KR102463860B1 - Method for providing couple matching service using saju-myeongri based on artificial intelligence - Google Patents

Abstract

Embodiments provide a method for providing a couple matching service using four pillars and marital compatibility based on artificial intelligence. The method for providing a couple matching service using four pillars and marital compatibility based on artificial intelligence may comprise the actions of: receiving, by a user information management module, user personal information from a user terminal, wherein the user personal information includes first user personal information including one or more pieces of element information, respectively, corresponding to one or more of a user's gender, height, weight, age, occupation, and residential district, and second user personal information including information corresponding to the time of birth; providing, by the user information management module, a plurality of pieces of subscription question information to the user terminal, and receiving a plurality of pieces of user selection information, respectively, corresponding to the plurality of pieces of subscription question information from the user terminal; outputting, by a matching information generation module, a first vector based on first element information included in the first user personal information and user selection information corresponding to the first element information among the plurality of pieces of user selection information; outputting, by a four pillars analysis module, a second vector based on the second user personal information; generating, by the matching information generation module, user matching information based on the first vector and the second vector; storing, by a database, user profile information generated based on the user personal information and the plurality of pieces of user selection information; and selecting one of a plurality of pieces of user profile information stored in the database based on the user matching information and option information and providing the selected one to the user terminal.

Description

A method of providing a couple matching service using artificial intelligence-based four weeks and compatibility

Embodiments of the present invention relate to a method of providing a couple matching service, and more specifically, providing a better couple matching service based on matching information generated by giving different weights to stock ownership and compatibility information and user preference item information it's about how to

In addition, the present invention is to graft artificial intelligence (artificial intelligence) technology, which is the fourth industrial technology, when matching couples using four weeks and compatibility.

Recently, with the development of communication technology, various encounters in an online environment have increased significantly. In line with this trend, various blind date apps or platforms have appeared in the online environment where you can meet the opposite sex with your preferred conditions. However, existing blind date apps apply simple methods and algorithms such as recommending other users with similar conditions according to the location or personal information entered by the user, rather than a customized partner recommendation method reflecting the user's individual characteristics in couple matching. just stop doing Accordingly, there is an increasing need for a blind date app that collects more diverse user information and recommends a suitable counterpart to the user by comprehensively analyzing the collected user information.

The background art described above is possessed or acquired by the inventor in the process of deriving the disclosure of the present application, and cannot necessarily be said to be a known technology disclosed to the general public prior to the present application.

Embodiments provide a method of providing a couple matching service using artificial intelligence-based four weeks and compatibility.

The technical problems to be achieved in the embodiments are not limited to those mentioned above, and other technical problems not mentioned may be considered by those of ordinary skill in the art from various embodiments to be described below. can

A method of providing a couple matching service using artificial intelligence-based four weeks and compatibility according to some embodiments of the present invention includes, by a user information management module, receiving user personal information from a user terminal; - The user personal information includes first user personal information including one or more element information corresponding to one or more of the user's gender, height, weight, age, occupation, and residence area, and information corresponding to birth Includes second user personal information - by the user information management module, provide a plurality of subscription question information to the user terminal, and provide a plurality of user selection information corresponding to each of the plurality of subscription question information from the user terminal receiving action; outputting, by the matching information generating module, a first vector based on first element information included in the first user personal information and user selection information corresponding to the first element information among the plurality of user selection information ; outputting, by the stock week analysis module, a second vector based on the second user personal information; generating, by the matching information generating module, user matching information based on the first vector and the second vector; storing, in a database, user profile information generated based on the user personal information and the plurality of user selection information; and selecting any one of a plurality of user profile information stored in the database based on the user matching information and the selection information and providing the selected one to the user terminal.

The first user selection information corresponding to the first element information among the plurality of user selection information includes a first user selection section for the first subscription question information corresponding to the first user selection information, and the matching information The operation of outputting the first vector by the generating module comprises, by the matching information generating module, response information to the first subscription question information by using a matching model function based on the first user selection section outputting a first selection element and a second selection element including a weight for the first selection element; and generating the first vector for the first subscription question information based on the first selection element and the second selection element.

[Equation]

The matching information generating module generates the first vector by using the <Equation>, where c is the first selection element, P(c) is the second selection element, and c_l is the minimum value of the first user-selected section, c_h is the maximum value of the first user-selected section, c_m is the median value of the first user-selected section, w_i is the first correction coefficient, p_i is the second correction coefficient. have.

The step of outputting the second vector by the key week analysis module may include, by the key week analysis module, extracting, by the key week analysis module, information corresponding to the time of birth included in the second user personal information; and generating the second vector based on the extracted zenith and support.

The plurality of user profile information stored in the database includes first user profile information, and by the matching information generating module, the first vector and a first counterpart corresponding to the first vector among the first user profile information The method may further include generating a first score based on the similarity of the vectors.

[Equation]

The matching information generating module outputs the degree of similarity between the first vector and the first relative vector based on the <Equation>, where KS is the similarity and v_k is the first vector , rv_ may mean the first relative vector, and k may mean a natural number for identifying the vector.

generating, by the matching information generation module, a first correction score using a matching information correction model based on the first score; further comprising, wherein the matching information correction model includes an input layer, one or more hidden layers and an output layer, wherein a plurality of training data relating to the first score is input to the input layer of the matching information correction model to pass through the one or more hidden layers and an output layer to output an output vector, and the output vector is It is input to a loss function layer connected to the output layer, and the loss function layer outputs a loss value using a loss function that compares the output vector with a correct vector for each training data, and a parameter of the matching information correction model can be learned in a direction in which the loss value becomes smaller.

According to embodiments, it is possible to provide a better couple matching service based on matching information generated by giving different weights to the key stock, compatibility information, and user preference item information.

Effects obtainable from the embodiments are not limited to the effects mentioned above, and other effects not mentioned are clearly derived and understood by those of ordinary skill in the art based on the following detailed description. can be

BRIEF DESCRIPTION OF THE DRAWINGS The accompanying drawings, which are included as part of the detailed description to aid understanding of the embodiments, provide various embodiments and, together with the detailed description, explain technical features of the various embodiments.
1 is a diagram illustrating a configuration of an electronic device according to an embodiment of the present invention.
2 is a diagram showing the configuration of a program according to an embodiment of the present invention.
3 is a diagram schematically illustrating a couple matching system according to an embodiment of the present invention.
FIG. 4 is a block diagram for explaining the structure of the server of FIG. 3 .
5 is a view for explaining the heavens.
6 is a view for explaining the support.
7 is a flowchart illustrating a couple matching operation of a server according to an embodiment of the present invention.

