KR20190031421A - Method for recommending designated items - Google Patents

Abstract

Disclosed in the present application is a recommendation method of a designation item, which comprises the following steps: determining at least one reference designation item based on input information received from a user electronic device; generating at least one recommended designation item set which can be recommended to a user based on the at least one reference designation item; and delivering the at least one recommended designation item set to the user electronic device.

Description

{METHOD FOR RECOMMENDING DESIGNATED ITEMS}

This specification relates to a method for recommending a designation item.

As interest in artificial intelligence has increased in recent years, much of the work has been replaced by artificial intelligence. This phenomenon is not an exception for intellectual property services, so various artificial intelligence technologies are being applied to intellectual property search and service.

Korean Patent Publication No. 10-2009-0005684

The present specification provides a method for recommending items using artificial intelligence and / or machine learning.

The disclosed technique includes determining at least one reference designation based on input information received from a user electronic device; Generating at least one recommendation item set that can be recommended to a user based on the at least one reference designation item; And communicating the at least one set of recommendation items to a user electronics device.

In addition, the input information may include at least one of business type information related to a business type of a user, similarity group information, a designated product, and a designated service business.

Also, the step of generating the at least one recommended designation item set may include: generating a plurality of designation items including a set of at least one designation items included in a plurality of trademark applications commonly including the at least one reference designation item Extracting information; And generating the at least one recommendation item set based on the at least one designation item included in the plurality of designation item information.

Also, the step of generating the at least one recommended designation item set based on the at least one designation item commonly included in the plurality of designation item information may include: In descending order based on the appearance frequency, and generate the at least one recommended designation item set in the sorted order.

The generating of the at least one recommended designation item set based on the at least one designation item commonly included in the plurality of designation item information may include generating at least one item of designation item information Constructing a pattern tree storing a set of designated items; And mining the at least one set of recommendation items based on the pattern tree.

The step of constructing the pattern tree may include: generating a data structure including information on nodes and links constituting the pattern tree; Extracting a plurality of sets of candidate designation items including the at least one designation item having an appearance frequency of at least a predetermined degree of support among at least designation items included in each trademark application information; Arranging the at least one designation item included in the plurality of candidate designation item sets in descending order based on the appearance frequency; And constructing the pattern tree based on the plurality of candidate designation items sets including the aligned at least one designation item.

In addition, the step of mining the at least one recommended designation item set based on the pattern tree may include, for each designation item included in the header table, at least Generating condition pattern base information including a set of one dictionary path; Constructing a conditional pattern tree including at least one designation item having an appearance frequency of the degree of support or higher among at least one designation items included in the conditional pattern base information for each designation item included in the header table; And generating at least one recommendation item set in which a subset of the condition pattern tree and each designation item included in the header table are combined.

In addition, the techniques disclosed herein may further comprise receiving user tag information that includes information about a mark of a trademark from a user electronic device, wherein generating the at least one recommended tag set includes: If the mark information for at least one trademark application included in the trademark application is similar to the user mark information, a designation item similar to at least one designation item included in the at least one trademark application is excluded from the set of recommended designation items .

The techniques disclosed herein may include a computer program stored on a medium in combination with hardware to carry out the method of recommending items described above.

The techniques disclosed herein include a communication module; A processor for executing instructions; And a computer readable memory having stored thereon a program for executing the instructions in an electronic device, the instructions comprising: determining at least one reference designation based on input information received from a user electronic device; Generating at least one recommendation item set that can be recommended to a user based on the at least one reference designation item; And forwarding the at least one set of recommendation items to a user electronics device.

An exemplary technique is to use an artificial intelligence to search for intellectual property on an image basis.

Exemplary techniques provide a way for a user to search for trademarks associated with a particular image, even if the user does not have expert knowledge of the trademark.

Exemplary techniques may recommend a customized designated product or designated service industry to the user.

1 is a diagram illustrating an exemplary electronic system.
2 is a block diagram illustrating an exemplary electronic device.
Figure 3 is a block diagram of an illustrative program module.
4 is a diagram illustrating an exemplary electronic system.
5 is a diagram illustrating functions of the exemplary first server and / or the second server.
6 is a diagram for explaining the recognition function of the exemplary first server and / or the second server.
7 is a diagram for explaining a matching function and / or a search information generating function of the exemplary first server and / or the second server.
8 is a diagram showing a control method of an exemplary electronic system.
9 is a diagram showing a control method of an exemplary electronic system.
10 is a diagram showing an exemplary recommended item recommendation method.
11 is a diagram illustrating a method of generating an exemplary recommended item set.
12 is a diagram illustrating another method of generating an exemplary recommendation item set.
13 is a diagram illustrating another method of generating an exemplary recommendation item set.
14 is a diagram showing a method of constructing an exemplary pattern tree.
15 is another diagram showing a method of constructing an exemplary pattern tree.
16 is a diagram illustrating a method of mining an exemplary set of recommended items.
Figure 17 is another diagram illustrating a method of mining an exemplary set of recommended entries.

It is noted that the technical terms used herein are used only to describe specific embodiments and are not intended to limit the scope of the technology disclosed herein. Also, the technical terms used herein should be interpreted as being generally understood by those skilled in the art to which the presently disclosed subject matter belongs, unless the context clearly dictates otherwise in this specification, Should not be construed in a broader sense, or interpreted in an oversimplified sense. It is also to be understood that the technical terms used herein are erroneous technical terms that do not accurately represent the spirit of the technology disclosed herein, it is to be understood that the technical terms used herein may be understood by those of ordinary skill in the art to which this disclosure belongs And it should be understood. Also, the general terms used in the present specification should be interpreted in accordance with the predefined or prior context, and should not be construed as being excessively reduced in meaning.

As used herein, terms including ordinals, such as first, second, etc., may be used to describe various elements, but the elements should not be limited by the terms. The terms are used only for the purpose of distinguishing one component from another. For example, without departing from the scope of the present disclosure, the first component may be referred to as a second component, and similarly, the second component may also be referred to as a first component.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings, wherein like reference numerals denote like or similar elements, and redundant description thereof will be omitted.

Further, in the description of the technology disclosed in this specification, a detailed description of related arts will be omitted if it is determined that the gist of the technology disclosed in this specification may be obscured. It is to be noted that the attached drawings are only for the purpose of easily understanding the concept of the technology disclosed in the present specification, and should not be construed as limiting the spirit of the technology by the attached drawings.

1 is a diagram illustrating an exemplary electronic system.

Referring to FIG. 1, an electronic system 100 may include at least one electronic device 101, 102, 104, a server 106, and / or a network 162.

The electronic device according to the present disclosure may be a device including a communication function. For example, the electronic device can be a smart phone, a tablet personal computer, a mobile phone, a videophone, an ebook reader, a desktop personal computer, a laptop PC such as a laptop personal computer, a netbook computer, a personal digital assistant (PDA), a portable multimedia player (PMP), an MP3 player, a mobile medical device, a camera, or a wearable device Such as a head-mounteddevice (HMD) such as eyeglasses, an electronic garment, an electronic bracelet, an electronic necklace, an electronic app apparel, an electronic newspaper, or a smartwatch.

According to some embodiments, the electronic device may be a smart home appliance with communication capabilities. [0003] Smart household appliances, such as electronic devices, are widely used in the fields of television, digital video disk (DVD) player, audio, refrigerator, air conditioner, vacuum cleaner, oven, microwave oven, washing machine, air cleaner, set- (E.g., Samsung HomeSync, Apple TV, or Google TV), game consoles, an electronic dictionary, an electronic key, a camcorder, or an electronic photo frame.

According to some embodiments, the electronic device may be implemented in a variety of medical devices (e.g., magnetic resonance angiography (MRA), magnetic resonance imaging (MRI), computed tomography (CT), camera, ultrasound, global positioning system receiver, EDR (event data recorder), flight data recorder (FDR), automotive infotainment device, marine electronic equipment (eg marine navigation device and gyro compass), avionics, security An automotive head unit, an industrial or household robot, an automatic teller machine (ATM) of a financial institution, or a point of sale (POS) of a store.

