KR102470815B1 - Server for providing service for popular voting and method for operation thereof - Google Patents

Abstract

Various embodiments of the present invention relate to a server providing a popularity voting service and an operation method thereof.
A server and its operating method according to various embodiments of the present invention, based on the number of voters participating, when users participate in voting in excess of a certain number, prioritize the number of votes and give final scores for the candidates. and if less than a certain number of users participate in the vote, an artificial intelligence model may be introduced to calculate the final score for the candidates by prioritizing the qualitative aspects of the candidates.

Description

Server providing popularity voting service and its operating method {SERVER FOR PROVIDING SERVICE FOR POPULAR VOTING AND METHOD FOR OPERATION THEREOF}

Various embodiments of the present invention relate to a server providing a popularity voting service and an operation method thereof.

With the development of communication means, the offline voting method for candidates is changing to the online voting method. As voting is conducted online, unnecessary costs can be reduced, and since voting can be done simply and quickly using a PC or smartphone, the number of people participating in online voting on preferred topics is gradually increasing. are doing

No. 10-1999-0068301 (1999.09.06) No. 10-2008-0082016 (2008.09.11)

In the case of simply evaluating candidates with only quantitative aspects (e.g., the number of votes), the qualitative aspects of the candidate (e.g., the social influence of the candidate or the reputation of the candidate) are not evaluated, and a comprehensively fair review is performed. There is a risk of not being able to perform

A server and its operating method according to various embodiments of the present invention, based on the number of voters participating, when users participate in voting in excess of a certain number, prioritize the number of votes and give final scores for the candidates. and if less than a certain number of users participate in the vote, an artificial intelligence model may be introduced to calculate the final score for the candidates by prioritizing the qualitative aspects of the candidates.

According to various embodiments, a server providing a popularity voting service includes a communication interface and a processor, wherein the processor includes candidate voting data for selecting a plurality of candidates from a plurality of user devices through the communication interface, and the By receiving candidate review data for evaluating a plurality of candidates and performing morphological analysis and sentiment analysis on the candidate review data, positive and negative evaluations included in the candidate review data are determined based on predetermined screening criteria. Calculate emotion scores for the plurality of candidates by digitizing them, analyze social network relationship information according to the subscription relationship of the plurality of candidates and the quotation relationship of contents on social media, and based on the social network relationship information, An average exposure score obtained by indexing the average number of exposures per user by other users exposed to the contents of a plurality of candidates is calculated, and based on the average exposure score and the number of other users exposed to the contents of the plurality of candidates. Influence indexes of the plurality of candidates are calculated, and when the number of the plurality of user devices participating in voting exceeds a predetermined number, a score reflection ratio of the candidate voting data is set to a first ratio, and the emotional score Calculating final scores for the plurality of candidates by setting the score reflection ratio to a second ratio lower than the first ratio, and setting the score reflection ratio of the influence index to a third ratio lower than the second ratio, and when the number of the plurality of user devices is less than or equal to a predetermined number, setting a score reflection ratio of the emotion score to a first ratio, and setting a score reflection ratio of the influence index to a second ratio lower than the first ratio; The final score may be calculated by setting a score reflection ratio of the candidate voting data to a third ratio lower than the second ratio.

The processor determines the plurality of candidates by using Equation 1 based on a final review score (KR1) for a first review criterion and a final review score (KR2) for a second review criterion among the predetermined review criteria. A server that provides a popularity voting service, set to calculate a sentiment score (ReviewSentimentScore) for .

Each element of Equation 1 is a first review (FR) including a keyword representing the first review criterion, a first score (FS) derived from positive/negative scores of the first review, and the second review criterion. It may indicate the second review (SR) including the keyword indicating, and the second score (SS) derived from the positive/negative score of the second review.

The processor calculates the influence factor by multiplying the average exposure score per user by the number of other users exposed to the contents of the plurality of candidates based on Equations 2, 3, and 4. A set popularity voting service can be provided.

UE1i in Equation 2 represents the total number of exposures of all contents created by candidate i, and is expressed as the sum of the number of exposed users (|Ti,x|) of individual contents (x1, x2, ..., xn) created by candidate i, , DFi in Equation 3 is a set of users directly exposed to content x, which means a set of followers of candidate i, and RFx is a set of users indirectly exposed to content x, which means a set of followers of users who quote specific content x, Rx means a set of users who retweet the content x, UE2i in Equation 4 is the number of other users exposed to the content created by candidate i, and the individual content created by candidate i (x1, x2, ..., xn ) can be expressed as the number of users of the union of the set of exposed users (Ti,x).

The processor may provide a popularity voting service configured to calculate the influence factor based on Equations 5 and 6 below.

UE1/UE2 in Equation 5 means the average number of exposures per other user based on other users exposed to the content of the candidate, and Equation 6 may be a form obtained by taking the natural logarithm of the number of exposures in Equation 5.

The processor may provide a popularity voting service configured to calculate an influence index using Equation 7. UE1i is the total exposure count of all content created by candidate i, UE2i is the number of other users exposed to content created by candidate i, and (e-1) is a correction value to prevent the influence index from being calculated as 0, e is a natural constant.

According to various embodiments of the present invention, it is possible to adjust the ratio of screening criteria reflected in the final score according to the number of users who participated in the vote, as well as qualitative aspects of candidates (e.g., candidates) using artificial intelligence rather than humans. It is possible to provide a popularity voting service that can conduct a fair screening by considering the social influence of the candidate or the reputation of the candidate).

The effects obtainable in the present invention are not limited to the effects mentioned above, and other effects not mentioned can be clearly understood by those skilled in the art from the description below. will be.

Also other aspects as described above, features and benefits of certain preferred embodiments of the present invention will become more apparent from the following description taken in conjunction with the accompanying drawings.
1 shows a block diagram of an electronic device and network according to various embodiments of the present invention.
2 is a block diagram of an electronic device according to various embodiments.
3 is a block diagram of program modules according to various embodiments.
4 is a flowchart illustrating a method of providing a popularity voting service by an electronic device, according to various embodiments.
5 illustrates candidate voting data in which each user device has voted a plurality of votes for specific candidates, according to various embodiments.
6 is a diagram illustrating an example of calculating a set of users exposed to content A when there is only direct exposure to content A, according to various embodiments.
7 is a diagram illustrating a user set exposed to content B when indirect exposure exists, according to various embodiments.
8 is a diagram illustrating an example of measuring the number of exposures UE1 and UE2 for a specific candidate according to various embodiments.
It should be noted that throughout the drawings, like reference numbers are used to show the same or similar elements, features and structures.

Hereinafter, various embodiments of this document will be described with reference to the accompanying drawings. Examples and terms used therein are not intended to limit the technology described in this document to specific embodiments, and should be understood to include various modifications, equivalents, and/or substitutes of the embodiments. In connection with the description of the drawings, like reference numerals may be used for like elements. Singular expressions may include plural expressions unless the context clearly dictates otherwise. In this document, expressions such as "A or B" or "at least one of A and/or B" may include all possible combinations of the items listed together. Expressions such as "first," "second," "first," or "second," may modify the corresponding components regardless of order or importance, and are used to distinguish one component from another. It is used only and does not limit the corresponding components. When a (e.g., first) element is referred to as being "(functionally or communicatively) coupled to" or "connected to" another (e.g., second) element, that element refers to the other (e.g., second) element. It may be directly connected to the component or connected through another component (eg, a third component).