The following embodiments combine elements and features of the embodiments in a predetermined form. Each component or feature may be considered optional unless explicitly stated otherwise. Each component or feature may be implemented in a form that is not combined with other components or features. In addition, various embodiments may be configured by combining some components and/or features. The order of operations described in various embodiments may be changed. Some features or features of one embodiment may be included in another embodiment, or may be replaced with corresponding features or features of another embodiment.

In the description of the drawings, procedures or steps that may obscure the gist of various embodiments are not described, and procedures or steps that can be understood at the level of those of ordinary skill in the art are also not described. did.

Throughout the specification, when a part is said to "comprising or including" a certain component, it does not exclude other components unless otherwise stated, meaning that other components may be further included. do. In addition, terms such as "... unit", "... group", and "module" described in the specification mean a unit that processes at least one function or operation, which is hardware or software or a combination of hardware and software. can be implemented as Also, "a or an", "one", "the" and like related terms are used herein in the context of describing various embodiments (especially in the context of the claims that follow). Unless otherwise indicated or clearly contradicted by context, it may be used in a sense including both the singular and the plural.

Hereinafter, embodiments according to various embodiments will be described in detail with reference to the accompanying drawings. DETAILED DESCRIPTION The detailed description set forth below in conjunction with the appended drawings is intended to describe exemplary embodiments of various embodiments, and is not intended to represent the only embodiments.

In addition, specific terms used in various embodiments are provided to help the understanding of various embodiments, and the use of these specific terms may be changed to other forms without departing from the technical spirit of various embodiments. .

1 is a diagram illustrating a configuration of an electronic device according to an embodiment of the present invention.

1 is a block diagram of an electronic device 101 in a network environment 100, according to various embodiments. Referring to FIG. 1 , in a network environment 100 , an electronic device 101 communicates with an electronic device 102 through a first network 198 (eg, a short-range wireless communication network) or a second network 199 . It may communicate with at least one of the electronic device 104 and the server 108 through (eg, a long-distance wireless communication network). According to an embodiment, the electronic device 101 may communicate with the electronic device 104 through the server 108 . According to an embodiment, the electronic device 101 includes a processor 120 , a memory 130 , an input module 150 , a sound output module 155 , a display module 160 , an audio module 170 , and a sensor module ( 176), interface 177, connection terminal 178, haptic module 179, camera module 180, power management module 188, battery 189, communication module 190, subscriber identification module 196 , or an antenna module 197 . In some embodiments, at least one of these components (eg, the connection terminal 178 ) may be omitted or one or more other components may be added to the electronic device 101 . In some embodiments, some of these components (eg, sensor module 176 , camera module 180 , or antenna module 197 ) are integrated into one component (eg, display module 160 ). can be The electronic device 101 may also be referred to as a client, a terminal, or a peer.

The processor 120, for example, executes software (eg, a program 140) to execute at least one other component (eg, a hardware or software component) of the electronic device 101 connected to the processor 120. It can control and perform various data processing or operations. According to one embodiment, as at least part of data processing or operation, the processor 120 converts commands or data received from other components (eg, the sensor module 176 or the communication module 190 ) to the volatile memory 132 . may be stored in , process commands or data stored in the volatile memory 132 , and store the result data in the non-volatile memory 134 . According to an embodiment, the processor 120 is the main processor 121 (eg, a central processing unit or an application processor) or a secondary processor 123 (eg, a graphic processing unit, a neural network processing unit (eg, a graphic processing unit, a neural network processing unit) a neural processing unit (NPU), an image signal processor, a sensor hub processor, or a communication processor). For example, when the electronic device 101 includes the main processor 121 and the sub-processor 123 , the sub-processor 123 uses less power than the main processor 121 or is set to be specialized for a specified function. can The auxiliary processor 123 may be implemented separately from or as a part of the main processor 121 .

The secondary processor 123 may, for example, act on behalf of the main processor 121 while the main processor 121 is in an inactive (eg, sleep) state, or when the main processor 121 is active (eg, executing an application). ), together with the main processor 121, at least one of the components of the electronic device 101 (eg, the display module 160, the sensor module 176, or the communication module 190) It is possible to control at least some of the related functions or states. According to an embodiment, the coprocessor 123 (eg, an image signal processor or a communication processor) may be implemented as part of another functionally related component (eg, the camera module 180 or the communication module 190 ). have. According to an embodiment, the auxiliary processor 123 (eg, a neural network processing device) may include a hardware structure specialized for processing an artificial intelligence model. Artificial intelligence models can be created through machine learning. Such learning may be performed, for example, in the electronic device 101 itself on which the artificial intelligence model is performed, or may be performed through a separate server (eg, the server 108). The learning algorithm may include, for example, supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning, but in the above example not limited The artificial intelligence model may include a plurality of artificial neural network layers. Artificial neural networks include deep neural networks (DNNs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), restricted boltzmann machines (RBMs), deep belief networks (DBNs), bidirectional recurrent deep neural networks (BRDNNs), It may be one of deep Q-networks or a combination of two or more of the above, but is not limited to the above example. The artificial intelligence model may include, in addition to, or alternatively, a software structure in addition to the hardware structure.

The memory 130 may store various data used by at least one component (eg, the processor 120 or the sensor module 176 ) of the electronic device 101 . The data may include, for example, input data or output data for software (eg, the program 140 ) and instructions related thereto. The memory 130 may include a volatile memory 132 or a non-volatile memory 134 .

The program 140 may be stored as software in the memory 130 , and may include, for example, an operating system 142 , middleware 144 , or an application 146 .

The input module 150 may receive a command or data to be used by a component (eg, the processor 120 ) of the electronic device 101 from the outside (eg, a user) of the electronic device 101 . The input module 150 may include, for example, a microphone, a mouse, a keyboard, a key (eg, a button), or a digital pen (eg, a stylus pen).

The sound output module 155 may output a sound signal to the outside of the electronic device 101 . The sound output module 155 may include, for example, a speaker or a receiver. The speaker can be used for general purposes such as multimedia playback or recording playback. The receiver can be used to receive incoming calls. According to one embodiment, the receiver may be implemented separately from or as part of the speaker.

The display module 160 may visually provide information to the outside (eg, a user) of the electronic device 101 . The display module 160 may include, for example, a control circuit for controlling a display, a hologram device, or a projector and a corresponding device. According to an embodiment, the display module 160 may include a touch sensor configured to sense a touch or a pressure sensor configured to measure the intensity of a force generated by the touch.

The audio module 170 may convert a sound into an electric signal or, conversely, convert an electric signal into a sound. According to an embodiment, the audio module 170 acquires a sound through the input module 150 , or an external electronic device (eg, a sound output module 155 ) connected directly or wirelessly with the electronic device 101 . The electronic device 102) (eg, a speaker or headphones) may output a sound.

