Prior to the detailed description of the present invention, the terms or words used in the present specification and claims should not be construed as limited to ordinary or preliminary meaning, and the inventor may designate his own invention in the best way It should be construed in accordance with the technical idea of the present invention based on the principle that it can be appropriately defined as a concept of a term to describe it. Therefore, the embodiments described in the present specification and the configurations shown in the drawings are merely the most preferred embodiments of the present invention, and are not intended to represent all of the technical ideas of the present invention. Therefore, various equivalents It should be understood that water and variations may be present.
Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. Note that, in the drawings, the same components are denoted by the same reference symbols as possible. Further, the detailed description of known functions and configurations that may obscure the gist of the present invention will be omitted. For the same reason, some of the elements in the accompanying drawings are exaggerated, omitted, or schematically shown, and the size of each element does not entirely reflect the actual size.
First, a system for profiling a user according to an embodiment of the present invention will be described. 1 is a block diagram for explaining a configuration of a system for profiling a user according to an embodiment of the present invention. Referring to FIG. 1, a system for profiling a user according to an embodiment of the present invention (hereinafter abbreviated as a 'profiling system') includes a profile server 100 and a user device 200.
The profiling system derives profile information including the user's profile, interests and lifestyle using the user device 200. In the embodiment of the present invention, the user's profile includes information such as the user's name, resident registration number, etc., excluding the information that can be uniquely identified by distinguishing the user from other users. The user's information such as age, sex, occupation, marital status, Which can be classified into any one group. Also, interest refers to an area of interest to a user in categories such as health, beauty, marriage, travel, shopping, language, and the like. Lifestyle refers to a user's life pattern such as sleep time, weather time, work time, work time, outdoor activity time, indoor activity time, and the like.
The profile server 100 may perform, for example, at least one of a web server, a database server, and an application server. The user device 200 may represent a smart phone, a tablet PC, a tablet PC, and the like. The user device 200 may access the profile server 100 via the network and receive the necessary information from the profile server 100 or may transmit necessary information to the profile server 100. [ The profile server 100 provides app information to the user device 200 so as to derive a profile, a concern, and a lifestyle based on an app used by the user. The app information includes app profile information that shows a profile mapped to the app as a statistic and app interest information to which a concern to which the app belongs is mapped according to a predetermined category. The app information collects a list of apps from an ESD (Electronic Software Distribution) server 300, and maps the apps included in the list of collected apps. The user device 200 can derive the user's profile, interest, and lifestyle using the app information provided by the profile server 100 and the device information extracted from the user device 200 itself. Here, the device information includes all the information that can be obtained from the resource of the user device 200. [ User device 200 will be described in more detail below, but is a device that accesses and controls all resources through an operating system. The resources of the user device 200 may be generated by hardware such as a GPS receiver, a camera, a sensor, a battery, a memory, and storage, software such as various apps and applications stored in memory or storage, Which is information of each kind, can be exemplified. Meanwhile, the hardware and software generate information as the user device 200 is used. For example, when the user device 200 is a smart phone, information such as a place where a photograph was taken, a photographing time, and the like is generated not only by a photograph as a digital image file but also by a GPS receiver, Will be stored in memory or storage. Alternatively, when the user makes a telephone call, a call log will be stored, and information such as when, where, to whom, for how long, etc., will be recorded. As described above, each type of information is generated as a user uses the user device 200, and all of the information can be accessed through an operating system (OS). Accordingly, in the embodiment of the present invention, the device information is information that can be obtained from all kinds of resources accessible through the operating system of the user device 200, or all information obtained by processing the information obtained from the resource.
Hereinafter, the configuration of the profile server 100 and the user device 200 according to the embodiment of the present invention will be described in detail. First, the configuration of the profile server 100 according to the embodiment of the present invention will be described. 2 is a block diagram illustrating a configuration of a profile server according to an embodiment of the present invention. Referring to FIG. 2, the profile server 100 includes a communication module 110, a storage module 120, and a control module 130.
The communication module 110 is for communicating with the ESD server 300 or the user device 200. The communication module 110 performs communication for exchanging data including necessary information with the user device 200 when the user device 200 accesses the profile server 100. That is, when the communication module 110 receives data for transmission from the control module 130 to the user equipment 200, the communication module 110 composes and transmits the received data. The communication module 110 extracts data from a packet received from the user device 200 and transmits the extracted data to the control module 130. [
The storage module 120 stores programs and data necessary for the operation of the profile server 100, and can be divided into a program area and a data area. The program area may store a program for controlling the overall operation of the profile server 100 and an operating system (OS) for booting the profile server 100, applications, and the like. The data area is an area where data generated according to the operation of the profile server 100 and data necessary for operating the profile server 100 are stored. Such data may include, for example, statistics of profile information for each of a plurality of apps, a category of interest, a profile of a user received from the user device 200, a concern and a lifestyle. Each kind of data stored in the storage module 120 can be deleted, changed or added according to a user's operation.
The control module 130 may perform a data processing function for controlling the overall operation of the profile server 100 and the signal flow between the internal blocks of the profile server 100 and processing the data. The control module 130 is preferably a central processing unit (CPU). The control module 130 provides information necessary for deriving the user's profile, interest and lifestyle of each of the plurality of user devices 200, and provides a profile of the user derived by each of the plurality of user devices 200, The interest and the lifestyle are stored and stored in the storage module 120 to construct big data and the constructed big data is processed to transfer the interests and lifestyle of a plurality of users having profiles similar to the individual users to the user device (200). Thereby, an individual user can compare himself / herself with a plurality of users having a profile similar to himself / herself. The operation of this control module 130 will be described in more detail below.