According to some embodiments, the electronic device may be a piece of furniture or a structure / structure including a communication function, an electronic board, an electronic signature receiving device, a projector, (E.g., water, electricity, gas, or radio wave measuring instruments, etc.). An electronic device according to the present disclosure may be one or more of the various devices described above. Further, the electronic device according to the present disclosure may be a flexible device. It should also be apparent to those skilled in the art that the electronic device according to the present disclosure is not limited to the above-described devices.

The electronic device 101 may include a bus 110, a processor 120, a memory 130, an input / output interface 150, a display 160, and / or a communication interface 170.

At this time, the network 162 may include a wired LAN, a cable channel network, and all wirelessly connected methods.

In some embodiments, the electronic device 101 may omit at least one of the components or further comprise other components.

The bus 110 may include circuitry, for example, to connect components 110-170 to one another and to communicate communications (e.g., control messages and / or data) between the components.

The processor 120 may include one or more of a central processing unit (CPU), an application processor (AP), or a communication processor (CP). The processor 120 may perform, for example, operations or data processing relating to the control and / or communication of at least one other component of the electronic device 101. For example,

The memory 130 may include volatile and / or non-volatile memory. The memory 130 may store instructions or data related to at least one other component of the electronic device 101, for example. According to one embodiment, the memory 130 may store software and / or programs 140. The program 140 may be stored in a memory such as, for example, a kernel 141, a middleware 143, an application programming interface (API) 145, an application program . ≪ / RTI > At least a part of the kernel 141, the middleware 143, or the API 145 may be referred to as an operating system (OS).

The kernel 141 is a system that is used to execute an operation or function implemented in other programs (e.g., the middleware 143, the API 145, or the application program 147) Resources (e.g., the bus 110, the processor 120, or the memory 130, etc.). The kernel 141 can also control or manage system resources by accessing individual components of the electronic device 101 at the middleware 143, the API 145, or the application program 147 You can provide an interface.

The middleware 143 may perform an intermediary function such that the API 145 or the application program 147 can communicate with the kernel 141 to exchange data.

In addition, the middleware 143 may process one or more task requests received from the application program 147 according to a priority order. For example, the middleware 143 may access system resources (e.g., the bus 110, the processor 120, or the memory 130) of the electronic device 101 in at least one of the application programs 147, Etc.) can be given priority. For example, the middleware 143 may perform the scheduling or load balancing of the one or more task requests by processing the one or more task requests according to the priority assigned to the at least one task.

The API 145 is an interface for the application 147 to control the functions provided by the kernel 141 or the middleware 143. For example, At least one interface or function (e.g., command) for processing, character control, or the like.

The input / output interface 150 may serve as an interface through which commands or data input from, for example, a user or other external device can be transmitted to the other component (s) of the electronic device 101. The input / output interface 150 may output commands or data received from other component (s) of the electronic device 101 to a user or other external device.

The display 160 may be, for example, a liquid crystal display (LCD), a light emitting diode (LED) display, an organic light-emitting diode (OLED) Micro-electro-mechanical systems (MEMS) displays, or electronic paper displays. The display 160 may display various content (e.g., text, images, video, icons, symbols, etc.) to a user, for example. The display 160 may include a touch screen and may receive a touch, gesture, proximity, or hovering input using, for example, an electronic pen or a portion of the user's body.

The communication interface 170 may establish communication between the electronic device 101 and an external device such as the electronic device 102, the electronic device 104, or the server 106, for example. For example, the communication interface 170 may be connected to the network 162 via wireless or wired communication to communicate with an external device (e.g., the electronic device 104 or the server 106).

The wireless communication may include, for example, cellular communication. The cellular communication may include, for example, long-term evolution (LTE), LTE Advance, code division multiple access (CDMA), wideband CDMA (WCDMA), universal mobile telecommunications system (UMTS), WiBro Broadband, or Global System for Mobile Communications (GSM). The wireless communication may also include, for example, local area communication 164. The local area communication 164 may include at least one of, for example, wireless fidelity (Wi-Fi), Bluetooth, or near field communication (NFC). Also, the wireless communication may include a global positioning system (GPS).

The wired communication may include at least one of a universal serial bus (USB), a high definition multimedia interface (HDMI), a recommended standard 232 (RS-232), or a plain old telephone service (POTS). The network 162 may include at least one of a telecommunications network, e.g., a computer network (e.g., LAN or WAN), the Internet, or a telephone network.

Each of the electronic device 102 and the electronic device 104 may be the same or a different kind of device as the electronic device 101 described above. According to one embodiment, the server 106 may include one or more groups of servers. According to various embodiments, all or a portion of the operations performed on the electronic device 101 may be performed on another or a plurality of external devices (e.g., the electronic device 102, 104, or the server 106). According to one embodiment, in the event that the electronic device 101 has to perform a function or service automatically or upon request, the electronic device 101 may, instead of or in addition to executing the function or service itself, (E.g., electronic device 102, 104, or server 106) at least some of its associated functionality. An external device (e.g., electronic device 102, 104, or server 106) may execute the requested function or additional function and deliver the result to the electronic device 101. The electronic device 101 can directly or additionally process the received result to provide a requested function or service. For this purpose, for example, cloud computing, distributed computing, or client-server computing technology may be used.

2 is a block diagram illustrating an exemplary electronic device.

The electronic device 201 may include all or part of the electronic device 101 shown in Fig. 1, for example. The electronic device 200 may include one or more processors (e.g., APs) 210, a communication module 220, a memory 230, a sensor module 240, an input device 250, a display 260 An interface 270, an audio module 280, a camera module 291, a power management module 295, a battery 296, an indicator 297, and a motor 298.

The processor 210 may, for example, drive an operating system or an application program to control a plurality of hardware or software components coupled to the processor 210, and may perform various data processing and operations. The processor 210 may be implemented as a system on chip (SoC), for example. According to one embodiment, the processor 210 may further include a graphics processing unit (GPU) and / or an image signal processor. The processor 210 may include at least some of the components shown in FIG. 2 (e.g., a cellular module 221). The processor 210 may load or process instructions or data received from at least one of the other components (e.g., non-volatile memory) into volatile memory and store the various data in non-volatile memory .

The communication module 220 may have the same or similar configuration as the communication interface 170 of FIG. The communication module 220 includes a cellular module 221, a Wi-Fi module 223, a Bluetooth module 225, a GPS module 227, an NFC module 228, (229).

The cellular module 221 may provide a voice call, a video call, a text service, or an Internet service, for example, through a communication network. According to one embodiment, the cellular module 221 may utilize a subscriber identity module (e.g., a SIM card) 224 to perform the identification and authentication of the electronic device 201 within the communication network. According to one embodiment, the cellular module 221 may perform at least some of the functions that the processor 210 may provide. According to one embodiment, the cellular module 221 may include a communication processor (CP).

Each of the Wi-Fi module 223, the Bluetooth module 225, the GPS module 227, and the NFC module 228 includes a processor for processing data transmitted and received through a corresponding module . According to some embodiments, at least some of the cellular module 221, the Wi-Fi module 223, the Bluetooth module 225, the GPS module 227, or the NFC module 228 Or more) may be included in one integrated chip (IC) or IC package.

The RF module 229 can, for example, send and receive communication signals (e.g., RF signals). The RF module 229 may include, for example, a transceiver, a power amplifier module (PAM), a frequency filter, a low noise amplifier (LNA), and the like. The RF module 229 may further include a component for transmitting and receiving electromagnetic waves in a free space in a wireless communication, for example, a conductor or a lead wire. 2, the cellular module 221, the Wi-Fi module 223, the Bluetooth module 225, the GPS module 227, or the NFC module 228 share one RF module 229 At least one of the cellular module 221, the Wi-Fi module 223, the Bluetooth module 225, the GPS module 227, or the NFC module 228, One can transmit and receive RF signals through separate RF modules.

The SIM card 224 may include, for example, a card containing a subscriber identity module and / or an embedded SIM, and may include unique identification information (e.g., an integrated circuit card identifier (ICCID) Subscriber information (e.g., international mobile subscriber identity (IMSI)).