The sensor module 176 detects an operating state (eg, power or temperature) of the electronic device 101 or an external environmental state (eg, a user state), and generates an electrical signal or data value corresponding to the sensed state. can do. According to an embodiment, the sensor module 176 may include, for example, a gesture sensor, a gyro sensor, a barometric pressure sensor, a magnetic sensor, an acceleration sensor, a grip sensor, a proximity sensor, a color sensor, an IR (infrared) sensor, a biometric sensor, It may include a temperature sensor, a humidity sensor, or an illuminance sensor.

The interface 177 may support one or more specified protocols that may be used by the electronic device 101 to directly or wirelessly connect with an external electronic device (eg, the electronic device 102 ). According to an embodiment, the interface 177 may include, for example, a high definition multimedia interface (HDMI), a universal serial bus (USB) interface, an SD card interface, or an audio interface.

The connection terminal 178 may include a connector through which the electronic device 101 can be physically connected to an external electronic device (eg, the electronic device 102 ). According to an embodiment, the connection terminal 178 may include, for example, an HDMI connector, a USB connector, an SD card connector, or an audio connector (eg, a headphone connector).

The haptic module 179 may convert an electrical signal into a mechanical stimulus (eg, vibration or movement) or an electrical stimulus that the user can perceive through tactile or kinesthetic sense. According to an embodiment, the haptic module 179 may include, for example, a motor, a piezoelectric element, or an electrical stimulation device.

The camera module 180 may capture still images and moving images. According to an embodiment, the camera module 180 may include one or more lenses, image sensors, image signal processors, or flashes.

The power management module 188 may manage power supplied to the electronic device 101 . According to an embodiment, the power management module 188 may be implemented as, for example, at least a part of a power management integrated circuit (PMIC).

The battery 189 may supply power to at least one component of the electronic device 101 . According to one embodiment, battery 189 may include, for example, a non-rechargeable primary cell, a rechargeable secondary cell, or a fuel cell.

The communication module 190 is a direct (eg, wired) communication channel or a wireless communication channel between the electronic device 101 and an external electronic device (eg, the electronic device 102, the electronic device 104, or the server 108). It can support establishment and communication performance through the established communication channel. The communication module 190 may include one or more communication processors that operate independently of the processor 120 (eg, an application processor) and support direct (eg, wired) communication or wireless communication. According to one embodiment, the communication module 190 is a wireless communication module 192 (eg, a cellular communication module, a short-range communication module, or a global navigation satellite system (GNSS) communication module) or a wired communication module 194 (eg, : It may include a local area network (LAN) communication module, or a power line communication module). A corresponding communication module among these communication modules is a first network 198 (eg, a short-range communication network such as Bluetooth, wireless fidelity (WiFi) direct, or infrared data association (IrDA)) or a second network 199 (eg, legacy It may communicate with the external electronic device 104 through a cellular network, a 5G network, a next-generation communication network, the Internet, or a computer network (eg, a telecommunication network such as a LAN or a WAN). These various types of communication modules may be integrated into one component (eg, a single chip) or may be implemented as a plurality of components (eg, multiple chips) separate from each other. The wireless communication module 192 uses subscriber information (eg, International Mobile Subscriber Identifier (IMSI)) stored in the subscriber identification module 196 within a communication network such as the first network 198 or the second network 199 . The electronic device 101 may be identified or authenticated.

The wireless communication module 192 may support a 5G network after a 4G network and a next-generation communication technology, for example, a new radio access technology (NR). NR access technology includes high-speed transmission of high-capacity data (eMBB (enhanced mobile broadband)), minimization of terminal power and access to multiple terminals (mMTC (massive machine type communications)), or high reliability and low latency (URLLC (ultra-reliable and low-latency) -latency communications)). The wireless communication module 192 may support a high frequency band (eg, mmWave band) to achieve a high data rate, for example. The wireless communication module 192 uses various techniques for securing performance in a high-frequency band, for example, beamforming, massive multiple-input and multiple-output (MIMO), all-dimensional multiplexing. It may support technologies such as full dimensional MIMO (FD-MIMO), an array antenna, analog beam-forming, or a large scale antenna. The wireless communication module 192 may support various requirements defined in the electronic device 101 , an external electronic device (eg, the electronic device 104 ), or a network system (eg, the second network 199 ). According to an embodiment, the wireless communication module 192 may include a peak data rate (eg, 20 Gbps or more) for realizing eMBB, loss coverage (eg, 164 dB or less) for realizing mMTC, or U-plane latency for realizing URLLC ( Example: Downlink (DL) and uplink (UL) each 0.5 ms or less, or round trip 1 ms or less) can be supported.

The antenna module 197 may transmit or receive a signal or power to the outside (eg, an external electronic device). According to an embodiment, the antenna module 197 may include an antenna including a conductor formed on a substrate (eg, a PCB) or a radiator formed of a conductive pattern. According to an embodiment, the antenna module 197 may include a plurality of antennas (eg, an array antenna). In this case, at least one antenna suitable for a communication method used in a communication network such as the first network 198 or the second network 199 is connected from the plurality of antennas by, for example, the communication module 190 . can be selected. A signal or power may be transmitted or received between the communication module 190 and an external electronic device through the selected at least one antenna. According to some embodiments, other components (eg, a radio frequency integrated circuit (RFIC)) other than the radiator may be additionally formed as a part of the antenna module 197 .

According to various embodiments, the antenna module 197 may form a mmWave antenna module. According to one embodiment, the mmWave antenna module comprises a printed circuit board, an RFIC disposed on or adjacent to a first side (eg, bottom side) of the printed circuit board and capable of supporting a designated high frequency band (eg, mmWave band); and a plurality of antennas (eg, an array antenna) disposed on or adjacent to a second side (eg, top or side) of the printed circuit board and capable of transmitting or receiving signals of the designated high frequency band. can do.

At least some of the components are connected to each other through a communication method between peripheral devices (eg, a bus, general purpose input and output (GPIO), serial peripheral interface (SPI), or mobile industry processor interface (MIPI)) and a signal ( e.g. commands or data) can be exchanged with each other.