In this document, "configured (or configured to)" means "suitable for," "having the ability to," "changed to," depending on the situation, for example, hardware or software. ," can be used interchangeably with "made to," "capable of," or "designed to." In some contexts, the expression "device configured to" can mean that the device is "capable of" in conjunction with other devices or components. For example, the phrase "a processor configured (or configured) to perform A, B, and C" may include a dedicated processor (eg, embedded processor) to perform the operation, or by executing one or more software programs stored in a memory device. , may mean a general-purpose processor (eg, CPU or application processor) capable of performing corresponding operations.

Electronic devices according to various embodiments of the present document include, for example, a smart phone, a tablet PC, a mobile phone, a video phone, an e-book reader, a desktop PC, a laptop PC, a netbook computer, a workstation, a server, a PDA, and a PMP. It may include at least one of a portable multimedia player, an MP3 player, a medical device, a camera, or a wearable device. A wearable device may be in the form of an accessory (e.g. watch, ring, bracelet, anklet, necklace, eyeglasses, contact lens, or head-mounted-device (HMD)), integrated into textiles or clothing (e.g. electronic garment); In some embodiments, the electronic device may include, for example, a television, a digital video disk (DVD) player, Audio, refrigerator, air conditioner, vacuum cleaner, oven, microwave, washing machine, air purifier, set top box, home automation control panel, security control panel, media box (e.g. Samsung HomeSync ^TM , Apple TV ^TM , or Google TV ^TM ) , a game console (eg, Xbox ^TM , PlayStation ^TM ), an electronic dictionary, an electronic key, a camcorder, or an electronic picture frame.

In another embodiment, the electronic device may include various types of medical devices (e.g., various portable medical measuring devices (such as blood glucose meter, heart rate monitor, blood pressure monitor, or body temperature monitor), magnetic resonance angiography (MRA), magnetic resonance imaging (MRI), CT (computed tomography), imager, or ultrasonicator, etc.), navigation device, global navigation satellite system (GNSS), EDR (event data recorder), FDR (flight data recorder), automobile infotainment device, marine electronic equipment (e.g. navigation devices for ships, gyrocompasses, etc.), avionics, security devices, head units for vehicles, industrial or home robots, drones, ATMs in financial institutions, point of sale (POS) in stores of sales), or IoT devices (eg, light bulbs, various sensors, sprinkler devices, fire alarms, thermostats, street lights, toasters, exercise equipment, hot water tanks, heaters, boilers, etc.). According to some embodiments, the electronic device may be a piece of furniture, a building/structure or a vehicle, an electronic board, an electronic signature receiving device, a projector, or various measuring devices (eg, water, electricity, gas, radio wave measuring device, etc.). In various embodiments, the electronic device may be flexible or a combination of two or more of the various devices described above. An electronic device according to an embodiment of the present document is not limited to the aforementioned devices. In this document, the term user may refer to a person using an electronic device or a device using an electronic device (eg, an artificial intelligence electronic device).

Referring to FIG. 1 , an electronic device 101 in a network environment 100 in various embodiments is described. The electronic device 101 may include a bus 110, a processor 120, a memory 130, an input/output interface 150, a display 160, and a communication interface 170. In some embodiments, the electronic device 101 may omit at least one of the components or may additionally include other components. Bus 110 may include circuitry that connects components 110-170 to each other and communicates (eg, control messages or data) between components. The processor 120 may include one or more of a central processing unit, an application processor, or a communication processor (CP). The processor 120 may, for example, execute calculations or data processing related to control and/or communication of at least one other component of the electronic device 101 .

Memory 130 may include volatile and/or non-volatile memory. The memory 130 may store, for example, commands or data related to at least one other component of the electronic device 101 . According to one embodiment, memory 130 may store software and/or programs 140 . The program 140 may include, for example, a kernel 141, middleware 143, an application programming interface (API) 145, and/or an application program (or “application”) 147, and the like. . At least part of the kernel 141, middleware 143, or API 145 may be referred to as an operating system. Kernel 141, for example, includes system resources (eg, middleware 143, API 145, or application program 147) used to execute operations or functions implemented in other programs (eg, middleware 143, API 145, or application program 147). : The bus 110, the processor 120, or the memory 130, etc.) can be controlled or managed. In addition, the kernel 141 may provide an interface capable of controlling or managing system resources by accessing individual components of the electronic device 101 from the middleware 143, API 145, or application program 147. can

The middleware 143 may perform an intermediary role so that, for example, the API 145 or the application program 147 communicates with the kernel 141 to exchange data. Also, the middleware 143 may process one or more task requests received from the application program 147 according to priority. For example, the middleware 143 may use system resources (eg, the bus 110, the processor 120, or the memory 130, etc.) of the electronic device 101 for at least one of the application programs 147. Prioritize and process the one or more work requests. The API 145 is an interface for the application 147 to control functions provided by the kernel 141 or the middleware 143, for example, at least for file control, window control, image processing, or text control. It can contain one interface or function (eg command). The input/output interface 150 transmits, for example, a command or data input from a user or other external device to other component(s) of the electronic device 101, or other components of the electronic device 101 ( s) may output commands or data received from the user or other external devices.

The display 160 may be, for example, a liquid crystal display (LCD), a light emitting diode (LED) display, an organic light emitting diode (OLED) display, a microelectromechanical system (MEMS) display, or an electronic paper display. can include The display 160 may display various types of content (eg, text, image, video, icon, and/or symbol) to the user. The display 160 may include a touch screen, and may receive, for example, a touch, gesture, proximity, or hovering input using an electronic pen or a part of the user's body. The communication interface 170 establishes communication between the electronic device 101 and an external device (eg, the first external electronic device 102 , the second external electronic device 104 , or the server 106 ). can For example, the communication interface 170 may be connected to the network 162 through wireless or wired communication to communicate with an external device (eg, the second external electronic device 104 or the server 106).

Wireless communication is, for example, LTE, LTE-A (LTE Advance), CDMA (code division multiple access), WCDMA (wideband CDMA), UMTS (universal mobile telecommunications system), WiBro (Wireless Broadband), or GSM (Global System for Mobile Communications) may include cellular communication using at least one of the like. According to one embodiment, wireless communication, for example, WiFi (wireless fidelity), Bluetooth, Bluetooth Low Energy (BLE), Zigbee, near field communication (NFC), magnetic secure transmission (Magnetic Secure Transmission), radio It may include at least one of a frequency (RF) and a body area network (BAN). According to one embodiment, wireless communication may include GNSS. The GNSS may be, for example, a Global Positioning System (GPS), a Global Navigation Satellite System (Glonass), a Beidou Navigation Satellite System (hereinafter “Beidou”) or Galileo, the European global satellite-based navigation system. Hereinafter, in this document, "GPS" may be used interchangeably with "GNSS". Wired communication may include, for example, at least one of universal serial bus (USB), high definition multimedia interface (HDMI), recommended standard 232 (RS-232), power line communication, or plain old telephone service (POTS). have. Network 162 may include at least one of a telecommunication network, for example, a computer network (eg, LAN or WAN), the Internet, or a telephone network.