The memory 230 (e.g., memory 130) may include, for example, an internal memory 232 or an external memory 234. The built-in memory 232 may be a volatile memory such as a dynamic RAM (RAM), a static random access memory (SRAM), or a synchronous dynamic RAM (SDRAM), a non-volatile memory : Programmable ROM (PROM), erasable and programmable ROM (EPROM), electrically erasable and programmable ROM (EEPROM), mask ROM, flash ROM, flash memory (e.g., NAND flash or NOR flash) , A hard drive, or a solid state drive (SSD).

The external memory 234 may be a flash drive, for example, a compact flash (CF), a secure digital (SD), a micro secure digital (SD) extreme digital, an MMC (MultiMediaCard), a memory stick, and the like. The external memory 234 may be functionally and / or physically connected to the electronic device 201 through various interfaces.

The sensor module 240 may, for example, measure a physical quantity or sense an operating state of the electronic device 201 to convert the measured or sensed information into an electrical signal. The sensor module 240 includes a proximity sensor 241, a gyro sensor 242, an illuminance sensor 243, a magnetic sensor 244, an acceleration sensor 245, a grip sensor 246, A biometric sensor 247, or a biometric sensor 248. Additionally or alternatively, the sensor module 240 can be, for example, an E-nose sensor, an electromyography sensor, an electroencephalogram sensor, an electrocardiogram sensor ), An infrared (IR) sensor, an iris sensor, and / or a fingerprint sensor. The sensor module 240 may further include a control circuit for controlling at least one sensor included therein. In some embodiments, the electronic device 201 further comprises a processor configured to control the sensor module 240, either as part of the processor 210 or separately, such that the processor 210 is in a sleep state The sensor module 240 can be controlled.

The input device 250 may include, for example, a touch panel 252, a (digital) pen sensor 254, or a key 256. The touch panel 252 may employ, for example, at least one of an electrostatic type, a pressure sensitive type, an infrared type, and an ultrasonic type. Further, the touch panel 252 may further include a control circuit. The touch panel 252 may further include a tactile layer to provide a tactile response to the user.

The pen sensor 254 may be part of, for example, a touch panel or may include a separate recognition sheet. The key 256 may include, for example, a physical button, an optical key, or a keypad.

The display 260 (e.g., display 160) may include a panel 262, a hologram device 264, or a projector 266. The panel 262 may include the same or similar configuration as the display 160 of FIG. The panel 262 may be embodied, for example, flexible, transparent, or wearable. The panel 262 may be configured as one module with the touch panel 252. The hologram device 264 can display a stereoscopic image in the air using interference of light. The projector 266 can display an image by projecting light onto a screen. The screen may be located, for example, inside or outside the electronic device 201. According to one embodiment, the display 260 may further include control circuitry for controlling the panel 262, the hologram device 264, or the projector 266.

The interface 270 may include, for example, a high-definition multimedia interface (HDMI), or a universal serial bus (USB). The interface 270 may, for example, be included in the communication interface 170 shown in FIG. Additionally or alternatively, the interface 270 can be, for example, an optical interface, a D-subminiature, a mobile high-definition link (MHL) interface, a secure digital card / MMC (multi-media card) interface, or IrDA (infrared data association) interface.

The audio module 280 may, for example, convert sound and electrical signals in both directions. At least some components of the audio module 280 may be included, for example, in the input / output interface 150 shown in FIG. The audio module 280 may process sound information input or output through, for example, a speaker 282, a receiver 284, an earphone 286, a microphone 288, or the like.

The camera module 291 may be, for example, a device capable of capturing a still image and a moving image, and may include one or more image sensors (e.g., a front sensor or a rear sensor), a lens, an image signal processor ), Or a flash (e.g., an LED or xenon lamp, etc.).

The power management module 295 may manage the power of the electronic device 201, for example. According to one embodiment, the power management module 295 may include a power management integrated circuit (PMIC), a charger integrated circuit (PMIC), or a battery or fuel gauge. The PMIC may have a wired and / or wireless charging scheme. The wireless charging scheme may include, for example, a magnetic resonance scheme, a magnetic induction scheme or an electromagnetic wave scheme, and may further include an additional circuit for wireless charging, for example, a coil loop, a resonant circuit, have. The battery gauge may measure, for example, the remaining amount of the battery 296, the voltage during charging, the current, or the temperature. The battery 296 may include, for example, a rechargeable battery and / or a solar battery.

The indicator 297 may indicate a particular state of the electronic device 201 or a portion thereof (e.g., the processor 210), e.g., a boot state, a message state, or a state of charge. The motor 298 can convert an electrical signal to mechanical vibration and can cause vibration, haptic effects, and the like. Although not shown, the electronic device 201 may include a processing unit (e.g., a GPU) for mobile TV support. The processing device for mobile TV support can process media data according to standards such as digital multimedia broadcasting (DMB), digital video broadcasting (DVB), or MediaFlo ( ^TM ), for example.

Each of the components described in this document may be composed of one or more components, and the name of the component may be changed according to the type of the electronic device. In various embodiments, the electronic device may comprise at least one of the components described herein, some components may be omitted, or may further include additional other components. In addition, some of the components of the electronic device according to various embodiments may be combined into one entity, so that the functions of the components before being combined can be performed in the same manner.

3 is a block diagram of an exemplary program module.

According to one embodiment, the program module 300 (e.g., program 140) includes an operating system (OS) and / or an operating system (OS) that controls resources associated with an electronic device (E. G., The application program 147) running on the system. The operating system can be, for example, android, iOS, windows, symbian, RTOS, Linux, webOS, peer to peer An OS having a characteristic, a tizen, or the like.

The program module 300 may include a kernel 320, a middleware 330, an application programming interface (API) 360, and / or an application 370. At least a portion of the program module 300 may be preloaded on an electronic device or downloaded from an external electronic device such as an external electronic device 102 or 104 or a server 106 or the like.

The kernel 320 (e.g., the kernel 141) may include, for example, a system resource manager 321 and / or a device driver 323. The system resource manager 321 can perform control, assignment, or recovery of system resources. According to one embodiment, the system resource manager 321 may include a process management unit, a memory management unit, or a file system management unit. The device driver 323 may include, for example, a display driver, a camera driver, a Bluetooth driver, a shared memory driver, a USB driver, a keypad driver, a Wi-Fi driver, an audio driver, or an interprocess communication .

The middleware 330 may provide the functionality commonly required by the application 370 or may be provided to the application 370 in order to allow the application 370 to efficiently use limited system resources within the electronic device. The various functions can be provided to the application 370. [ According to one embodiment, the middleware 330 (e.g., middleware 143) includes a runtime library 335, an application manager 341, a window manager 342, a multimedia manager a manager 343, a resource manager 344, a power manager 345, a database manager 346, a package manager 347, a connectivity manager 344, at least one of a manager 348, a notification manager 349, a location manager 350, a graphic manager 351, or a security manager 352 .

The runtime library 335 may include, for example, a library module that the compiler uses to add new functionality via a programming language while the application 370 is running. The runtime library 335 may perform input / output management, memory management, or functions for arithmetic functions.

The application manager 341 may manage the lifecycle of at least one of the applications 370, for example. The window manager 342 can manage GUI resources used in the screen. The multimedia manager 343 can recognize a format required for reproducing various media files and can encode or decode a media file using a codec suitable for the format. The resource manager 344 may manage resources such as a source code, a memory, or a storage space of at least one of the applications 370.

The power manager 345 operates together with a basic input / output system (BIOS), for example, to manage a battery or a power source, and can provide power information and the like necessary for the operation of the electronic device . The database manager 346 may create, search, or modify a database for use in at least one of the applications 370. The package manager 347 can manage installation or update of an application distributed in the form of a package file.

The connection manager 348 may manage wireless connections, such as, for example, Wi-Fi or Bluetooth. The notification manager 349 may display or notify events such as arrival messages, appointments, proximity notifications, etc. in a manner that does not interfere with the user. The location manager 350 may manage the location information of the electronic device. The position information represented by the present invention may include not only GPS (Global Positioning System) information but also acceleration sensor information, gyro sensor information, indoor coordinate sensor information for LBS (location based service), position information estimated on a network basis, Location information, and location information associated with movement received from the new electronic device. The graphic manager 351 may manage a graphic effect to be provided to the user or a user interface related thereto. The security manager 352 may provide security functions necessary for system security or user authentication. According to one embodiment, when the electronic device (e.g., the electronic device 101) includes a telephone function, the middleware 330 may include a telephony manager for managing the voice or video call function of the electronic device .