According to an embodiment, the command or data may be transmitted or received between the electronic device 101 and the external electronic device 104 through the server 108 connected to the second network 199 . Each of the external electronic devices 102 or 104 may be the same as or different from the electronic device 101 . According to an embodiment, all or a part of operations executed in the electronic device 101 may be executed in one or more external electronic devices 102 , 104 , or 108 . For example, when the electronic device 101 needs to perform a function or service automatically or in response to a request from a user or other device, the electronic device 101 may perform the function or service itself instead of executing the function or service itself. Alternatively or additionally, one or more external electronic devices may be requested to perform at least a part of the function or the service. One or more external electronic devices that have received the request may execute at least a part of the requested function or service, or an additional function or service related to the request, and transmit a result of the execution to the electronic device 101 . The electronic device 101 may process the result as it is or additionally and provide it as at least a part of a response to the request. For this purpose, for example, cloud computing, distributed computing, mobile edge computing (MEC), or client-server computing technology may be used. The electronic device 101 may provide an ultra-low latency service using, for example, distributed computing or mobile edge computing. In another embodiment, the external electronic device 104 may include an Internet of things (IoT) device. The server 108 may be an intelligent server using machine learning and/or neural networks. According to an embodiment, the external electronic device 104 or the server 108 may be included in the second network 199 . The electronic device 101 may be applied to an intelligent service (eg, smart home, smart city, smart car, or health care) based on 5G communication technology and IoT-related technology.

The server 108 is connected to the electronic device 101 and may provide a service to the connected electronic device 101 . In addition, the server 108 may store and manage various types of information of users who have joined as members by performing a membership registration procedure, and may provide various purchase and payment functions related to services. Also, the server 108 may share execution data of a service application executed in each of the plurality of electronic devices 101 in real time so that the service can be shared among users. The server 108 may have the same configuration as a typical web server (Web Server) or WAP server (WAP Server) in terms of hardware. However, in terms of software, it may include a program module that is implemented through any language such as C, C++, Java, Visual Basic, or Visual C and performs various functions. In addition, the server 108 is generally connected to an unspecified number of clients and/or other servers through an open computer network such as the Internet, receives a request to perform a task from a client or other server, and derives and provides the work result. It means a computer system and the computer software (server program) installed therefor. In addition, the server 108, in addition to the above-described server program, a series of application programs (Application Program) operating on the server 108 and in some cases, various databases (DB: Database, hereinafter " DB") should be understood as a broad concept including. Accordingly, the server 108 classifies, stores and manages member registration information, various information and data about the game in a DB, and this DB may be implemented inside or outside the server 108 . In addition, the server 108 uses a server program that is provided in various ways according to operating systems such as DOS, Windows, Linux, UNIX, and Macintosh in general server hardware. As a representative example, a website used in a Windows environment, Internet Information Server (IIS), and CERN, NCSA, APPACH, etc. used in a Unix environment may be used. In addition, the server 108 may cooperate with an authentication system and a payment system for user authentication of a service or a purchase payment related to a service.

The first network 198 and the second network 199 are a connection structure capable of exchanging information between respective nodes such as terminals and servers, or a network connecting the server 108 and the electronic devices 101 and 104 . (Network). The first network 198 and the second network 199 are Internet (Internet), LAN (Local Area Network), Wireless LAN (Wireless Local Area Network), WAN (Wide Area Network), PAN (Personal Area Network), 3G , 4G, LTE, 5G, Wi-Fi, and the like. The first network 198 and the second network 199 may be the closed first network 198 and the second network 199 such as a LAN or a WAN, but preferably an open type such as the Internet. The Internet is a TCP/IP protocol and several services existing in its upper layers, namely HTTP (HyperText Transfer Protocol), Telnet, FTP (File Transfer Protocol), DNS (Domain Name System), SMTP (Simple Mail Transfer Protocol), SNMP ( Simple Network Management Protocol), NFS (Network File Service), and NIS (Network Information Service) means a worldwide open computer first network 198 and second network 199 structure.

The database may have a general data structure implemented in a storage space (hard disk or memory) of a computer system using a database management program (DBMS). The database may have a data storage form in which data can be freely searched (extracted), deleted, edited, added, and the like. Database is a relational database management system (RDBMS) such as Oracle, Infomix, Sybase, DB2, or object-oriented database management such as Gemston, Orion, O2, etc. It can be implemented for the purpose of an embodiment of the present disclosure by using a system (OODBMS) and an XML-only database (XML Native Database) such as Excelon, Tamino, and Sekaiju, and its function It may have an appropriate field or elements to achieve .

2 is a diagram showing the configuration of a program according to an embodiment of the present invention.

2 is a block diagram 200 illustrating a program 140 in accordance with various embodiments. According to an embodiment, the program 140 executes an operating system 142 , middleware 144 , or an application 146 executable in the operating system 142 for controlling one or more resources of the electronic device 101 . may include Operating system 142 may include, for example, Android™, iOS™, Windows™, Symbian™, Tizen™, or Bada™. At least some of the programs 140 are, for example, preloaded into the electronic device 101 at the time of manufacture, or an external electronic device (eg, the electronic device 102 or 104 ), or a server (eg, the electronic device 102 or 104 ) when used by a user ( 108)) or may be updated. All or part of the program 140 may include a neural network.

The operating system 142 may control management (eg, allocation or retrieval) of one or more system resources (eg, a process, memory, or power) of the electronic device 101 . The operating system 142 may additionally or alternatively include other hardware devices of the electronic device 101 , for example, the input module 150 , the sound output module 155 , the display module 160 , and the audio module 170 . , sensor module 176 , interface 177 , haptic module 179 , camera module 180 , power management module 188 , battery 189 , communication module 190 , subscriber identification module 196 , or It may include one or more driver programs for driving the antenna module 197 .

The middleware 144 may provide various functions to the application 146 so that functions or information provided from one or more resources of the electronic device 101 may be used by the application 146 . The middleware 144 includes, for example, an application manager 201 , a window manager 203 , a multimedia manager 205 , a resource manager 207 , a power manager 209 , a database manager 211 , and a package manager 213 . ), a connectivity manager 215 , a notification manager 217 , a location manager 219 , a graphics manager 221 , a security manager 223 , a call manager 225 , or a voice recognition manager 227 . can

The application manager 201 may manage the life cycle of the application 146 , for example. The window manager 203 may manage one or more GUI resources used in the screen, for example. The multimedia manager 205, for example, identifies one or more formats required for playback of media files, and encodes or decodes a corresponding media file among the media files using a codec suitable for the selected format. can be done The resource manager 207 may manage the space of the source code of the application 146 or the memory of the memory 130 , for example. The power manager 209 may, for example, manage the capacity, temperature, or power of the battery 189 , and determine or provide related information required for the operation of the electronic device 101 by using the corresponding information. . According to an embodiment, the power manager 209 may interwork with a basic input/output system (BIOS) (not shown) of the electronic device 101 .

The database manager 211 may create, retrieve, or change a database to be used by the application 146 , for example. The package manager 213 may manage installation or update of an application distributed in the form of a package file, for example. The connectivity manager 215 may manage, for example, a wireless connection or a direct connection between the electronic device 101 and an external electronic device. The notification manager 217 may provide, for example, a function for notifying the user of the occurrence of a specified event (eg, an incoming call, a message, or an alarm). The location manager 219 may manage location information of the electronic device 101 , for example. The graphic manager 221 may manage, for example, one or more graphic effects to be provided to a user or a user interface related thereto.