Each of the first and second external electronic devices 102 and 104 may be the same as or different from the electronic device 101 . According to various embodiments, all or part of operations executed in the electronic device 101 may be executed in one or more electronic devices (eg, the electronic devices 102 and 104, or the server 106). According to this, when the electronic device 101 needs to perform a certain function or service automatically or upon request, the electronic device 101 instead of or in addition to executing the function or service by itself, at least some functions related thereto may request another device (eg, the electronic device 102 or 104 or the server 106). The additional function may be executed and the result may be transmitted to the electronic device 101. The electronic device 101 may provide the requested function or service by processing the received result as it is or additionally. For example, cloud computing, distributed computing, or client-server computing technologies may be used.

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2 is a block diagram of an electronic device 201 according to various embodiments. The electronic device 201 may include, for example, all or part of the electronic device 101 shown in FIG. 1 . The electronic device 201 includes one or more processors (eg, APs) 210, a communication module 220, a subscriber identification module 224, a memory 230, a sensor module 240, an input device 250, a display 260, interface 270, audio module 280, camera module 291, power management module 295, battery 296, indicator 297, and motor 298. Processor The processor 210 may control a plurality of hardware or software components connected to the processor 210 by driving, for example, an operating system or an application program, and may perform various data processing and calculations. ) may be implemented as, for example, a system on chip (SoC) According to one embodiment, the processor 210 may further include a graphic processing unit (GPU) and/or an image signal processor. 210 may include at least some of the components (eg, the cellular module 221) shown in Fig. 2. The processor 210 may include at least one of the other components (eg, non-volatile memory). Received commands or data may be loaded into volatile memory for processing, and resultant data may be stored in non-volatile memory.

It may have the same or similar configuration as the communication module 220 (eg, the communication interface 170). The communication module 220 may include, for example, a cellular module 221, a WiFi module 223, a Bluetooth module 225, a GNSS module 227, an NFC module 228 and an RF module 229. have. The cellular module 221 may provide, for example, a voice call, a video call, a text service, or an Internet service through a communication network. According to one embodiment, the cellular module 221 may identify and authenticate the electronic device 201 within a communication network using the subscriber identity module (eg, SIM card) 224 . 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). According to some embodiments, at least some (eg, two or more) of the cellular module 221, the WiFi module 223, the Bluetooth module 225, the GNSS module 227, or the NFC module 228 are one integrated chip (IC) or within an IC package. The RF module 229 may transmit and receive communication signals (eg, RF signals), for example. The RF module 229 may include, for example, a transceiver, a power amp module (PAM), a frequency filter, a low noise amplifier (LNA), or an antenna. According to another embodiment, at least one of the cellular module 221, the WiFi module 223, the Bluetooth module 225, the GNSS module 227, or the NFC module 228 transmits and receives an RF signal through a separate RF module. can The subscriber identification module 224 may include, for example, a card or an embedded SIM including a subscriber identification module, and may include unique identification information (eg, integrated circuit card identifier (ICCID)) or subscriber information (eg, IMSI). (international mobile subscriber identity)).

The memory 230 (eg, the memory 130) may include, for example, an internal memory 232 or an external memory 234. The built-in memory 232 may include, for example, volatile memory (eg, DRAM, SRAM, SDRAM, etc.), non-volatile memory (eg, OTPROM (one time programmable ROM), PROM, EPROM, EEPROM, mask ROM, flash ROM). , a flash memory, a hard drive, or a solid state drive (SSD).The external memory 234 may include a flash drive, for example, a compact flash (CF) or secure digital (SD). ), Micro-SD, Mini-SD, extreme digital (xD), multi-media card (MMC), or memory stick, etc. The external memory 234 is functionally compatible with the electronic device 201 through various interfaces. can be physically or physically connected.

The sensor module 240 may, for example, measure a physical quantity or detect an operating state of the electronic device 201 and convert the measured or sensed information into an electrical signal. The sensor module 240 includes, for example, a gesture sensor 240A, a gyro sensor 240B, an air pressure sensor 240C, a magnetic sensor 240D, an acceleration sensor 240E, a grip sensor 240F, and a proximity sensor ( 240G), color sensor (240H) (e.g. RGB (red, green, blue) sensor), bio sensor (240I), temperature/humidity sensor (240J), light sensor (240K), or UV (ultra violet) ) may include at least one of the sensors 240M. Additionally or alternatively, the sensor module 240 may include, for example, an e-nose sensor, an electromyography (EMG) sensor, an electroencephalogram (EEG) sensor, an electrocardiogram (ECG) sensor, It may include an IR (infrared) sensor, an iris sensor, and/or a fingerprint sensor. The sensor module 240 may further include a control circuit for controlling one or more sensors included therein. In some embodiments, the electronic device 201 further includes a processor configured to control the sensor module 240, either as part of the processor 210 or separately, so that while the processor 210 is in a sleep state, The sensor module 240 may be controlled.

The input device 250 may include, for example, a touch panel 252 , a (digital) pen sensor 254 , a key 256 , or an ultrasonic input device 258 . The touch panel 252 may use at least one of, for example, a capacitive type, a pressure-sensitive type, an infrared type, or an ultrasonic type. Also, 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 (digital) pen sensor 254 may be, for example, part of a touch panel or may include a separate recognition sheet. Keys 256 may include, for example, hardware buttons, optical keys, or keypads. The ultrasonic input device 258 may detect ultrasonic waves generated from an input tool through a microphone (eg, the microphone 288) and check data corresponding to the detected ultrasonic waves.

The display 260 (eg, the display 160) may include a panel 262, a hologram device 264, a projector 266, and/or a control circuit for controlling them. Panel 262 may be implemented to be flexible, transparent, or wearable, for example. The panel 262 may include the touch panel 252 and one or more modules. According to one embodiment, the panel 262 may include a pressure sensor (or force sensor) capable of measuring the strength of a user's touch. The pressure sensor may be implemented integrally with the touch panel 252 or may be implemented as one or more sensors separate from the touch panel 252 . The hologram device 264 may display a 3D image in the air using interference of light. The projector 266 may display an image by projecting light onto a screen. The screen may be located inside or outside the electronic device 201 , for example. Interface 270 may include, for example, HDMI 272, USB 274, optical interface 276, or D-sub (D-subminiature) 278. Interface 270 may be included in, for example, communication interface 170 shown in FIG. 1 . Additionally or alternatively, the interface 270 may include, for example, a mobile high-definition link (MHL) interface, an SD card/multi-media card (MMC) interface, or an infrared data association (IrDA) compliant interface. have.

The audio module 280 may, for example, convert a sound and an electrical signal in both directions. At least some components of the audio module 280 may be included in the input/output interface 145 shown in FIG. 1 , for example. The audio module 280 may process sound information input or output through, for example, the speaker 282, the receiver 284, the earphone 286, or the microphone 288. The camera module 291 is, for example, a device capable of capturing still images and moving images, and according to one embodiment, one or more image sensors (eg, a front sensor or a rear sensor), a lens, and an image signal processor (ISP) , or a flash (eg, LED or xenon lamp, etc.). The power management module 295 may manage 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 IC, or a battery or fuel gauge. A PMIC may have a wired and/or wireless charging method. The wireless charging method includes, for example, a magnetic resonance method, a magnetic induction method, or an electromagnetic wave method, and may further include an additional circuit for wireless charging, for example, a coil loop, a resonance circuit, or a rectifier. have. The battery gauge may measure, for example, the remaining capacity of the battery 296, voltage, current, or temperature during charging. Battery 296 may include, for example, a rechargeable battery and/or a solar cell.

