at the first beauty shop from the user's current location by using the real-time location information of the user.

In step S470, the shortest path information is transmitted. For example, referring to FIGS. 1 to 3 , the server 120 of the artificial intelligence-based beauty shop reservation platform service providing system 100 completes the reservation through the network N to the first user terminal 110-1. Information on the shortest route formed using the guidance and map application can be transmitted.

5 is an exemplary diagram of a configuration of an apparatus according to an embodiment.

The device 501 according to one embodiment includes a processor 502 and a memory 503 . The device 501 according to an embodiment may be the above-described server or terminal. The processor may include at least one of the devices described above with reference to FIGS. 1 to 4 , or may perform at least one method described above with reference to FIGS. 1 to 4 . The memory 503 may store information related to the above-described method or a program in which the above-described method is implemented. The memory 503 may be a volatile memory or a non-volatile memory.

The processor 502 may execute a program and control the device 501 . Codes of programs executed by the processor 502 may be stored in the memory 503 . The device 501 may be connected to an external device (eg, a personal computer or a network) through an input/output device (not shown) and exchange data.

The embodiments described above may be implemented by a hardware component, a software component, and/or a combination of a hardware component and a software component. For example, the apparatus, methods, and components described in the embodiments may include, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable gate (FPGA) array), a programmable logic unit (PLU), a microprocessor, or any other device capable of executing and responding to instructions, may be implemented using one or more general purpose or special purpose computers. The processing device may execute an operating system (OS) and one or more software applications running on the operating system. A processing device may also access, store, manipulate, process, and generate data in response to execution of the software. For convenience of understanding, although one processing device is sometimes described as being used, one of ordinary skill in the art will recognize that the processing device includes a plurality of processing elements and/or a plurality of types of processing elements. It can be seen that can include For example, the processing device may include a plurality of processors or one processor and one controller. Other processing configurations are also possible, such as parallel processors.

The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded in a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, etc. alone or in combination. The program instructions recorded on the medium may be specially designed and configured for the embodiment, or may be known and available to those skilled in the art of computer software. Examples of the computer-readable recording medium include magnetic media such as hard disks, floppy disks and magnetic tapes, optical media such as CD-ROMs and DVDs, and magnetic such as floppy disks. - includes magneto-optical media, and hardware devices specially configured to store and execute program instructions, such as ROM, RAM, flash memory, and the like. Examples of program instructions include not only machine language codes such as those generated by a compiler, but also high-level language codes that can be executed by a computer using an interpreter or the like. The hardware devices described above may be configured to operate as one or more software modules to perform the operations of the embodiments, and vice versa.

Software may comprise a computer program, code, instructions, or a combination of one or more thereof, which configures a processing device to operate as desired or is independently or collectively processed You can command the device. The software and/or data may be any kind of machine, component, physical device, virtual equipment, computer storage medium or apparatus, to be interpreted by or to provide instructions or data to the processing device. , or may be permanently or temporarily embody in a transmitted signal wave. The software may be distributed over networked computer systems and stored or executed in a distributed manner. Software and data may be stored in one or more computer-readable recording media.

As described above, although the embodiments have been described with reference to the limited drawings, those skilled in the art may apply various technical modifications and variations based on the above. For example, the described techniques are performed in an order different from the described method, and/or the described components of the system, structure, apparatus, circuit, etc. are combined or combined in a different form than the described method, or other components Or substituted or substituted by equivalents may achieve an appropriate result.

Therefore, other implementations, other embodiments, and equivalents to the claims are also within the scope of the following claims.

Claims (3)

Receiving a beauty shop reservation request from the first user terminal, wherein the beauty shop reservation request includes real-time location information of the user;
forming a first list including location information of beauty shops that can be reserved;
forming a modified first list by rearranging the beauty shops included in the first list in the order closest to the user by using the location information of the beauty shops included in the first list and the real-time location information of the user;
transmitting the modified first list to the first user terminal;
receiving a selection reservation request for a first beauty shop among beauty shops included in the first modified list from the first user terminal;
calculating a time required for the user to arrive at the first beauty shop by using the user's real-time location information;
transmitting the selection reservation request to a second user terminal used in the first beauty shop in consideration of the required time;
receiving a reservation completion guide from the second user terminal;
forming shortest route information for arriving at the first beauty shop from the user's current location;
transmitting the reservation completion guide and the shortest route information to the first user terminal;
calculating an expected time for the user to arrive at the first beauty shop by using the real-time location information of the first user terminal;
transmitting the estimated time to the second user terminal;
forming a user arrival notification signal when the user is located within a predetermined distance from the first beauty shop using real-time location information of the first user terminal;
transmitting the user arrival notification signal to the second user terminal;
using the real-time location information of the first user terminal to form a user review request when the user deviates from the first beauty shop by a predetermined distance or more and transmitting the request to the first user terminal;
receiving a review response to the user review request from the first user terminal;
transmitting a preset point to the first user terminal in response to receiving the review response; and
classifying and storing the review response by item;
The beauty shop reservation request is,
Further comprising the movement path information of the user,
receiving and storing advertisement information of multiple beauty shops;
extracting a predetermined number of second beauty shop information located within a predetermined distance from the movement path of the user by using the movement path information;
extracting a third beauty shop matching the service item information extracted from the selection reservation request from among the second beauty shops; and
Further comprising the step of transmitting the advertisement information of the third beauty shop to the first user terminal,
How to provide AI-based beauty shop reservation platform service. delete According to claim 1,
When the user is located within a predetermined distance from the first beauty shop using real-time location information of the first user terminal, a coupon list including information on coupons usable in the first beauty shop is transmitted to the first user terminal to do;
performing a first payment of the estimated cost of using the first beauty shop by applying a first coupon having the highest discount rate among the coupons in the coupon list;
receiving service information provided by the user from the first beauty shop from the second user terminal when the user deviates from the first beauty shop by a predetermined distance or more using real-time location information of the first user terminal;
forming a second payment history according to the use of the first beauty shop using the service information and the first coupon and transmitting it to the first user terminal;
receiving an approval request for the second payment details from the first user terminal; and
performing a second payment by transmitting the second payment details to a card company server
further comprising,
How to provide AI-based beauty shop reservation platform service.

Images