Security manager 223 may provide, for example, system security or user authentication. The telephony manager 225 may manage, for example, a voice call function or a video call function provided by the electronic device 101 . The voice recognition manager 227, for example, transmits the user's voice data to the server 108, and based at least in part on the voice data, a command corresponding to a function to be performed in the electronic device 101; Alternatively, the converted text data may be received from the server 108 based at least in part on the voice data. According to an embodiment, the middleware 244 may dynamically delete some existing components or add new components. According to an embodiment, at least a portion of the middleware 144 may be included as a part of the operating system 142 or implemented as software separate from the operating system 142 .

Application 146 includes, for example, home 251 , dialer 253 , SMS/MMS 255 , instant message (IM) 257 , browser 259 , camera 261 , alarm 263 . , contacts 265, voice recognition 267, email 269, calendar 271, media player 273, album 275, watch 277, health 279 (such as exercise or blood sugar) measuring biometric information), or environmental information 281 (eg, measuring atmospheric pressure, humidity, or temperature information). According to an embodiment, the application 146 may further include an information exchange application (not shown) capable of supporting information exchange between the electronic device 101 and an external electronic device. The information exchange application may include, for example, a notification relay application configured to transmit specified information (eg, call, message, or alarm) to an external electronic device, or a device management application configured to manage the external electronic device. have. The notification relay application, for example, transmits notification information corresponding to a specified event (eg, mail reception) generated in another application (eg, the email application 269 ) of the electronic device 101 to the external electronic device. can Additionally or alternatively, the notification relay application may receive notification information from the external electronic device and provide it to the user of the electronic device 101 .

The device management application is, for example, a power source (eg, turn-on or turn-off) of an external electronic device that communicates with the electronic device 101 or some components thereof (eg, a display module or a camera module of the external electronic device). ) or a function (eg brightness, resolution, or focus). The device management application may additionally or alternatively support installation, deletion, or update of an application operating in an external electronic device.

Next, a couple matching system according to an embodiment of the present invention will be described.

3 is a diagram schematically illustrating a couple matching system according to an embodiment of the present invention.

The couple matching system may provide a couple matching program to a plurality of user terminals subscribed to the couple matching system. The user terminal may store the couple matching program and execute the couple matching program to perform the registration procedure of the couple matching system. To this end, referring to FIG. 3 , the couple matching system may include a server 310 that exchanges data with a plurality of user terminals through a network 340 . The plurality of user terminals may include a first user terminal 320 and a second user terminal 330 . That is, the server 310 may exchange data with the first user terminal 320 and the second user terminal 330 through the network 340 . However, this is an example, and the plurality of user terminals according to an embodiment of the present invention may include three or more user terminals in addition to the first user terminal 320 and the second user terminal 330 .

Server 310 may include a server processor, a server transceiver, and server memory. In the couple matching system subscription procedure of the first user terminal, the server 310 may receive user personal information from the first user terminal 320 . The user personal information may be information generated by the first user terminal 320 by a user's manipulation. The user personal information may include first user personal information and second user personal information. The first user personal information may include information corresponding to the user's personal information, such as gender, height, weight, and age. The second user personal information may include information corresponding to the time of birth of the user.

Also, in the couple matching system subscription procedure of the first user terminal, the server 310 may provide a plurality of subscription question information to the first user terminal 320 . The plurality of subscription question information may include, for example, information corresponding to the preferred counterpart's age, the preferred counterpart's residential area, the preferred counterpart's height, and the like. The first user terminal 320 may generate a plurality of user selection information corresponding to each of the plurality of subscription question information and provide it to the server 310 . The user selection information may include, for example, when the subscription question information corresponds to the age of the preferred counterpart, the corresponding user selection information may be an age range of '25 to 30 years old'. Alternatively, when the subscription question information is information corresponding to the height (height) of a preferred counterpart, the corresponding user selection information may include a height section of '175 cm to 180 cm'. That is, the user selection information may include a user selection section corresponding to the subscription question information.

To this end, in an embodiment, the first user terminal 320 includes a first processor, a first transceiver, a first input unit, a GPS module, a camera module, a first output unit, and a first memory. ) may be included. The first memory of the first user terminal 320 may store a couple matching program. The first processor of the first user terminal 320 may control each component of the first user terminal 320 by executing a couple matching program. For example, the first processor of the first user terminal 320 may output the membership registration interface to the first output unit of the first user terminal 320 . The first input unit of the first user terminal 320 may receive a user's manipulation of the membership registration interface, and the first processor may generate the user personal information based on the user's manipulation. For example, the membership registration interface may include a question area asking the user's gender, height, weight, age, time of birth, and the like. The user may complete the membership registration through the first user terminal 320 by inputting each response information into the question area of the interface. In this case, the first user terminal 320 may generate user personal information based on the user's input of response information. Also, the GPS module of the first user terminal 320 may generate location information of the first user terminal 320 . Similarly, the camera module of the first user terminal 320 may generate photo information of the user by photographing the user of the first user terminal 320 . The location information of the first user terminal 320 and the user's photo information may constitute a part of the user's personal information. The first transceiver of the first user terminal 320 may transmit the generated user personal information to the server 310 .

The second user terminal 330 may be the same as or similar to the first user terminal 320 . That is, the second user terminal 330 may include a second processor, a second transceiver, a second input unit, a second output unit, and a second memory. Each component of the second user terminal 330 may be the same as or similar to each component of the first user terminal 320 .

The server 310 may include the same hardware module as a conventional web server or a network server in hardware. The server 310 may be implemented in the form of a web server or a network server, and may be implemented as a series of application programs operating on the web server including various databases built in the tangible storage device. . Therefore, the server 310 should be understood as a broad concept that is not limited to any one of the above-described contents.

The server 310 may be implemented through a physical server. That is, the server 310 is implemented as a server including a communication device, and receives data from the second user terminal 330 and the first user terminal 320 , and also the second user terminal 330 and the first user. Data may be transmitted to the terminal 320 . The server 310 is a workstation, a data center, an internet data center (IDC), a direct attached storage (DAS) system, a storage area network (SAN) system, a network attached storage (NAS) system, It may be implemented as at least one of a RAID (redundant array of inexpensive disks, or redundant array of independent disks) system and an EDMS (Electronic Document Management) system, but the present embodiment is not limited thereto.

When the server 310 is implemented through a physical server, the server 310 may transmit or receive data through the network 340 connected wirelessly or wiredly. The network 340 may include a network based on a wired Internet technology, a wireless Internet technology, and a short-range communication technology. Wired Internet technology may include, for example, at least one of a local area network (LAN) and a wide area network (WAN).