The indicator 297 may indicate a specific state of the electronic device 201 or a part thereof (eg, the processor 210), for example, a booting state, a message state, or a charging state. The motor 298 may convert electrical signals into mechanical vibrations and generate vibrations or haptic effects. The electronic device 201 is, for example, a mobile TV support device capable of processing media data according to standards such as digital multimedia broadcasting (DMB), digital video broadcasting (DVB), or mediaFlo ^TM (e.g., : GPU) may be included. Each of the components described in this document may be composed of one or more components, and the name of the corresponding component may vary depending on the type of electronic device. In various embodiments, an electronic device (eg, the electronic device 201) is configured as a single entity by omitting some components, further including additional components, or combining some of the components. The functions of the previous corresponding components may be performed identically.

In various embodiments of the present disclosure, the electronic device 201 (or the electronic device 101) may include a housing including a front surface, a rear surface, and a side surface surrounding a space between the front surface and the rear surface. A touch screen display (eg, the display 260) is disposed within the housing and may be exposed through the front surface. A microphone 288 is disposed within the housing and may be exposed through a portion of the housing. At least one speaker 282 is disposed within the housing and may be exposed through another part of the housing. A hardware button (eg, key 256) may be located on another part of the housing or configured to display on the touchscreen display. A wireless communication circuit (eg, the communication module 220) may be located in the housing. The processor 210 (or processor 120) is located in the housing and may be electrically connected to the touch screen display, the microphone 288, the speaker 282, and the wireless communication circuit. The memory 230 (or the memory 130 ) may be located in the housing and electrically connected to the processor 210 .

In various embodiments of the present invention, the memory 230 is set to store a first application program including a first user interface for receiving text input, and the memory 230, when executed, the The processor 210 stores instructions that cause a first operation and a second operation to be performed, and the first operation is performed through the button while the first user interface is not displayed on the touch screen display. Receive a first type of user input, and after receiving the first type of user input, receive a first user utterance through the microphone 288, automatic speech recognition (ASR) and intelligence First data for the first user utterance is provided to an external server including an intelligence system, and after providing the first data, the intelligence system responds to the first user utterance from the external server. Receives at least one command for performing a task generated by, and the second operation receives the first user input through the button while the first user interface is displayed on the touch screen display, , After receiving the first type of user input, receiving a second user speech through the microphone 288, providing second data for the second user speech to the external server, and After providing data, the server receives data about text generated by the automatic speech recognition from the second user utterance, but not commands generated by the intelligent system, and the first user You can input the text into the interface.

In various embodiments of the present invention, the button may include a physical key located on the side of the housing.

In various embodiments of the present invention, the first type of user input is after pressing the button once, pressing the button twice, pressing the button three times, or pressing the button once. It can be either a held press, or a two-time press and hold press on the button.

In various embodiments of the present invention, the instructions may further cause the processor to display the first user interface along with a virtual keyboard. The button may not be part of the virtual keyboard.

In various embodiments of the invention, the instructions further cause the processor 210 to receive, from the external server, data for text generated by ASR from the first user utterance within the first action. can cause

In various embodiments of the present invention, the first application program may include at least one of a note application program, an e-mail application program, a web browser application program, or a calendar application program.

In various embodiments of the present invention, the first application program includes a message application, and the instructions cause the processor 210 to, if a selected period of time after inputting the text, exceed the wireless communication circuitry. It can be further caused to transmit automatically input text through.

In various embodiments of the present invention, the instructions further cause the processor 210 to perform a third operation, wherein the third operation is while displaying the first user interface on the touchscreen display. , Receives a second type of user input through the button, receives a third user speech through the microphone after receiving the second type of user input, and responds to the third user speech by the external server. After providing the third data, at least one command for performing a task generated by the intelligent system in response to the third user utterance may be received from the external server. have.

In various embodiments of the present invention, the instructions further cause the processor 210 to perform a fourth operation, wherein the fourth operation occurs when the first user interface is not displayed on the touch screen display. On the way, the second type of user input is received through the button, and after receiving the second type of user input, a fourth user speech is received through the microphone 288, and the fourth user speech is received. Provides fourth data for the external server to the external server, and after providing the fourth data, in response to the fourth user utterance, at least one command for performing a task generated by the intelligent system is provided. After receiving from an external server, receiving a fifth user speech through the microphone, providing fifth data for the fifth user speech to the external server, and providing the fifth data, 5 In response to user speech, at least one command for performing a task generated by the intelligent system may be received from the external server.

In various embodiments of the present invention, the first type of user input and the second type of user input are different, and include pressing the button once, pressing the button twice, and pressing the button three times. , Pressing and maintaining the button after pressing the button once, or pressing and maintaining the button twice and maintaining the button may be selected.

In various embodiments of the present invention, the memory 230 is further configured to store a second application program including a second user interface for receiving a text input, and the instructions, when executed, are configured by the processor ( 210) further causes a third operation to be performed, wherein the third operation receives a user input of the first type through the button while displaying the second user interface, and the user of the first type After the input is received, a third user speech is received through the microphone, third data for the third user speech is provided to the external server, and after the third data is provided, the external server inputting the text to the second user interface while receiving data about text generated by ASR from the third user utterance from the server, but not receiving a command generated by the intelligent system; and is input, and when the selected time period is exceeded, the inputted text may be automatically transmitted through the wireless communication circuit.

In various embodiments of the present invention, the memory 230 is set to store a first application program including a first user interface for receiving text input, and the memory 230, when executed, the The processor 210 stores instructions that cause a first operation and a second operation to be performed, the first operation receives a first type of user input through the button, and the first type of user input After receiving , the first user utterance is received through the microphone 288, and an external server including an automatic speech recognition (ASR) and intelligence system is configured to receive the first user utterance. Provide first data for, and, after providing the first data, receive at least one command for performing a task generated by the intelligent system in response to the first user utterance from the external server. and the second operation receives a second type of user input through the button and, after receiving the second type of user input, receives a second user utterance through the microphone 288; After providing the second data for the second user utterance to the external server, and receiving data for text generated by ASR from the second user utterance from the server after providing the second data, , the command generated by the intelligent system is not received, and the text can be input to the first user interface.

In various embodiments of the present invention, the instructions may further cause the processor 210 to display the first user interface along with a virtual keyboard, and the buttons may not be part of the virtual keyboard.

In various embodiments of the invention, the instructions further cause the processor 210 to receive data for text generated by the ASR from the first user utterance within the first action from the external server. can do.

In various embodiments of the present invention, the first application program may include at least one of a note application program, an e-mail application program, a web browser application program, or a calendar application program.

In various embodiments of the present invention, the first application program includes a message application, and the instructions cause the processor 210 to, if a selected period of time after inputting the text, exceed the wireless communication circuitry. It can be further caused to transmit automatically input text through.