The middleware 330 may include a middleware module that forms a combination of various functions of the above-described components. The middleware 330 may provide a module specialized for each type of operating system to provide a differentiated function. In addition, the middleware 330 may dynamically delete some existing components or add new components.

The API 360 (e.g., API 145) may be provided in a different configuration depending on the operating system, for example, as a set of API programming functions. For example, for Android or iOS, you can provide one API set per platform, and for tizen, you can provide more than one API set per platform.

The application 370 (e.g., the application program 147) may include, for example, a home 371, a dialer 372, an SMS / MMS 373, an instant message 374, A calendar 378, a camera 376, an alarm 377, a contact 378, a voice dial 379, an email 380, a calendar 381, a media player 382, an album 383, 384), one or more applications capable of performing functions such as health care (e.g., measuring exercise or blood glucose), or providing environmental information (e.g., providing atmospheric pressure, humidity, or temperature information) .

According to one embodiment, the application 370 is an application (hereinafter referred to as an application) that supports information exchange between an electronic device (e.g., the electronic device 101) and an external device (e.g., electronic devices 102 and 104) Quot; information exchange application "for convenience of description). The information exchange application may include, for example, a notification relay application for transferring specific information to an external device, or a device management application for managing an external device.

For example, the notification delivery application may transmit notification information generated by another application (e.g., an SMS / MMS application, an email application, a healthcare application, or an environment information application) of the electronic device to an external device , 104), respectively. In addition, the notification delivery application may receive notification information from, for example, an external electronic device and provide the notification information to the user.

The device management application may include at least one function (e.g., turn-on / turn-off) of an external device itself (or some component) (Eg, install, delete, or update) an application running on an external device or services provided by an external device (such as a call service or a message service) .

According to one embodiment, the application 370 may include an application (e.g., a healthcare application of a mobile medical device, etc.) designated according to an attribute of an external device (e.g., electronic device 102, 104). According to one embodiment, the application 370 may include an application received from an external device (e.g., server 106 or electronic device 102, 104). According to one embodiment, the application 370 May include a preloaded application or a third party application downloadable from a server. The names of the components of the program module 310 according to the illustrated embodiment include the name of the operating system Depending on the type.

According to various embodiments, at least some of the program modules 310 may be implemented in software, firmware, hardware, or a combination of at least two of them. At least some of the program modules 300 may be implemented (e.g., executed) by, for example, a processor (e.g., the processor 210). At least some of the program modules 300 may include, for example, modules, programs, routines, sets of instructions or processes, etc. to perform one or more functions.

As used herein, the term "module" may refer to a unit comprising, for example, one or more combinations of hardware, software or firmware. "Module" may be interchangeably used with terms such as, for example, unit, logic, logical block, component, or circuit. A "module" may be a minimum unit or a portion of an integrally constructed component. A "module" may be a minimum unit or a portion thereof that performs one or more functions. "Modules" may be implemented either mechanically or electronically. For example, a "module" may be an application-specific integrated circuit (ASIC) chip, field-programmable gate arrays (FPGAs) or programmable-logic devices that perform known or later- And may include at least one.

At least a portion of a device (e.g., modules or functions thereof) or a method (e.g., operations) according to various embodiments may include, for example, computer-readable storage media in the form of program modules, As shown in FIG. When the instruction is executed by a processor (e.g., the processor 120), the one or more processors may perform a function corresponding to the instruction. The computer readable storage medium may be, for example, the memory 130. [

The computer readable recording medium may be a hard disk, a floppy disk, a magnetic media (e.g., a magnetic tape), an optical media (e.g., a compact disc read only memory (CD-ROM) a magneto-optical media (e.g., a floptical disk), a hardware device (e.g., read only memory (ROM), random access memory (RAM) Etc. Also, the program instructions may include machine language code such as those produced by a compiler, as well as high-level language code that may be executed by a computer using an interpreter, etc. The above- May be configured to operate as one or more software modules to perform exemplary operations, and vice versa.

Modules or program modules according to various embodiments may include at least one or more of the components described above, some of which may be omitted, or may further include other additional components. Operations performed by modules, program modules, or other components in accordance with various embodiments may be performed in a sequential, parallel, iterative, or heuristic manner. Also, some operations may be performed in a different order, omitted, or other operations may be added.

4 is a diagram illustrating an exemplary electronic system.

The electronic system 4000 may include at least one of a terminal 4010, a first server 4020, a second server 4030, and / or a third server 4040. Terminal 4010 may include the above-described electronic devices, and may include components of some and / or all of the above-described electronic devices. The first server 4020, the second server 4030, and / or the third server 4040 may include the above-described electronic devices and / or servers and may include portions of the electronic devices and / or servers described above and / And may include all of the components.

The terminal 4010 can acquire the target information. For example, the terminal may include at least one of a smart phone, a computer, a wearable computer, and / or an electronic device. Terminal 4010 may include the above-described electronic device. The target information may include at least one of audio, video, image, text, and / or additional information.

The terminal 4010 may forward the object information to the first server 4020. The terminal 4010 may receive search result information from the first server 4020. The terminal 4010 can display the search result information.

The first server 4020 may receive the object information from the terminal 4010 and may transmit the object information to the second server 4030. [ For example, the first server 4020 may transmit the target information to the second server 4030 as it is, or may process / edit / modify the target information, and then process / edit / ). The first server 4020 recognizes at least one image, audio, video, text, metadata, attribute information, and / or additional information contained in the object information and extracts at least one image, Extracts at least one image, audio, video, text, metadata, attribute information, and / or additional information from the second server 4030 after extracting the text, metadata, attribute information, and / .

The first server 4020 can receive the first recognition information corresponding to the object information from the second server 4030. [ For example, the second server 4030 may include an artificial intelligence server including artificial intelligence and / or machine learning functionality.

The first server 4020 may generate the second recognition information based on at least one of the object information and the first recognition information.

The first server 4020 may generate search information for searching for intellectual property rights corresponding to the object information based on at least one of the object information, the first recognition information, and the second recognition information. For example, intellectual property rights may include trademarks, patents, design rights, and copyright. The search information may include a search expression.

The first server 4020 can request the third server 4040 to search based on the search information and receive the search result information corresponding to the search information from the third server 4040. [

The first server 4020 may transmit the search result information to the terminal 4010. [

The second server 4030 may generate recognition information describing the object information based on artificial intelligence and / or machine learning techniques, and may transmit the generated recognition information to the first server 4020. [ For example, the second server 4030 may include a pre-learned artificial intelligence model (or machine learning model) based on a training set. The second server 4030 may exist in a form independent from the first server 4020 and may be partly and / or integrally integrated with the first server 4020. When the second server 4030 is integrated into the first server 4020, the first server 4020 can perform some and / or all of the functions of the second server 4030.

The third server 4040 may include a plurality of intellectual property information. For example, the third server 4040 may include a large database server that includes specific information related to at least one of patent, trademark, design right, and / or copyright. For example, the third server 4040 may include images, audio, video, text, metadata, attribute information, and / or additional information related to intellectual property rights.

The third server 4040 may receive the search information from the second server 4020 and may transmit the search result information corresponding to the search information to the second server 4020. [ For example, the search result information may include specific information about the intellectual property rights retrieved.

The third server 4040 may exist independently of the first server 4020 and may be partially and / or entirely integrated with the first server 4020. When the third server 4040 is integrated into the first server 4020, the first server 4020 may perform some and / or all of the functions of the third server 4040.

5 is a diagram illustrating functions of the exemplary first server and / or the second server.

(a), the first server and / or the second server may include various artificial intelligence algorithms. Hereinafter, the second server will be mainly described, but the first server may include all the functions of the second server.

For example, artificial intelligence algorithms can be classified into three types: classification algorithms (Logistic regression, Decision tree, Nearest-neighbor classifier, Kernel discriminant analysis, Neural network, Support vector machine, Random forest, Boosted tree) regression, Support vector regression, Principal component analysis, Non-negative matrix factorization, Manifold learning, SVD, K-means, Hierarchical clustering, mean- (SOMs), Pre-training / Deep Learning (Stacked Restricted Boltzmann Machine, Multi Layer Neural Nets using Stacked Auto-Encoders, Convolutional Neural Network, Recurrent Neural Network), a data comparison algorithm (Bipartite cross-matching, n-point correlation two-sample testing, minimum spanning tree).