Wireless Internet technology is, for example, wireless LAN (WLAN), DLNA (Digital Living Network Alliance), WiBro (Wireless Broadband: Wibro), Wimax (World Interoperability for Microwave Access: Wimax), HSDPA (High Speed Downlink Packet) Access), High Speed Uplink Packet Access (HSUPA), IEEE 802.16, Long Term Evolution (LTE), Long Term Evolution-Advanced (LTE-A), Wireless Mobile Broadband Service (WMBS) and 5G New Radio (NR) technology. However, the present embodiment is not limited thereto.

When the server 310 transmits/receives data using a wireless communication method, the server 310 may comply with technical standards and standard communication methods for mobile communication. For example, standard communication methods include Global System for Mobile communication (GSM), Code Division Multi Access (CDMA), Code Division Multi Access 2000 (CDMA2000), Enhanced Voice-Data Optimized or Enhanced Voice-Data Only (EV-DO). , at least one of Wideband CDMA (WCDMA), High Speed Downlink Packet Access (HSDPA), High Speed Uplink Packet Access (HSUPA), Long Term Evolution (LTE), Long Term Evolution-Advanced (LTEA), and 5G New Radio (NR). may include. However, the present embodiment is not limited thereto.

FIG. 4 is a block diagram for explaining the structure of the server 310 of FIG. 3 . 5 is a view for explaining the heavens. 6 is a view for explaining the support.

Referring to FIG. 4 , the server 310 may include a user information management module 311 , a stock week analysis module 312 , a database 313 , and a matching information generation module 314 .

The user information management module 311 may receive user personal information from the first user terminal 320 . The user personal information may be information generated by the first user terminal 320 by a user's manipulation. The user personal information may include first user personal information and second user personal information. The first user personal information may include information corresponding to the user's personal information, such as gender, height, weight, and age. The second user personal information may include information corresponding to the time of birth of the user. Here, it should be borne in mind that 'first' and 'second' are only modifiers for specifying the user's personal information, and do not limit the order of the user's personal information.

Also, the user information management module 311 may provide a plurality of subscription question information to the first user terminal 320 . The plurality of subscription question information may include, for example, information corresponding to the preferred counterpart's age, the preferred counterpart's residential area, the preferred counterpart's height, and the like. The user information management module 311 may receive a plurality of pieces of user selection information corresponding to each of a plurality of pieces of subscription question information from the first user terminal 320 .

The stock week analysis module 312 may generate the stock week vector based on the second user personal information. The four weeks analysis module 312 may extract the heaven and the support based on the information corresponding to the time of birth included in the second user's personal information. Here, the time of birth may mean the date and time at which a person was born. Specifically, the time of birth may include four pieces of information of the year, month, day, and time of the person's birth.

5 and 6, the four pillars of year-ju, wol-ju, il-ju, and si-ju are called four poles, and are composed of two characters in year, two in month, two in day, and two in city. Eight letters are called eight letters to compose four weeks and eight letters. Of the two letters constituting the four pillars of year, month, day, and hour, the upper letter is called cheongan, and the lower letter is called Jiji. Cheongan refers to the name of the sky, and consists of 10 gans: Gap, Eul, Byeong, Jeong, Mu, Ki, Gyeong, Shin, Im, and Gye, and each letter has its own meaning. Gap, Byeong, Radish, Gyeong, and Im are called Yanggan (yang), and Eul, Jeong, Kishin, and Gye are 5 types of Yin, so they are called Yingan (陰干). Also, in harmony with the five elements, it can be interpreted in a broader sense. Jiji is made up of 12 characters: ruler, axis, in, myo, jin, sa, oh, mi, god, yu, sul, and hae, and each letter symbolizes an animal. In, Jin, Sa, Shin, Liquor, and the year are the six elements of the sun, and Myo, Oh, Mi, Yu, Ja, and the axis are the six shades.

The 10 celestial poles and 12 jijis have the meaning of coexisting together, and the 10 celestial poles and 12 jijis combine to create 60 zodiac signs that end suddenly in the end of the year. Also, it is called 6-gap because it moves six times, and the 60 zodiac signs repeat six times and repeat once every 360 days, which is one year in the lunar calendar. In other words, the changes and phenomena between the heavens contain the principles of heaven, and the changes in the 12 zodiac signify the image that occurs on the earth. Information on the ceiling and support may be stored in the memory of the server 310 .

The key stock analysis module 312 receives the user's second user personal information and information about the heavens and the support stored in the memory of the server 310, and based on the second user personal information and the information on the heavens and the support You can output the user's four weeks vector. That is, the stock week analysis module 312 may analyze the user's stock week based on the time of birth of the user. The stock week analysis module 312 may generate key week information of the user by matching the information shown in FIGS. 5 and 6 based on the time of birth of the user. The key stock analysis module 312 may generate user stock week information by using the information on the heavens and the support in the memory of the server 310 based on the time of birth included in the second user personal information. The user stock stock information may include a stock stock vector of the user. That is, the stock week analysis module 312 may output a stock week vector based on the generated user stock week information. The stock stock vector may be an n-dimensional vector corresponding to user stock stock information.

The database 313 may receive user personal information from the user information management module 311 and store user personal information. The database 313 may have a general data structure implemented in the storage space of the server 310 using a database management program (DBMS). The database 313 may select any one of a plurality of user personal information stored in the database 313 in response to a control signal from an external device or module using a database management program. Specifically, the database 313 may select and output any one of a plurality of user personal information stored in the database 313 based on the control of the user information management module 311 .

The matching information generation module 314 may receive the first user personal information from the user information management module 311 . Also, the matching information generation module 314 may receive user selection information from the user information management module 311 . The matching information generation module 314 may extract first element information based on the first user personal information. The first element information may correspond to any one of one or more pieces of personal information included in the first user personal information. For example, the first element information may be information corresponding to the user's height (height). Alternatively, the first element information may be information corresponding to the age of the user.

The matching information generating module 314 may output a personalized vector based on the first user personal information and user selection information. The matching information generating module 314 may extract first element information from the first user personal information. The matching information generating module 314 may output a personalized vector based on the first element information and user selection information corresponding to the first element information. The personalized vector may be an n-dimensional vector representing user selection information for the first element information. A method in which the matching information generating module 314 generates the personalized vector will be described in detail later.

In this specification, the four weeks vector may be referred to as a second vector, and the personalization vector may be referred to as a first vector. Here, the first and the second are means for specifying the four weeks vector and the personalized vector, and do not limit the order of each vector.