In various embodiments of the present invention, the instructions may further cause the processor 210 to perform the first operation independently of display on the display of the first user interface.

In various embodiments of the present disclosure, the instructions may cause the processor 210 to perform the second operation when at least one of the electronic device is locked or the touch screen display is turned off. can cause more

In various embodiments of the present disclosure, the instructions may further cause the processor 210 to perform the second operation while displaying the first user interface on the touch screen display.

In various embodiments of the present invention, the memory 230, when executed, allows the processor 210 to receive user utterances through the microphone 288, perform automatic speech recognition (ASR) or An external server that performs at least one of natural language understanding (NLU), and performs the ASR on the user utterance data together with the user utterance data to obtain the natural language understanding for text obtained. transmits information associated with whether or not to perform the natural language understanding, and if the information indicates not to perform the natural language understanding, receive the text for data on the user's utterance from the external server; If indicated, an instruction causing the external server to receive a command obtained as a result of performing the natural language understanding of the text may be stored.

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3 is a block diagram of program modules according to various embodiments. According to one embodiment, the program module 310 (eg, the program 140) is an operating system that controls resources related to an electronic device (eg, the electronic device 101) and/or various applications running on the operating system (eg, the electronic device 101). Example: application program 147). The operating system may include, for example, Android ^TM , iOS ^TM , Windows ^TM , Symbian ^TM , Tizen ^TM , or Bada ^TM . Referring to FIG. 3, the program module 310 includes a kernel 320 (eg kernel 141), middleware 330 (eg middleware 143), (API 360 (eg API 145) ), and/or an application 370 (eg, the application program 147). At least a part of the program module 310 is preloaded on an electronic device, or an external electronic device (eg, an electronic device ( 102, 104), server 106, etc.).

The kernel 320 may include, for example, a system resource manager 321 and/or a device driver 323 . The system resource manager 321 may perform control, allocation, 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 WiFi driver, an audio driver, or an inter-process communication (IPC) driver. . The middleware 330, for example, provides functions commonly required by the application 370 or provides various functions through the API 360 so that the application 370 can use limited system resources inside the electronic device. It can be provided as an application 370 . According to one embodiment, the middleware 330 includes a runtime library 335, an application manager 341, a window manager 342, a multimedia manager 343, a resource manager 344, a power manager 345, a database manager ( 346), a package manager 347, a connectivity 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 used by a compiler to add new functions through a programming language while the application 370 is being executed. The runtime library 335 may perform input/output management, memory management, or arithmetic function processing. The application manager 341 may manage the life cycle of the application 370 , for example. The window manager 342 may manage GUI resources used in the screen. The multimedia manager 343 may determine a format required for reproducing media files, and encode or decode the media files using a codec suitable for the format. The resource manager 344 may manage a source code of the application 370 or a memory space. The power manager 345 may manage, for example, battery capacity or power, and provide power information necessary for the operation of the electronic device. According to one embodiment, the power manager 345 may interoperate with a basic input/output system (BIOS). The database manager 346 may create, search, or change a database to be used in the application 370 , for example. The package manager 347 may manage installation or update of applications distributed in the form of package files.

The connectivity manager 348 may manage wireless connections, for example. The notification manager 349 may provide a user with an event such as an arrival message, an appointment, or proximity notification. The location manager 350 may manage, for example, location information of an electronic device. The graphic manager 351 may manage, for example, graphic effects to be provided to the user or user interfaces related thereto. Security manager 352 may provide system security or user authentication, for example. According to one embodiment, the middleware 330 may include a telephony manager for managing voice or video call functions of an electronic device or a middleware module capable of forming a combination of functions of the aforementioned components. . According to one embodiment, the middleware 330 may provide modules specialized for each type of operating system. The middleware 330 may dynamically delete some existing components or add new components. The API 360 is, for example, a set of API programming functions, and may be provided in different configurations depending on the operating system. For example, in the case of Android or iOS, one API set can be provided for each platform, and in the case of Tizen, two or more API sets can be provided for each platform.

The application 370 includes, for example, a home 371, a dialer 372, an SMS/MMS 373, an instant message (IM) 374, a browser 375, a camera 376, and an alarm 377. , Contacts (378), Voice Dial (379), Email (380), Calendar (381), Media Player (382), Album (383), Watch (384), Health Care (e.g. exercise or blood sugar measurement) , or environmental information (eg, air pressure, humidity, or temperature information) providing applications. According to one embodiment, the application 370 may include an information exchange application capable of supporting information exchange between an electronic device and an external electronic device. The information exchange application may include, for example, a notification relay application for delivering specific information to an external electronic device or a device management application for managing an external electronic device. For example, a notification delivery application may transfer notification information generated by another application of an electronic device to an external electronic device or may receive notification information from an external electronic device and provide the notification information to a user. The device management application is, for example, a function of an external electronic device communicating with the electronic device (eg, turn-on/turn-off of the external electronic device itself (or some component parts) or display brightness (or resolution)). adjustment), or an application operating in an external electronic device may be installed, deleted, or updated. According to an embodiment, the application 370 may include an application designated according to the properties of an external electronic device (eg, a health management application of a mobile medical device). According to one embodiment, the application 370 may include an application received from an external electronic device. At least a portion of the program module 310 may be implemented (eg, executed) in software, firmware, hardware (eg, the processor 210), or a combination of at least two of them, and a module for performing one or more functions; It can include a program, routine, set of instructions, or process.

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4 is a flowchart illustrating a method of providing a popularity voting service by an electronic device (eg, the electronic device 101 of FIG. 1 ) according to various embodiments.

FIG. 5 illustrates candidate voting data in which each user device (eg, the electronic device 102 of FIG. 1 ) casts a plurality of votes for specific candidates, according to various embodiments.

6 is a diagram illustrating an example of calculating a set of users exposed to content A when there is only direct exposure to content A, according to various embodiments.

7 is a diagram illustrating a user set exposed to content B when indirect exposure exists, according to various embodiments.

8 is a diagram illustrating an example of measuring the number of exposures UE1 and UE2 for a specific candidate according to various embodiments.

According to various embodiments, the electronic device 101 communicates with a user device (eg, the electronic device 102 of FIG. 1) (eg, a smartphone or a laptop) through a communication network, and the user device 102 communicates with a plurality of It may be a server that operates an application composed of execution screens or a web site composed of a plurality of web pages. The electronic device 101 may transmit, to the user device 102, a source code enabling the user device 102 to display each execution screen of a dedicated application or website providing a popularity voting service for a plurality of candidates. The user device 102 may receive the source code and display an execution screen requested by the user of the user device 102 through the dedicated application or a web browser. According to an embodiment, the user device 102 may refer to a user account that accesses the electronic device 101 through the corresponding user device.