(b), the second server may generate recognition information describing the object information based on at least one of the various artificial intelligence algorithms.

For example, the second server may classify the input target information into a plurality of detailed areas, and generate recognition information for each detailed area. The recognition information may include an attribute, a location, an arrangement, a direction, a number, a meaning, and / or characteristic information describing an object included in the object information and / or the detailed area.

6 is a diagram for explaining the recognition function of the exemplary first server and / or the second server.

The first server and / or the second server may recognize the object information 6010 based on the artificial intelligence technology described above to generate at least one piece of recognition information 6020. [ Hereinafter, the second server will be mainly described, but the first server can perform the same function as the second server.

The second server receives the object information (e.g., image or text) and can recognize the object included in the object information by region. For example, the target information may include an image, the image may include a photograph or picture of the chameleon in the first region, and a text image of "chameleon" in the second region.

The second server can classify objects based on object information, recognize objects, and recognize text (words or sentences). For example, the second server may generate recognition candidate information such as "Lizard, Chameleon, Vertebrate, Scaled Reptile, Reptile, Iguania, Fauna"

Further, the second server can calculate the accuracy of the recognition candidate information generated based on the object information. For example, Lizard has 96% accuracy, Chameleon has 92%, Vertebrate has 92%, Scaled Reptile has 91%, Reptile has 90%, Iguania has 88% and Fauna has 85% accuracy.

In addition, the second server can extract at least one piece of recognition information 6020 based on the recognized at least one (or plurality of) pieces of recognition candidate information. For example, the second server may extract at least one piece of recognition information 6020 closest to the target information 6010 from a plurality of pieces of recognition candidate information. For example, the extracted at least one piece of identification information 6020 may be "Chameleon ".

The method for the second server to extract at least one piece of recognition information from at least one (or plurality of) pieces of recognition candidate information may be based on the accuracy of the recognition candidate information, the matching relation with the target information, the correspondence with the target information, and / May be dependent on the method of FIG.

7 is a diagram for explaining a matching function and / or a search information generating function of the exemplary first server and / or the second server.

The first server 7020 and / or the second server 7030 may match at least one piece of identification information to the classification information. Hereinafter, the second server 7030 will mainly focus on recognizing the object information using the artificial intelligence, but the first server 7020 can also recognize the object information using the artificial intelligence. Also, the first server 7020 may include both the functions of the second server 7030 described above and the functions of the second server 7030 described below.

The terminal 7010 may receive the destination information and may forward the destination information to the first server 7020 and / or the second server 7030. For example, the target information may include audio, video, image, text, and / or additional information.

The first server 7020 may receive the target information and may transmit the target information to the second server 7030. [ Also, the first server 7020 may directly recognize the target information.

The second server 7030 may receive the object information from the terminal 7010 and / or the first server 7020, and may generate at least one identification information corresponding to the object information. In addition, the second server 7030 may divide and / or extract the object information into at least one region, and may generate at least one piece of recognition information corresponding to at least one region divided and / or extracted.

Then, it may transmit the generated at least one identification information to the first server 7020.

The first server 7020 can generate search information based on at least one piece of recognition information received and / or generated. For example, the search information may include search keywords and / or classification information.

The first server 7020 may match at least one piece of recognition information to classification information. For example, the classification information may include classification code information corresponding to the object information and / or recognition information, graphic element information describing the object information and / or recognition information, and / or other information.

For example, if the target information includes an image of a chameleon, the recognition information may include a chameleon or a chameleon. The first server 7020 can determine a field including Chameleon or Chameleon from among the graphic element information and determine classification code information 301110 corresponding to Chameleon or Chameleon. Then, the first server 7020 can generate classification information (e.g., DR = [031110]) based on classification code information.

The first server 7020 then generates search information by combining at least one of at least one identification information (e.g., Chameleon, Chameleon) and / or classification information (e.g., DR = [031110]) can do. For example, the search information may include a search expression.

For example, when the recognition information is a character, it can be included as a keyword of a direct search expression, and an object (graphic form, etc.) can be included as a keyword of a search expression after being converted into graphic code information. Artificial intelligence technology can be used in converting objects into graphic code information.

In addition, the first server 7020 may transmit the intellectual property rights (for example, patent, trademark, design, and / or copyright) associated with the object information to the first server 7020 and / . ≪ / RTI > For example, the first server 7020 may search for intellectual property rights stored in an external third server using a search engine installed in the first server 7020, or may search for a search engine installed in the first server 7020 May be used to search for intellectual property rights stored in the first server 7020. Also, the first server 7020 may include searching for intellectual property rights stored in the first server 7020, the third server, and / or an external DB server using an external search engine server.

Also, the first server 7020 and / or the second server 7030 may calculate the similarity between the object information and the searched intellectual property rights. In this case, the first server 7020 and / or the second server 7030 may be configured to perform a natural language processing, a natural language comparison algorithm, a sentence / context comparison algorithm, an image comparison algorithm, and / or an artificial intelligence CNN), or regressive neural network (RNN)) to calculate the degree of similarity between the object information and the searched intellectual property rights. On the basis of this, the first server 7020 can arrange the searched intellectual property rights in order of the degree of similarity to the terminal and / or the user, and the second server 7030 can sort the searched intellectual property rights To the terminal, the first server 7020, and / or the user.

In addition, the first server 7020 and / or the second server 7030 can determine the possibility of registration and / or the infringement based on the degree of similarity.

Also, the first server 7020 and / or the second server 7030 may generate recommendation information recommending the designated goods and / or designated service industry to the user, and provide the terminal and / or the user with the recommendation information. For example, the first server 7020, the second server 7030, the third server, and / or other servers may include an intellectual property DB. The intellectual property DB may include information such as an application number, an applicant, a name of a trademark, a designated product, and / or a designated service industry.

When the user inputs the application information related to the trademark application by using the terminal, the first server 7020 and / or the second server 7030 recommends the user the proper designated goods and / or designated service business based on the application information can do. For example, if the user enters application information such as a field of use of a trademark, a business type, a designated product, a designated service industry, applicant information, and / or other information, the first server 7020 and / ) May generate recommendation information recommending the designated product and / or the designated service industry based on the application information, and may provide the terminal and / or the user with the recommendation information. The first server 7020 and / or the second server 7030 may generate recommendation information for the application information using probability, statistics, machine learning, artificial intelligence, recommendation system, and / or expert system. The application information may include all information about the applicant, all information on intellectual property rights, and / or any information necessary for the filing of intellectual property rights.

For example, when the first user inputs the application information such as "trademark 1", "business type 1", and / or "designated goods 1 (or designated service industry)", the first server 7020 and / The server 7030 may generate recommendation information related to the designated goods and / or designated service industry appropriate to the first user based on the application information. The recommendation information may be a designated product and / or a designated service industry that is preferred or frequently filed by the first user, or a designated product and / or designated service business that is preferred or frequently filed in another trademark application and / or trademark similar to "trademark 1" Or may be a designated product and / or a designated service industry that is preferred or frequently filed in other trademark applications and / or trademarks in a field / industry similar to "trademark 1", or a trademark application and / Or a designated goods and / or designated service industry which is preferred or frequently filed in a trademark right.

Also, the first server 7020 and / or the second server 7030 may determine the possibility of registration and / or the infringement by considering the relationship between the application information provided from the first user and the other trademark application and / or trademark , Recommendation information that can be registered and / or not infringed in relation to other trademark applications and / or trademark rights can be generated and provided to the terminal and / or the user.

As a result, the user can quickly apply for intellectual property rights on his or her own without the help of another person. To this end, the first server 7020 and / or the second server 7030 may provide the user with an interface through which the user can apply for an intellectual property right. In addition, the applicant can submit his / her own application form to the Patent Office.

8 is a diagram showing a control method of an exemplary electronic system.