In addition, the matching information generation module 314 may receive user stock week information including the user's stock stock vector from the stock week analysis module 312 . The matching information generation module 314 may generate user matching information based on the four weeks vector and the personalized vector. In an embodiment, the matching information generating module 314 may encrypt the key stock vector and the personalization vector to generate encrypted user matching information based on the encrypted key stock vector and the encrypted personalization vector. The matching information generating module 314 may store user matching information in the database 313 .

The database 313 may receive user matching information from the matching information generation module 314 and store the user matching information. In this case, the database 313 may store user profile information by generating user profile information for the same user based on user personal information and user matching information.

The matching information generating module 314 may receive the user profile information of the second user from the database 313 and output a matching score based on the user profile information of the second user and the user profile information of the first user. The matching score may be, for example, a score generated based on user personal information of each of the first user and the second user, subscription question information, user stock ownership information, and the like. The matching score may be a score indicating a preference between the first user and the second user. The matching information generating module 314 extracts the first vector from the user profile information of the first user, and extracts the first relative vector from the user profile information of the second user, so as to determine the degree of similarity between the first vector and the first relative vector. A first score may be generated based on it. Here, the first relative vector corresponds to the first vector included in the user profile information of the first user, and may mean a first vector included in the user profile information of the second user extracted for comparison with the first vector. can The first score may be a score generated based on a similarity between the first vector and the first relative vector.

In addition, the matching information generation module 314 extracts a second vector from the user profile information of the first user, and extracts a second relative vector from the user profile information of the second user, so that the second vector and the second relative vector are A second score may be generated based on the similarity. Here, the second relative vector corresponds to the second vector included in the user profile information of the first user, and may mean a second vector included in the user profile information of the second user extracted for comparison with the second vector. can The second score may be a score generated based on the similarity between the second vector and the second relative vector.

The matching information generation module 314 may generate a matching score based on the first score and the second score.

In an embodiment, the matching information generating module 314 may output the first correction score using the matching information correction model based on the first score. The first correction score may mean a correction value for correcting the first score in order to accurately calculate a matching score based on the first score. Here, the matching information correction model may include an input layer, one or more hidden layers, and an output layer. The matching information correction model may be trained in advance so that the first correction score is accurately output based on the first score and the second score through a learning process. To this end, in the learning process, a plurality of learning data related to the first score and the second score may be input to an input layer of the matching information correction model, pass through one or more hidden layers and an output layer, and an output vector may be output. The output vector may be input to a loss function layer connected to the output layer. The loss function layer may output a loss value using a loss function that compares the output vector with the correct vector for each training data. The parameters of the matching information correction model may be learned in a direction in which the loss value becomes smaller.

For example, the loss function may calculate a loss value according to [Equation 1]. In [Equation 1], N is the number of a plurality of training data, n is a natural number identifying the training data, k is a natural number identifying the value of the n-th training data, nk is the k-th value of the n-th training data , t denotes correct answer data, y denotes an output vector, and E denotes a loss value.

Alternatively, the loss function may calculate a loss value according to [Equation 2]. In [Equation 2], n is the number of learning data for each class, y and j are identifiers indicating classes, C is a constant value, M is the number of classes, x_y is the probability value that the learning data belongs to class y, x_j is learning A probability value that data belongs to class j, L may mean a loss value.

To this end, the matching information generation module 314 may include an artificial intelligence machine learning model. When the server 310 is implemented as hardware, the matching information generation module 314 may include a hardware structure specialized for processing a machine learning model. Machine learning models can be created through artificial intelligence machine learning.

The machine learning algorithm may include, for example, supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning, but the above-described example is not limited to The artificial intelligence model may include a plurality of artificial neural network layers. Artificial neural networks include deep neural networks (DNNs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), restricted boltzmann machines (RBMs), deep belief networks (DBNs), bidirectional recurrent deep neural networks (BRDNNs), It may be one of deep Q-networks or a combination of two or more of the above, but is not limited to the above example. The artificial intelligence model may include, in addition to, or alternatively, a software structure in addition to the hardware structure.

Each component included in the server 310 may be connected to a communication path that connects a software module or a hardware module inside the device to operate organically with each other. These components may communicate using one or more communication buses or signal lines. Each component of the server 310 means a unit for processing at least one function or operation, and may be implemented as a software module, a hardware module, or a combination of software and hardware.

The configuration of the server 310 shown in FIG. 4 is not necessarily essential, and some configurations may be omitted or other configurations not shown in FIG. 4 may be added as necessary. That is, the configuration shown in FIG. 4 is for convenience of description, and embodiments are not limited thereto. Those of ordinary skill in the art will be able to modify and practice the embodiments of the present invention without departing from the scope of the present invention.

7 is a flowchart illustrating a couple matching operation of the server 310 according to an embodiment of the present invention.

Referring to FIG. 7 , first, the first user personal information, the second user personal information, and the user selection information are received from the first user terminal 320 by the user information management module 311 ( S710 ).

The matching information generating module 314 outputs a first vector based on the first element information and the user selection information included in the first user personal information (S720).

Here, the user selection information may include a first user selection section for subscription question information corresponding to the first element information. For example, when the first element information is 'age', the subscription question information corresponding to the first element information may be information corresponding to 'what is the age of the other party you prefer?' In this case, the first user selection section included in the user selection information may be '25 to 30'. That is, the first user-selected interval may be a finite interval including a minimum value and a maximum value. The first user-selected section may be expressed as a set of one or more real numbers. Alternatively, the first user-selected section may be expressed as a linear function.

by the matching information generating module 314 , a second selection including a first selection element for the first subscription question information and a weight for the first selection element by using a matching model function based on the first user selection interval elements can be printed. The first selection element may correspond to values included in the first user selection section for the first subscription question information. For example, when the first user selection section is '25 to 30', the first selection element may correspond to '25, 26, 27, 28, 29, 30', respectively. The second selection element may each correspond to weights for each of the first selection element.

The matching information generation module 314 may generate a first vector for the first subscription question information based on the first selection element and the second selection element. The matching information generating module 314 performs matrix operation on a first selection element composed of respective values of the first user selection interval for the first subscription question information and a weight corresponding to each value of the first user selection interval to obtain a first vector can create

The matching information generation module 314 may generate the first vector using Equation 3 above. In <Equation 3>, c is the first selection element, P(c) is the second selection element, c_l is the minimum value of the first user selection interval, c_h is the maximum value of the first user selection interval, c_m is A median value of the first user-selected section, w_i may mean a first correction coefficient, and p_i may mean a second correction coefficient.

By the four weeks analysis module 312, the second vector is output based on the information corresponding to the time of birth included in the second user personal information (S730).