In operation 401, according to various embodiments, the electronic device 101 (eg, the processor 120 of FIG. 1) receives information from a plurality of user devices through a communication interface (eg, the communication interface 170 of FIG. 1). Candidate voting data for selecting a plurality of candidates and candidate review data for evaluating the plurality of candidates may be received. According to an embodiment, the electronic device 101 may receive candidate voting data for selecting a specific candidate from among a plurality of candidates from the user device 102 . According to an embodiment, the candidate voting data may indicate a vote for selecting a candidate, and the user device 102 may vote for a single candidate with a plurality of votes according to settings of a manager of the electronic device 101 . For example, referring to FIG. 5 , each user device 102 may vote a plurality of votes 501 (eg, “18000 votes” for first place) for a single candidate. The electronic device 101 may include a paid payment platform so that the user device 102 can purchase a plurality of tickets using a paid payment method. According to an embodiment, the candidate review data may represent reviews written by user devices on a review page provided for each of a plurality of candidates. According to an embodiment, the electronic device 101 may store the received candidate voting data and candidate review data in a memory (eg, the memory 120 of FIG. 1 ).

In operation 403, according to various embodiments, the electronic device 101 (eg, the processor 120 of FIG. 1) performs morpheme analysis and emotion analysis on the candidate review data, based on predetermined screening criteria. Emotion scores for the plurality of candidates may be calculated by digitizing positive and negative evaluations included in the candidate review data. The emotion score does not simply depend on the number of votes of users, but can be used to fairly judge various qualities of candidates using an artificial intelligence (AI) model. According to an embodiment, the pre-determined screening criteria are criteria for judges at the host side conducting the popular vote to screen candidates, and keywords related to the screening criteria may include words such as personality, academics, speech and demeanor, and dignity. The electronic device 101 may extract a review including a sentence associated with the keyword from candidate review data. The electronic device 101 may preset priorities for each of a plurality of screening criteria. In this case, the electronic device 101 may assign a weight to each screening criterion according to a preset priority, and calculate an emotional score for the candidate by reflecting the weight assigned to each screening criterion.

According to various embodiments, the electronic device 101 (eg, the processor 120 of FIG. 1 ) performs noise filtering on the candidate review data to obtain special characters and meanings included in the candidate review data. A preprocessing operation may be performed in which stopwords without no words are judged as noise and excluded from the subject of the morpheme analysis. In addition, the electronic device 101 may perform a preprocessing operation of determining a sentence of the candidate review data that does not include an adjective capable of determining positive or negative as noise and excluding it from the subject of the morpheme analysis. have. According to an embodiment, the electronic device 101 performs morpheme analysis and sentiment analysis on candidate review data, digitizes positive evaluations and negative evaluations included in the candidate review data, and determines the criteria for the predetermined screening criteria. Emotion scores for a plurality of candidates may be calculated. Specifically, the electronic device 101 may perform morphological analysis on candidate review data including keywords associated with the screening criteria, and through the morphological analysis, nouns representing characteristics and screening criteria, and their characteristics It is possible to extract verbs and adjectives representing opinions and emotions about and perform sentiment analysis on the candidate review data based on the extracted nouns, verbs, and adjectives. Based on the result of the sentiment analysis, the electronic device 101 may count the number of positive evaluations and the number of negative evaluations among all reviews of the candidate to calculate a positive evaluation rate and a negative evaluation ratio. For example, the electronic device 101 calculates an emotion (positive/negative) score with an 'adjective' or 'verb' that evaluates the evaluation criteria in sentences including first and second screening criteria, respectively. can do. Specifically, if there is a review sentence "Your personality is really good" on the review page for a candidate, you can score 1 point because you expressed a positive expression of "Your personality is good" for the screening criterion of "personality". A positive evaluation is scored as plus 1 point, and a negative evaluation is minus 1 point. Among all reviews, the first review (FR, first review) containing the keyword representing the first review criterion is called FR={FR1, FR2, FR3, ..., FRn}, and the review is scored positive / negative When this is referred to as FS (first score), the final review score (Keyword Review) for the first screening criterion can be calculated as KR1 = FS/FR. Similarly, the second review (SR) containing the keyword representing the second review criterion is called SR = {SR1, SR2, SR3, ..., SRn}, and the review is scored positive / negative. When SS (second score) is assumed, the final review score (keyword review) for the second review criterion can be calculated as KR2 = SS/SR. If the sum of the positive and negative scores is multiplied by the weight (Wn) of each screening criterion and summed, and expressed as a percentage, an appraisal score for a specific candidate can be calculated based on each screening criterion. This is expressed as Equation 1 below.

[Equation 1]

ReviewSentimentScore = {(KR1*W1)+(KR2*W2)}/100

In operation 405, according to various embodiments, the electronic device 101 (eg, the processor 120 of FIG. 1 ) analyzes social network relationship information according to a subscription relationship of a plurality of candidates and a citation relationship of contents on social media. can do. Like the emotion score, the influence factor does not simply depend on the number of votes from users, but can be used to fairly evaluate various qualities of candidates using an artificial intelligence (AI) model.

According to various embodiments, the electronic device 101 (eg, the processor 120 of FIG. 1 ) provides a subscription relationship of a plurality of candidates on social media and posts on social media of a plurality of candidates through the communication interface 170 . It is possible to collect network relation information according to the citation relation of contents. For example, the electronic device 101 may receive network relation information from an operating system that operates social network services such as Twitter and Facebook. Network relationship information may vary in format and included information depending on the company that operates the social media, but basically, information on the subscription relationship that a user subscribes to which user and citation of which content is being cited It may contain relational information. In addition, information on the activities of each candidate, for example, information on which content was viewed on which site, and information about the case where the content was created in a space such as an online community even if it is not your own space may be further included. .

According to various embodiments, the electronic device 101 (eg, the processor 120 of FIG. 1 ) analyzes the obtained network relation information to check user information exposed for each content posted by candidates. For each content, the electronic device 101 may extract information about users directly exposed to the content, users who cited the content, and users indirectly exposed to the content, and the number of exposures for each content. For example, users who are directly exposed to the content include users who subscribe to the corresponding content, and may also include users who directly visit the site where the corresponding content is located and directly watch the corresponding content.

In operation 407, according to various embodiments, the electronic device 101 (eg, the processor 120 of FIG. 1 ), based on the social network relationship information, selects a user by other users exposed to the contents of a plurality of candidates. An average exposure score obtained by indexing the average number of exposures per person may be calculated, and an influence index of the plurality of candidates may be calculated based on the average exposure score and the number of other users exposed to the contents of the plurality of candidates.

According to various embodiments, the electronic device 101 (eg, the processor 120 of FIG. 1 ) determines the average exposure per user by other users exposed to the content of a specific candidate based on the analyzed network relation information. An influence factor capable of calculating the number of times can be extracted. The electronic device 101 may extract the total number of exposures of all contents created by a specific candidate and the number of other users exposed to the contents of a specific candidate as influence factors. Here, the total exposure count UE1i of all contents created by candidate i is the sum of the number of exposed users (|Ti,x|) of individual contents (x1, x2, ..., xn) created by candidate i, as shown in Equation 2 below. can express

[Equation 2]

UE1i = |Ti,x1| + |Ti,x2| + ... + |Ti,xn(i)|

In addition, the number of exposed users (|Ti,x|) is the number of users directly exposed to content x, users indirectly exposed to content x, and followers of users who quote (retweet, RT) content x as shown in Equation 3 below ( Subscribers) can be represented as the union of

[Equation 3]

Number of exposed users (|Ti,x|) = |DFi U RFx U Rx|

Here, DFi is a set of users directly exposed to content x, which means a set of followers of candidate i, RFx is a set of users indirectly exposed to content x, which means a set of followers of users who cited a specific content x, and Rx is a set of followers of content x. The set of users who retweet x. Here, examples of direct exposure and indirect exposure will be described with reference to FIGS. 6 to 8 . 6 to 8 show examples of direct exposure and indirect exposure for Twitter (trade name), one of social network services. 6 shows an example of calculating a user set exposed to content A (tweet A) when there is only direct exposure to content A (tweet A), and FIG. It shows the set of users exposed to the tweet B).