The electronic system may include at least one of a terminal 8010, a first server 8020, a second server 8030, a third server 8040, and / or other servers 8050 . Hereinafter, the second server 8030 and / or the third server 8040 are independent of the first server 8020, but a part of the second server 8030 and / or the third server 8040 and / The whole can be integrated into the first server 8020. When integrated, the first server 8020 may perform some and / or all of the functions of the second server 8030 and / or the third server 8040.

The terminal 8010 can receive the target information. The terminal 8010 may then pass the destination information to the first server 8020 and / or to the second server 8030. The first server 8020 may perform the preprocessing on the object information received from the terminal 8010 and then forward the processed object information to the second server 8030. For example, the preprocessing may include pre-processing necessary for recognition of object information, such as filtering of object information and object information extraction for each region.

The second server 8030 can receive the object information and generate the first recognition information corresponding to the object information using the artificial intelligence based on the object information. Then, the second server 8030 can forward the first recognition information to the first server 8020. [

Also, the first server 8020 can generate second recognition information corresponding to the object information based on at least one of the object information and / or the first recognition information.

Also, the first server 8020 can generate search information based on at least one of the object information, the first recognition information, and / or the second recognition information.

In addition, the first server 8020 may search the first server for the intellectual property corresponding to the search information and generate the first search result information based on the search information. Also, the first server 8020 may search for the intellectual property corresponding to the search information in the third server 8040 based on the search information, and receive and / or generate the second search result information. Also, the first server 8020 may search for intellectual property corresponding to the search information in the other server 8050 based on the search information, and receive and / or generate the third search result information. The first search result information, the second search result information, and / or the third search result information may include information related to intellectual property rights. For example, the first search result information, the second search result information, and / or the third search result information may include a name of an invention / design, a claim, a specification, a drawing, a classification information of a patent / design, An image, a designated product, a designated service business, classification information of a trademark / product / service, a name of an item of a design, a drawing of a design, a description of a design, and / or classification information of a design / article.

Also, the first server 8020 may transmit at least one of the object information, the first recognition information, the second recognition information, the first search result information, the second search result information, and / or the third search result information to the second server 8030).

The second server 8030 receives the first determination information based on at least one of the object information, the first recognition information, the second recognition information, the first search result information, the second search result information, and / Lt; / RTI > For example, the first judgment information may include at least one of first similarity degree information, first registration possibility information, first violation information, and / or first other information. The first degree-of-similarity information is information indicating the degree of similarity of the object information with the intellectual property rights included in at least one of the first search result information, the second search result information, and / or the third search result information. The first registration possibility information is information indicating whether target information is registerable based on the first search result information, the second search result information, and / or the third search result information. The first infringement information is information indicating whether the target information violates specific intellectual property rights based on the first search result information, the second search result information, and / or the third search result information. The second server 8030 can transmit the generated first determination information to the first server 8020. [

Also, the first server 8020 may store at least one of the object information, the first recognition information, the second recognition information, the first search result information, the second search result information, the third search result information, and / The second determination information can be generated based on the second determination information. For example, the second judgment information may include at least one of second similarity degree information, second registration possibility information, second violation information, and / or second other information. The second degree-of-similarity information is information indicating the degree of similarity of the object information with the intellectual property rights included in at least one of the first search result information, the second search result information, and / or the third search result information. The second registration possibility information is information indicating whether the target information is registerable based on the first search result information, the second search result information, the third search result information, and / or the first determination information. The second infringement information is information indicating whether the target information violates specific intellectual property rights based on the first search result information, the second search result information, the third search result information, and / or the first judgment information.

Also, the first server 8020 may store the first information, the first recognition information, the second recognition information, the first search result information, the second search result information, the third search result information, the first determination information, and / And may transmit at least one of the determination information to the terminal 8010.

In addition, the terminal 8010 may receive the first information, the first recognition information, the second recognition information, the first search result information, the second search result information, the third search result information, the first determination information, and / At least one of them can be displayed.

9 is a diagram showing a control method of an exemplary electronic system.

The electronic system may include at least one of a terminal 9010, a first server 9020, a second server 9030, a third server 9040, and / or other servers. Hereinafter, the second server 9030 and / or the third server 9040 are independent from the first server 9020, but a part of the second server 9030 and / or the third server 9040 and / The whole can be integrated into the first server 9020. When integrated, the first server 9020 may perform some and / or all of the functions of the second server 9030 and / or the third server 9040.

The terminal 9010 may transmit the first object information and / or the second object information to the first server 9020. For example, at least one of the first object information and / or the second object information may include registered and / or unregistered intellectual property information. In addition, the first object information and / or the second object information may include information to be subjected to comparison, search, and judgment.

The first server 9020 may generate search information based on the first object information and / or the second object information. The first server 9020 may search the first server 9020, the third server 9040, and / or other servers based on the search information. The first server 9020 may receive and / or generate the first search result information corresponding to the first object information and / or the second object information stored in the first server 9020 based on the search information. Also, the first server 9020 can receive and / or generate the first search result information corresponding to the first target information and / or the second search target information stored in the third server 9040 based on the search information . Also, the first server 9020 can receive and / or generate the first search result information corresponding to the first target information and / or the second search target information stored in the other server based on the search information.

At least one of the first search result information, the second search result information, and the third search result information may include registered and / or unregistered intellectual property information, and may include other information.

The second server 9030 may receive the artificial intelligence and / or other information based on at least one of the first object information, the second object information, the first search result information, the second search result information, and / Technology can be used to generate the first judgment information. For example, the first judgment information may include at least one of first similarity degree information, first registration possibility information, first violation information, and / or first other information. The second server 9030 may transmit the first determination information to the first server 9020. [

The first server 9020 may generate an artificial intelligence function based on at least one of the first object information, the second object information, the first search result information, the second search result information, the third search result information, and / And / or other techniques to generate second determination information. For example, the second judgment information may include at least one of second similarity degree information, second registration possibility information, second violation information, and / or second other information. The first server 9020 may receive at least one of the first object information, the second object information, the first search result information, the second search result information, the third search result information, the first determination information, and / To the terminal 9010.

The terminal 9010 displays at least one of the first object information, the second object information, the first search result information, the second search result information, the third search result information, the first determination information, and / can do.

10 is a diagram showing an exemplary recommended item recommendation method.

Hereinafter, a method for recommending a designated item will be described in detail. The designated item recommendation method may be implemented by the first server, the second server, and / or the third server, and the following description will be focused on what is implemented by the first server.

The exemplary first server may determine at least one reference specification item based on input information received from the user electronic device (S1010). For example, the input information may include at least one of business type information related to a user's business type, similarity information, a designated product, and a designated service business. The user electronic device may include the above-described electronic device and / or terminal. At least one reference designation item indicates at least one designation item derived by filtering and / or analyzing the received input information, and may be a basic data for generating a recommendation designation item. At least one designated item is stored in a database of the first server or the like. The designated item may include at least one of the designated goods and / or designated service industry.

Then, the first server may generate at least one recommendation item set that can be recommended to the user based on the at least one reference designation item (S1020). The first server may generate at least one set of recommendation items using various methods such as a statistical method and / or a method using an artificial intelligence. A specific method will be described below. The recommended designation item set is information provided to the user by the first server, and the user can select a desired designation item based on the recommended designation item set. If at least one designation item is selected by the user, then the selected at least one designation item may be another reference designation item, and the first server may include at least one reference designation item selected by the user and / And generate a new set of at least one recommended recommendation item based on the generated at least one reference designation item.

The first server may then forward the at least one recommended set of items to the user's electronic device (S1030). The set of recommendation items can be communicated from the first server to the user's electronic device, and the user's electronic device can display the received set of recommended trouble items.

11 is a diagram illustrating a method of generating an exemplary recommended item set.

The exemplary first server may extract a plurality of designation information including a set of at least one designation items included in a plurality of trademark applications commonly including the at least one designation item. For example, when the reference designation item determined by the first server is 'Korean-up', the first server can search a plurality of registered trademarks and / or registered trademarks including 'Korean-up' as a designation item. The plurality of searched trademarks and / or registered trademarks each include at least one designated item. The designation item information may be a set of at least one designation item included in each application trademark and / or registered trademark. Accordingly, the first server can extract a plurality of designated item information for a plurality of searched trademarks and / or registered trademarks.