The week week analysis module 312 may extract the year week, month week, week week, and week week based on information corresponding to the time of birth included in the second user personal information. The four week analysis module 312 may output a second vector by corresponding to the extracted year week, month week, week week, and week week, respectively, with information about heaven and support stored in the memory of the server 310 . The second vector may include information corresponding to a plurality of elements constituting the information on the ceiling and support stored in the memory of the server 310 .

The matching information generation module 314 generates user matching information based on the first vector and the second vector (S740).

The matching information generating module 314 generates a first score based on the similarity between the first vector and the first relative vector, and generates a second score based on the similarity between the second vector and the second relative vector ( S750).

The matching information generating module 314 may receive the user profile information of the second user from the database 313 and output a matching score based on the user profile information of the second user and the user matching information of the first user. The matching information generating module 314 extracts a first vector from the user matching information of the first user, and extracts a first relative vector corresponding to the first vector from the user profile information of the second user, so that the first vector and A first score may be generated based on the similarity of the first relative vector. Here, the first relative vector corresponds to the personalization vector (first vector) included in the user matching information of the first user, and is extracted for comparison with the personalization vector (first vector) in the user profile information of the second user. It may mean an included personalization vector (first vector). That is, the first personalized vector (first vector) included in the user profile information generated based on the user personal information of the first user, and the first personalized vector (first vector) included in the user profile information generated based on the user personal information of the second user When comparing two personalization vectors (the first vector), the first personalization vector and the second personalization vector may be referred to as a first vector and a first relative vector, respectively.

The first score may be a score generated based on a similarity between the first vector and the first relative vector.

In addition, the matching information generation module 314 extracts a second vector from the user profile information of the first user, and extracts a second relative vector from the user profile information of the second user, so that the second vector and the second relative vector are A second score may be generated based on the similarity. Here, the second relative vector corresponds to the second vector (four weeks vector) included in the user profile information of the first user, and corresponds to the user profile information of the second user extracted for comparison with the second vector (four weeks vector). It may mean an included second vector (six weeks vector). The second score may be a score generated based on the similarity between the second vector and the second relative vector.

The matching information generating module 314 may calculate the similarity between the first vector and the first relative vector and the similarity between the second vector and the second relative vector using any one of Cosine Similarity, Jaccard similarity, Euclidean distance, and Levenshtein distance. . However, this is only exemplary, and the embodiment of the present invention is not limited thereto. That is, methods for the matching information generating module 314 to calculate the similarity between the first vector and the first relative vector and the similarity between the second vector and the second relative vector may vary.

The matching information generating module 314 may output a degree of similarity between the first vector and the first relative vector and a degree of similarity between the second vector and the second relative vector based on <Equation 4>.

In <Equation 4>, KS may indicate similarity, v_k may indicate a first vector (or second vector), rv_k may indicate a first relative vector (or second vector), and k may indicate a natural number for identifying a vector.

The matching information generating module 314 selects user profile information from the database 313 based on the first score and the second score and provides it to the user terminal (S760).

The matching information generation module 314 may output a matching score based on the first score and the second score. The matching score may be a score indicating a preference between the first user and the second user. That is, the matching information generating module 314 extracts the first vector from the user matching information of the first user, and extracts the first relative vector from the user profile information of another user stored in the database 313, A first score is generated based on the similarity of the first relative vector, a second vector is extracted from user matching information of the first user, and a second relative vector is extracted from user profile information of another user stored in the database 313 . to generate a second score based on the similarity between the second vector and the second relative vector, output a matching score based on the first score and the second score, and select user profile information of a user with a high matching score Thus, it can be provided to the user terminal.

As described above, the method of providing a couple matching service according to an embodiment of the present invention provides a better couple matching service based on matching information generated by giving different weights to the stock ownership and compatibility information and user preference item information. can provide

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. The 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 may 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 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 device, 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.

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.

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 a different order than 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 (5)

receiving, by the user information management module, user personal information from the user terminal; - The user personal information includes first user personal information including one or more element information corresponding to one or more of the user's gender, height, weight, age, occupation, and residence area, and information corresponding to birth Includes second user personal information-
providing, by the user information management module, a plurality of subscription question information to the user terminal, and receiving a plurality of user selection information corresponding to each of the plurality of subscription question information from the user terminal;
outputting, by the matching information generating module, a first vector based on first element information included in the first user personal information and user selection information corresponding to the first element information among the plurality of user selection information ;
outputting, by the stock week analysis module, a second vector based on the second user personal information;
generating, by the matching information generating module, user matching information based on the first vector and the second vector;
storing, in a database, user profile information generated based on the user personal information and the plurality of user selection information; and
Selecting any one from among a plurality of user profile information stored in the database based on the user matching information and the plurality of user selection information and providing the selected one to the user terminal;
The first user selection information corresponding to the first element information among the plurality of user selection information includes a first user selection section for the first subscription question information corresponding to the first user selection information,
The operation of outputting the first vector by the matching information generating module includes:
A first selection element composed of response information to the first subscription question information using a matching model function based on the first user selection section by the matching information generation module, and a weight for the first selection element outputting a second selection element including; and
generating the first vector for the first subscription question information based on the first selection element and the second selection element;
[Equation]

The matching information generating module generates the first vector by using the <Equation>, where c is the first selection element, P(c) is the second selection element, and c_l is the minimum value of the first user-selected section, c_h is the maximum value of the first user-selected section, c_m is the median value of the first user-selected section, w_i is the first correction coefficient, p_i is the second correction coefficient,
A method of providing a couple matching service using artificial intelligence-based key stocks and compatibility. delete The method of claim 1,
The operation of outputting the second vector by the four week analysis module is,
extracting, by the four weeks analysis module, the celestial body and support based on the information corresponding to the time of birth included in the second user personal information; and
The operation of generating the second vector based on the extracted zenith and support; further comprising,
A method of providing a couple matching service using artificial intelligence-based key stocks and compatibility. The method of claim 1,
A plurality of user profile information stored in the database includes first user profile information,
generating, by the matching information generation module, a first score based on a similarity between the first vector and a first relative vector corresponding to the first vector among the first user profile information;
A method of providing a couple matching service using artificial intelligence-based key stocks and compatibility. 5. The method of claim 4,
generating, by the matching information generating module, a first correction score using a matching information correction model based on the first score;
The matching information correction model includes an input layer, one or more hidden layers and an output layer,
A plurality of training data related to the first score is input to the input layer of the matching information correction model and passes through the one or more hidden layers and output layers to output an output vector, and the output vector is a loss connected to the output layer It is input to a function layer, and the loss function layer outputs a loss value using a loss function that compares the output vector with a correct vector for each training data, and the parameter of the matching information correction model has a small loss value. learning in a losing direction,
A method of providing a couple matching service using artificial intelligence-based key stocks and compatibility.

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