In addition, among the influence factors, the number of other users (UE2i) exposed to the content created by candidate i is the set of exposed users (Ti, It can be expressed as the number of users of the union of x).

[Equation 4]

UE2i = |Ti,x1 U Ti,x2 U ... Ti,xn(i)|

FIG. 8 illustrates an example of measuring the total number of exposures UE1 of all contents created by a specific candidate and UE2, the number of other users exposed to the contents of a specific candidate. It is expressed as a sum, and UE2 may be expressed as a union of user sets (Ti,x) exposed to individual content.

According to various embodiments, the electronic device 101 (eg, the processor 120 of FIG. 1 ) calculates an average exposure score obtained by indexing the average number of exposures per user and the number of other users exposed to the content of a specific candidate. Based on this, the influence index of a specific candidate can be calculated.

[Equation 5]

Impact Factor = S(UE1/UE2)*UE2

Here, UE1 means the number of exposures of the candidate's entire content, and UE2 means the number of other users exposed to the entire content of the candidate. Therefore, UE1/UE2 is the average number of exposures per other user based on other users exposed to the candidate's content.

The function S converts the average number of exposures into an average exposure score as shown in Equation 6 below.

[Equation 6]

S(x) = ln(x+(e-1))

Equation 6 is basically a form of taking the natural logarithm of the number of exposures, and since it becomes 0 when UE1 and UE2 have the same value, it is a form in which (e-1), which is a correction value to prevent this, is added. Accordingly, the influence index Ei of candidate i can be expressed as Equation 7 below.

[Equation 7]

Ei={ln((UE1i/UE2i)+(e-1))}*UE2i

Here, UE1i is the total exposure count of all content created by candidate i, UE2i is the number of other users exposed to content created by candidate i, and (e-1) is a correction value to prevent the influence index from being calculated as 0. As , e is a natural constant. Among the influence factors, since the total number of impressions UE1 of all content created by a specific candidate is the sum of the number of impressions of all content, simply creating a lot of content tends to increase the corresponding value UE1. In addition, UE2, the number of other users exposed to the content of a specific candidate among the influence factors, can become very large even if only one or a portion of the content is exposed to many users, and thereafter, it is hardly exposed. have. Therefore, if these influence factors are reflected in the influence index as they are, the influence index of the corresponding candidate may be calculated higher than the actual one because the change in value is proportionally reflected in the influence index. Therefore, in an embodiment of the present invention, after calculating the average number of exposures (UE1/UE2) per other user based on other users exposed to the content of the candidate, this is converted into an average exposure score to be reflected in the influence index. As a result, when the number of exposed contents is simply large or when a lot of contents are exposed even though not many contents have been created, the influence index is not increased so much that an influence index close to reality is calculated.

In operation 409, according to various embodiments, the electronic device 101 (eg, the processor 120 of FIG. 1 ) may determine whether the number of user devices participating in voting exceeds a predetermined number. For example, the electronic device 101 may determine whether the number of user devices (or user accounts) participating in voting exceeds a predetermined number (eg, 1000).

In operation 411, according to various embodiments, the electronic device 101 (eg, the processor 120 of FIG. 1 ) determines the score of the candidate voting data when the number of user devices participating in voting exceeds a predetermined number. The reflection ratio is set to the first ratio, the score reflection ratio of the emotion score is set to the second ratio lower than the first ratio, and the score reflection ratio of the influence index is set to the third ratio lower than the second ratio. A final score for the candidates can be calculated. For example, when the number of user devices participating in the vote (eg, 2000) exceeds a predetermined number (eg, 1000), the electronic device 101 prioritizes the opinions of the participating users to vote for candidates. Set the score reflection ratio of the data to the first ratio (eg 40%), and as an artificial intelligence screening model, set the score reflection ratio of the appraisal scores for the plurality of candidates to the second ratio (eg 35%) , Final scores for the plurality of candidates may be calculated by setting the score reflection ratio of the influence index of the plurality of candidates to a third ratio (eg, 25%). According to an embodiment, the electronic device 101, prior to calculating the final score, takes into consideration that the numerical units of each data may be different and compares the candidate voting data, emotion scores, And normalization may be performed on the influence index, and a final score may be calculated using the normalized data.

In operation 413, according to various embodiments, the electronic device 101 (eg, the processor 120 of FIG. 1 ) determines the score reflection ratio of the emotional score when the number of user devices participating in the vote is less than or equal to a predetermined number. is set as a first ratio, the score reflection ratio of the influence index is set to a second ratio lower than the first ratio, and the score reflection ratio of the candidate voting data is set to a third ratio lower than the second ratio, Final scores for a plurality of candidates may be calculated. When the number of people who participated in the vote is small, this is a fair screening by considering the emotion score that directly evaluates the candidate by review using an artificial intelligence model as the first priority and considering the candidate's influence index as the second priority to calculate the score. to derive results. For example, when the number of user devices participating in the vote (eg, 500) is less than or equal to a predetermined number (eg, 1000), the electronic device 101 prioritizes the review evaluation of the candidates to generate artificial intelligence information. As a screening model, the score reflection ratio of the emotion scores for a plurality of candidates is set to a first ratio (eg 40%), and the score reflection ratio of the influence index of the plurality of candidates is set to a second ratio (eg 35%) , and the score reflection ratio of candidate voting data is set to a third ratio (eg, 25%) to calculate final scores for a plurality of candidates.

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According to various embodiments, a server providing a popularity voting service includes a communication interface and a processor, wherein the processor includes candidate voting data for selecting a plurality of candidates from a plurality of user devices through the communication interface, and the By receiving candidate review data for evaluating a plurality of candidates and performing morphological analysis and sentiment analysis on the candidate review data, positive and negative evaluations included in the candidate review data are determined based on predetermined screening criteria. Calculate emotion scores for the plurality of candidates by digitizing them, analyze social network relationship information according to the subscription relationship of the plurality of candidates and the quotation relationship of contents on social media, and based on the social network relationship information, An average exposure score obtained by indexing the average number of exposures per user by other users exposed to the contents of a plurality of candidates is calculated, and based on the average exposure score and the number of other users exposed to the contents of the plurality of candidates. Influence indexes of the plurality of candidates are calculated, and when the number of the plurality of user devices participating in voting exceeds a predetermined number, a score reflection ratio of the candidate voting data is set to a first ratio, and the emotional score setting a score reflection ratio to a second ratio lower than the first ratio, setting a score reflection ratio of the influence factor to a third ratio lower than the second ratio to calculate the final score, and calculating the final score; and When the number of these is less than or equal to a predetermined number, the score reflection ratio of the emotion score is set to a first ratio, the score reflection ratio of the influence index is set to a second ratio lower than the first ratio, and the score of the candidate voting data It may be set to calculate the final score by setting the reflection ratio to a third ratio lower than the second ratio.