The first server may generate the at least one recommendation item set based on the at least one designation item included in the plurality of designation item information. The first server may apply a statistical method or artificial intelligence method based on at least one designation item included in the plurality of designation item information, and may generate at least one recommended designation item set as a result. As described above, the plurality of designation item information can be used as a basic data for analysis by the first server.

12 is a diagram illustrating another method of generating an exemplary recommendation item set.

The exemplary first server may apply at least one assignment item by applying a statistical method. For example, the first server may search a plurality of registered trademarks and / or registered trademarks including 'Korean-up' as a designated item, and extract a plurality of designated item information from the searched registered trademark and / or registered trademark . Each of the searched trademarks and / or trademarked designation item information may include at least one designation item. The first server may calculate an appearance frequency for at least one designation item included in the plurality of designation item information. The first server may then provide the user with at least one set of recommendation items based on the appearance frequency of the at least one designation items included in the plurality of designation information items.

For this, the first server may sort the at least one designated item included in the plurality of designation item information in descending order based on the appearance frequency (S1210) The at least one recommendation item set may be generated (S1220). For example, if at least one designated item created on the basis of the reference designation item "Korean-up" is "100 items", "200 food items", "200 food items" Restaurant chain up (230 times) ", the first server calculates" restaurant chain up (230 times) "," general food service (200 times) "," simple food service (150 times) " (100 times) ", respectively. Then, the first server can preferentially determine the set of recommended designation items as "restaurant chain-up (230 times)" having the highest appearance frequency.

13 is a diagram illustrating another method of generating an exemplary recommendation item set.

Hereinafter, a method for the first server to generate a recommendation item set using artificial intelligence will be described. The first server can find a set or pair of recommended designation items, which is a set of designation items commonly generated together in the plurality of designation item information corresponding to the searched trademark and / or registered trademark. The first server may store a plurality of designation information items including at least one designation item in a special structure called a pattern tree to search for a recommended designation item set. The first server searches the database twice and generates a recommended set of recommended products, which is very fast. A detailed description will be given below.

Referring to FIG. 5A, the first server may construct a pattern tree storing a set of at least one designated items included in the plurality of designated item information (S1310). The first server can store a plurality of designated item information in a data structure called a pattern tree. The pattern tree may include links linking similar and / or identical assignments to each other. In addition, the linked assignment items can be considered as a linked list. The pattern tree is used to store a set of frequently occurring designations, and the set can store the path of the tree. A set containing similar and / or identical assignments share parts of the tree, only the parts that divide the tree. One node can be defined as a single assignment item in the set and the number of times this assignment item is generated in sequence. Thus, a path can describe how many times it has occurred sequentially. The pattern tree may include a node link providing connection information between known similar and / or same designated items, and the node link may include information capable of quickly locating similar and / or same designated items. When the first server retrieves the database first, the first server can calculate the occurrence frequency of all designated items to construct the pattern tree.

The first server may use a degree of support with a minimum threshold. For example, the first server can regard a designation item that occurs less than the support degree as a designation item that is not frequent, and the designation item that occurs more than the support degree can be regarded as a frequent designation item. The first server can construct a pattern tree using frequent designation items.

In addition, the first server may mine the at least one recommended set item set based on the pattern tree (S1320). When the first server searches the database for the second time, the first server can access only frequent designation items. The first server can generate a set of recommendation items that can be provided to the user by using the pattern tree constructed with frequent designation items.

Referring to FIG. 5 (b), the identification number of the searched trademark and / or registered trademark and designation item information are shown. For example, identification numbers may be indicated by 1, 2, 3, etc. for simplicity of explanation. In addition, designation items can also be indicated as a, b, c, d, etc. for the sake of simplicity of explanation. Each application includes at least one designation item, for example, a designation item such as 'r, z, h, j, p' may be included in the application corresponding to the identification number 1. Thus, the first server can generate identification numbers and designation information for all searched trademarks and / or registered trademarks.

Referring to Figure (c), an exemplary pattern tree is shown. The pattern tree can be generated using designation items whose appearance frequency of the designation item is equal to or higher than the support degree. The pattern tree may include at least one node, and each node may include information on the name of the designation item and the appearance frequency. In addition, the pattern tree may include link information linking between the same or similar designated items.

14 is a diagram showing a method of constructing an exemplary pattern tree.

The first server may generate a data structure including information on nodes and links constituting the pattern tree (S1410). To build a tree, a storage space is required to store the tree. The first server can create a class that stores and / or defines each node for the tree. For example, the class may include: name information indicating the name of the node; frequency information indicating the frequency of occurrence of the node; node link information including information linking similar and / or the same specified item; Parent information including information for the parent node, information for referring to the child node in the tree, or child information for storing the child node.

Thus, the first server can generate a data structure including information on nodes and links constituting the pattern tree by using the class. The first server can construct a pattern tree based on the plurality of designation item information and the support degree including at least one designation item. The first server can calculate the frequency of each designated item while reading all specified items in the specified item information. The server can store the calculated frequentities in the header table.

In addition, the first server may extract a plurality of sets of candidate designation items including the at least one designation item having an appearance frequency higher than a predetermined degree of support among at least designation items included in each trademark application information (S1420) . For example, a set of candidate designation items may indicate a designation item in which the frequency of occurrence is higher than or equal to one of the at least one designation items included in each of the application trademarks and / or registered trademarks. The first server can delete the designation items generated lower than the support degree while looking at the header table and extract the remaining designation items that occur more than the support degree as the candidate designation item sets. The first server may not proceed any further unless there is a frequent assignment item. The first server can then slightly extend the header table to store the number and indicator for each type of assignment. And the first server may create a base node that contains an empty set. The first server can repeat the set of designated items repeatedly. In this case, only frequent designation items can be read.

In addition, the first server may sort the at least one designated item included in the plurality of sets of candidate designation items in descending order based on the appearance frequency (S1430). In addition, the first server may construct the pattern tree based on the plurality of sets of candidate designation items including the sorted at least one designation item (S1440).

15 is another diagram showing a method of constructing an exemplary pattern tree.

Referring to Figure (a), an exemplary set of ordered items and a set of ordered candidate set items are shown. The first server can calculate the frequent occurrence rate for all the designated items included in each item of designation information. Then, the first server removes designated items having frequent occurrence less than the support degree, and extracts only designated items having a frequent occurrence degree of support or more as a candidate designated item.

The first server adds this candidate set of items to the existing path if each candidate set of items already exists. If the candidate set item does not exist, a new path is created. Each assignment item information is a set and may not be arranged in order. That is, when there are {z, x, y} and {y, z, r}, similar and / or identical assignments are required in order to cause these sets to overlap. To solve this, you must sort each set before adding it to the tree. The first server can sort the candidate designation item using the frequent occurrence of the designation item.

Specifically, the first server may sort the candidate designation items extracted in the respective item information items in descending order based on the frequent occurrence degree. For example, the designated item set corresponding to the identification information 1 may include 'r, z, h, j, p', and the first server may sort the 'z, r' can do. Thus, the first server can filter and sort the set of designated items based on the frequency.

Referring to FIG. 5B, a process for constructing a pattern tree based on a set of candidate designation items arranged by the first server is shown. After the first server filters and then arranges the set of designated items, the tree can be constructed using the sorted set of candidate items. The first server can start building the tree with an empty set, and add a set of candidate assignments sorted to this set. A set of filtered and ordered candidate assignments is added successively to the tree, increasing the number of existing elements in the tree and extending the branches if the tree does not have that element.

For example, the first server may create a vacant node and add a set of candidate designation items corresponding to the identification information 1 to 6 to the pattern tree. The first server can add a set of candidate designation items including the designation items having the highest frequency to the pattern tree first and add the next set of candidate designation items to the pattern tree in the order of the most frequent ones.

Referring to FIG. 5C, a pattern tree including a header table is shown. The header table may contain information about the designation items for which the frequent occurrence is more than or equal to the supportability, and information about the frequency of the designation items. The header table provides quick access to all the designations provided in the pattern tree. To this end, the header table may contain starting point information for finding similar and / or the same designation items. Thus, in addition to storing the starting point information (or indicator), the header table can be used to track the total number of all element types in the pattern tree. Each node included in the pattern tree may include information on a designated item in each node and information on the frequency of the designated item. Further, each node may include link information for finding similar and / or the same designation items.