According to various embodiments, the processor performs noise filtering on the candidate review data, determines special characters and meaningless stopwords included in the candidate review data as noise, A pre-processing operation is performed to exclude from the subject of morpheme analysis, and pre-processing to exclude sentences of the candidate review data from the subject of the morpheme analysis by determining that sentences that do not include adjectives capable of determining positive or negative in sentences of the candidate review data are noise. It can be set to perform an action.

According to various embodiments, the processor, based on a final review score (KR1) for a first review criterion and a final review score (KR2) for a second review criterion among the predetermined review criteria, It may be set to calculate ReviewSentimentScore for the plurality of candidates using Equation 1 below.

[Equation 1]

KR1 = FS/FR ,

KR2 = SS/SR ,

ReviewSentimentScore = {(KR1*W1)+(KR2*W2)}/100

Each element of Equation 1 is a first review (FR) including a keyword representing the first review criterion, a first score (FS) derived from positive/negative scores of the first review, and the second review criterion. Indicates a second review (SR) including a keyword indicating, and a second score (SS) obtained by deriving positive/negative scores of the second review.

According to various embodiments, the processor may expose the contents of the plurality of candidates at an average exposure score per user based on Equations 2, 3, and 4 below. It may be set to calculate the influence factor by multiplying the number of other users.

[Equation 2]

UE1i = |Ti,x1| + |Ti,x2| + ... + |Ti,xn(i)|

[Equation 3]

|Ti,x|= |DFi U RFx U Rx|

[Equation 4]

UE2i = |Ti,x1 U Ti,x2 U ... Ti,xn(i)|

UE1i in Equation 2 represents the total number of exposures of all contents created by candidate i, and is expressed as the sum of the number of exposed users (|Ti,x|) of individual contents (x1, x2, ..., xn) created by candidate i, ,

DFi in Equation 3 is a set of users directly exposed to content x, which means a set of followers of candidate i, RFx is a set of users indirectly exposed to content x, which means a set of followers of users who quoted a specific content x, and Rx denotes a set of users who retweet the content x,

UE2i in Equation 4 is the number of other users exposed to the content created by candidate i, and is represented by the number of users of the union of the user sets (Ti,x) exposed to individual content (x1, x2, ..., xn) created by candidate i. can

According to various embodiments, the processor may be set to calculate the influence factor based on Equations 5 and 6 below.

[Equation 5]

Impact Factor = S(UE1/UE2)*UE2

[Equation 6]

S(x) = ln(x+(e-1))

UE1/UE2 in Equation 5 means the average number of exposures per other user based on other users exposed to the candidate's content,

Equation 6 is a form obtained by taking the natural logarithm of the number of exposures in Equation 5.

According to various embodiments, the processor may be set to calculate an influence factor using Equation 7 below.

[Equation 7]

Impact Factor = {ln((UE1i/UE2i)+(e-1))}*UE2i

UE1i is the total exposure count of all content created by candidate i, UE2i is the number of other users exposed to content created by candidate i, and (e-1) is a correction value to prevent the influence index from being calculated as 0, e is a natural constant.

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The term "module" used in this document includes a unit composed of hardware, software, or firmware, and may be used interchangeably with terms such as logic, logic block, component, or circuit, for example. A “module” may be an integrally constructed component or a minimal unit or part thereof that performs one or more functions. A "module" may be implemented mechanically or electronically, for example, a known or future developed application-specific integrated circuit (ASIC) chip, field-programmable gate arrays (FPGAs), or A programmable logic device may be included. At least some of the devices (eg, modules or functions thereof) or methods (eg, operations) according to various embodiments are instructions stored in a computer-readable storage medium (eg, the memory 130) in the form of program modules. can be implemented as When the command is executed by a processor (eg, the processor 120), the processor may perform a function corresponding to the command. Computer-readable recording media include hard disks, floppy disks, magnetic media (e.g. magnetic tape), optical recording media (e.g. CD-ROM, DVD, magneto-optical media (e.g. floptical disks), built-in memory, etc.) A command may include code generated by a compiler or code executable by an interpreter A module or program module according to various embodiments may include at least one or more of the above-described components or , some may be omitted, or may further include other elements.According to various embodiments, operations performed by modules, program modules, or other elements may be executed sequentially, in parallel, iteratively, or heuristically, or at least Some actions may be performed in a different order, omitted, or other actions may be added.

And the embodiments disclosed in this document are presented for explanation and understanding of the disclosed technical content, and do not limit the scope of the present disclosure. Therefore, the scope of the present disclosure should be construed to include all changes or various other embodiments based on the technical spirit of the present disclosure.

Claims (5)

In a server providing a popularity voting service,
communication interface; and a processor; including,
The processor:
Receiving candidate voting data for selecting a plurality of candidates and candidate review data for evaluating the plurality of candidates from a plurality of user devices through the communication interface;
By performing morpheme analysis and sentiment analysis based on an AI (Artificial Intelligence) model on the candidate review data, positive evaluation and negative evaluation included in the candidate review data are quantified based on predetermined screening criteria. to calculate emotion scores for the plurality of candidates,
Analyzing social network relationship information according to the subscription relationship of the plurality of candidates and the citation relationship of contents on social media;
Based on the social network relationship information, an average exposure score obtained by indexing the average number of exposures per user by other users exposed to the contents of the plurality of candidates is calculated;
Calculate an influence index of the plurality of candidates based on the average exposure score and the number of other users exposed to the contents of the plurality of candidates;
When the number of the plurality of user devices participating in voting exceeds a predetermined number: a score reflection ratio of the candidate voting data is set to a first ratio, and a score reflection ratio of the emotion score is lower than the first ratio to a second ratio ratio, and the score reflection ratio of the influence index is set to a third ratio lower than the second ratio to calculate final scores for the plurality of candidates;
When the number of the plurality of user devices is less than or equal to the predetermined number: the score reflection ratio of the emotion score is set to the first ratio, the score reflection ratio of the influence index is set to the second ratio, and the candidate voting data By setting the score reflection ratio of to the third ratio to calculate the final score,
The processor:
performing noise filtering on the candidate review data, determining special characters and meaningless stopwords included in the candidate review data as noise, and performing a preprocessing operation of excluding them from the subject of the morpheme analysis;
Sentences of the candidate review data that do not contain adjectives capable of determining affirmation or negation are judged as noise and a preprocessing operation is performed to exclude them from the subject of the morpheme analysis;
Based on the final review score (KR1) for the first review criterion and the final review score (KR2) for the second review criterion among the predetermined review criteria, the evaluation of the plurality of candidates is performed using the following equation. It is set to calculate the score (RSS, ReviewSentimentScore),
[mathematical expression]
KR1 = FS/FR
KR2 = SS/SR
RSS = {(KR1*W1)+(KR2*W2)}/100
FR corresponds to the first review including the keyword representing the first review criterion, FS corresponds to the first score derived from the positive / negative score of the first review, and SR represents the second review criterion Corresponds to the second review including the keyword, SS corresponds to the second score derived from the positive / negative score of the second review, W1 corresponds to the first weight, W2 corresponds to the second weight, A server that provides popularity voting services. delete delete delete delete

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