16 is a diagram illustrating a method of mining an exemplary set of recommended items.

The exemplary first server may generate at least one set of recommendation items that can be recommended to the user based on the constructed pattern tree. This will be described in detail below.

The first server may generate conditional pattern base information for each designated item included in the header table, the conditional pattern base information including a set of at least one prior path for the end portion including the designated item to be searched from the pattern tree (S1610). For example, a dictionary path can be path information between the designation you are looking for in the pattern tree and the beginning of the pattern tree. The dictionary path can be used to create a pattern tree.

The first server may further include a condition pattern tree including at least one designation item having a frequency of occurrence of the support degree or higher among the at least one designation items included in the condition pattern base information for each designation item included in the header table, (S1620). For example, the first server may build a conditional pattern tree based on the conditional pattern base information, starting from the bottom of the header table. That is, the first server can construct a conditional pattern tree based on the conditional pattern base information starting from the designated item having the lowest frequency.

In addition, the first server may generate at least one recommended set item set in which a subset of the conditional pattern tree and each designated item included in the header table are combined (S1630). The first server may then provide the generated set of at least one recommendation item to the user terminal. At this time, the first server may additionally perform filtering and sorting on at least one designated item included in the generated set of recommended designation items, and provide the selected items to the user terminal. For example, the first server may preferentially provide the user terminal with a designation item or recommendation designation set having a high frequency.

Figure 17 is another diagram illustrating a method of mining an exemplary set of recommended entries.

Referring to Figure (a), a condition pattern tree is constructed. For example, the first server may construct a conditional pattern tree based on the designated item 't' having the lowest frequency. The conditional pattern base information corresponding to the designated item 't' may be '{z, x, y, s: 2}', '{z, x, y, r: 1}'. 'z', 'x', 'y', 'r' and 'z, x, y, s' may be a prior path and '2', '1' The first server can remove the designation items 's' and 'r' having the frequentness less than '3' based on the support degree '3'. Then, the first server may sequentially add {y, x, z: 2} and {y, x, z: 1} to the conditional pattern tree which is an empty set.

Referring to FIG. 5B, a set of recommendation items generated by the condition pattern tree is shown. For example, the dictionary path for the assignment item 't' may be {z, x, y, s}, {z, x, y, r}. Each of these pre-paths may have a number (or frequency) associated therewith. This number can be the same number as the start specification item. This number can be defined as the number of 't' s on each path.

The conditional pattern tree may be composed of designation items whose frequencies are equal to or higher than those of support items among all designation items included in the conditional pattern base information. For example, the conditional pattern tree for the assignment item 't' may consist of the items 'z', 'x', and 'y'.

The recommendation item set may be a combination of a subset of the condition pattern tree and each designation item included in the header table. For example, a set of recommendation items based on a designation item 't' may be a combination of a subset of {z, x, y} and a designation item {t}. That is, the set of recommended items based on the designated item 't' is {t, z}, {t, x}, {t, y}, {t}, {t, , y}, {t, z, y}, {t, z, x, y}.

In this way, the first server can generate a set of recommended designation items for all designation items included in the header table. The first server may then provide the generated set of recommended entries to the user electronics.

In addition, the first server may receive user identification information including information on the mark of the trademark from the user electronic device. And, the first server may be configured such that, in the step of generating the at least one recommended recommendation item set, if the mark information for at least one trademark application included in the plurality of trademark applications is similar to the user's identification information, A designation item similar to at least one designation item included in the trademark application of the present invention may be excluded from the recommended designation item set.

The techniques disclosed herein may include a computer program stored on a medium to perform the specified product recommendation method and the intellectual property search method described above in combination with hardware.

In addition, the techniques disclosed herein may be implemented by any one of a first server, a second server, and / or a third server. An exemplary first server may include a communication module, a processor executing the instructions, and a computer readable memory having stored thereon a program for executing the instructions on the electronic device, wherein the details of the first server are as described above Server, or electronic device. Exemplary instructions may include determining at least one reference designation based on input information received from a user electronic device; Generating at least one recommendation item set that can be recommended to a user based on the at least one reference designation item; And forwarding the at least one set of recommendation items to a user electronics device.

Further, according to the embodiments disclosed herein, the above-described method can be implemented as a code that can be read by a processor on a medium on which the program is recorded. Examples of the medium that can be read by the processor include a ROM, a RAM, a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.

The above-described electronic device can be applied to a configuration and a method of the embodiments described above in a limited manner, but the embodiments can be configured such that all or some of the embodiments are selectively combined so that various modifications can be made It is possible.

In the foregoing, preferred embodiments of the present invention have been described with reference to the accompanying drawings. Here, terms and words used in the present specification and claims should not be construed as limited to ordinary or dictionary terms, and should be construed in a sense and concept consistent with the technical idea of the present specification.

The scope of the present specification is not limited to the embodiments disclosed in this specification, and the specification can be modified, changed, or improved in various forms within the scope of the present invention and the claims.

4010: terminal 4020: first server
4030: second server 4040: third server

Claims (10)

Determining at least one reference designation item based on input information received from a user electronic device;
Generating at least one recommendation item set that can be recommended to a user based on the at least one reference designation item; And
Forwarding the at least one set of recommendation items to a user electronic device
How to recommend the containing assignment. The method according to claim 1,
Wherein the input information includes at least one of business type information related to a business type of a user, similarity group information, a designated product, and a designated service business. The method according to claim 1,
Wherein the step of generating the at least one recommendation item set comprises:
Extracting a plurality of designation information items including a set of at least one designation items included in a plurality of trademark applications commonly including the at least one reference designation item; And
The step of generating the at least one recommended designation item set based on the at least one designation item included in the plurality of designation item information
How to recommend the containing assignment. The method of claim 3,
Wherein the generating of the at least one recommended designation item set based on the at least one designation item commonly included in the plurality of designation item information comprises:
And arranging the at least one designation item included in the plurality of designation item information in descending order based on the appearance frequency and generating the at least one recommended designation item set in the ordered order. The method of claim 3,
Wherein the generating of the at least one recommended designation item set based on the at least one designation item commonly included in the plurality of designation item information comprises:
Constructing a pattern tree storing a set of at least one designation items included in the plurality of designation item information; And
And mining the set of at least one recommendation item based on the pattern tree
How to recommend the containing assignment. 6. The method of claim 5,
Wherein the step of constructing the pattern tree comprises:
Generating a data structure including information on nodes and links constituting the pattern tree;
Extracting a plurality of sets of candidate designation items including the at least one designation item having an appearance frequency of at least a predetermined degree of support among at least designation items included in each trademark application information;
Arranging the at least one designation item included in the plurality of candidate designation item sets in descending order based on the appearance frequency; And
And constructing the pattern tree based on the plurality of candidate designation items sets including the aligned at least one designation item
How to recommend the containing assignment. The method according to claim 6,
Wherein the step of mining the at least one recommended item set based on the pattern tree comprises:
Generating condition pattern base information for each designation item included in the header table, the condition pattern base information including a set of at least one preliminary route for the end portion including the designation item to be searched from the pattern tree;
Constructing a conditional pattern tree including at least one designation item having an appearance frequency of the degree of support or higher among at least one designation items included in the conditional pattern base information for each designation item included in the header table; And
Generating at least one set of recommended designation items in which a subset of the conditional pattern tree and each designation item included in the header table are combined
How to recommend the containing assignment. The method of claim 3,
Further comprising the step of receiving, from the user electronic device, user identification information including information on the mark of the trademark,
Wherein the step of generating the at least one recommendation item set comprises:
If the mark information for at least one trademark application included in the plurality of trademark applications is similar to the user's mark information, a designation item similar to at least one designation item included in the at least one trademark application, How to nominate items to exclude from. A computer program stored on a medium for execution of the method of any one of claims 1 to 7 in combination with hardware. Communication module;
A processor for executing instructions; And
A computer readable memory having stored thereon a program for causing the electronic device to execute the instructions,
The instructions,
Determining at least one reference designation item based on input information received from a user electronic device;
Generating at least one recommendation item set that can be recommended to a user based on the at least one reference designation item; And
Forwarding the at least one set of recommendation items to a user electronic device
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