Next, a description will be given of a user device 200 according to an embodiment of the present invention. 3 is a block diagram illustrating a configuration of a user apparatus according to an embodiment of the present invention. 3, a user apparatus 200 according to an exemplary embodiment of the present invention includes a communication unit 210, a position information receiving unit 220, a sensor unit 230, a camera unit 240, an input unit 250, 260, a storage unit 270, and a control unit 280.
The communication unit 210 is for communication with the profile server 100 and can communicate using a broadband mobile communication or a wireless local area communication method. The communication unit 210 may be implemented as a single module having both broadband mobile communication and wireless local area communication (WLAN) communication functions, and operates by selecting at least one of the two functions described above. However, the communication unit 210 may be implemented by a plurality of modules separately performing communication functions of the broadband mobile communication and the wireless local area communication connection method. Broadband mobile communication may exemplify a communication method of accessing a network through a base station according to standards such as WCDMA, LTE and LTE-A, and the wireless local area communication may be a wireless local area network (WLAN) using a wireless fidelity ) Method, it is possible to exemplify communication for accessing a network through an access point (AP). The communication unit 210 may include an RF transmitter for up-converting and amplifying a frequency of a transmitted signal, and an RF receiver for low-noise amplifying a received signal and down-converting the frequency of the received signal. In addition, the communication unit 210 may receive a radio signal including data through a wireless channel, and may transmit the received radio signal to the control unit 280. In addition, the data received from the controller 280 may be converted into a wireless signal and transmitted through a wireless channel.
The position information receiving unit 220 is for receiving position information. For example, the position information receiving unit 220 continuously receives GPS signals from GPS satellites (not shown) and extracts position information from the received GPS signals. Then, the position information receiving unit 220 can transmit the position information to the control unit 280. Such location information may be coordinates such as latitude, longitude, and altitude.
The sensor unit 230 senses the displacement, speed, and the like of the movement of the user device 200. The sensor unit 230 senses the displacement of the movement of the user device 200 and provides the detected movement displacement to the control unit 280 through the coordinate data. The coordinates provided by the sensor unit 230 may provide displacement from any reference position in a three-dimensional Cartesian coordinate system (x, y, z) or latitude, longitude and altitude. In addition, the coordinates provided by the sensor unit 230 may provide yaw, pitch, and roll displacements. Further, the sensor unit 230 senses the speed of the movement and can provide the speed to the control unit 280. [ The sensor unit 230 may be implemented by one or more sensors, and the sensor may be an accelerometer, a gyroscope, a magnetometer, or the like.
The camera unit 240 is for capturing an image. The camera unit 240 may include a lens, an actuator, a filter, an image sensor, and an image processor (ISP). The image sensor may be a CCD (Charge Coupled Device) or a CMOS (Complementary Metal-Oxide Semiconductor). Light reflected from a subject is input through a lens and converted into an electric signal. An image processor (ISP) converts an electrical signal output from the image sensor into a digital sequence and outputs the digital sequence as image data. The camera unit 240 also controls the actuator through an AF (Auto Focus) and / or an OIS (Optical Image Stabilization) driver to perform auto focus (AF) and / or shake correction Can be performed.
The input unit 250 receives user's key operation for controlling the user device 200, generates an input signal, and transmits the input signal to the control unit 280. The input unit 250 may include any one of a power key, a numeric key, and a direction key for power on / off, and may be formed of a predetermined function key on one side of the user device 200. In the case where the display unit 260 is a touch screen, functions of the various keys of the input unit 250 can be performed by the display unit 260. In the case where all functions can be performed only by the touch screen, It is possible.
The display unit 260 visually provides menus of the user device 200, input data, function setting information, and various other information to the user. The display unit 260 functions to output various screens such as a boot screen, a standby screen, a menu screen, and the like of the user device 200. The display unit 260 may be formed of a liquid crystal display (LCD), an organic light emitting diode (OLED), an active matrix organic light emitting diode (AMOLED), or the like. Meanwhile, the display unit 260 may be implemented as a touch screen. In this case, the display unit 260 includes a touch sensor, and the controller 280 can sense the touch input of the user through the touch sensor. The touch sensor may be constituted by a touch sensing sensor such as a capacitive overlay, a pressure type, a resistive overlay, or an infrared beam, or may be constituted by a pressure sensor . In addition to the above sensors, all kinds of sensor devices capable of sensing contact or pressure of an object can be used as the touch sensor of the present invention. The touch sensor senses the touch input of the user, generates a sensing signal, and transmits the sensed signal to the control unit 280. The sensing signal may include coordinate data input by the user. When the user inputs the touch position movement operation, the touch sensor may generate a sensing signal including coordinate data of the touch position movement path and transmit the sensing signal to the control unit 280. [ Particularly, when the display unit 260 is a touch screen, some or all of the functions of the input unit 250 may be performed through the display unit 260.
The storage unit 270 stores programs and data necessary for the operation of the user apparatus 200, and can be divided into a program area and a data area. The program area may store a program for controlling the overall operation of the user device 200, an operating system (OS) for booting the user device 200, an application program, and the like. The data area is an area where data generated according to use of the user device 200 is stored. The storage unit 270 may store profile data including each species data generated according to the operation of the user device 200, for example, app information, device information, user profile, interest, and lifestyle.
The control unit 280 may control the overall operation of the user device 200 and the signal flow between the internal blocks of the user device 200 and may perform a data processing function for processing the data. The controller 280 may be a central processing unit (CPU), an application processor, a graphic processing unit (GPU), or the like. The control unit 280 collects information necessary for deriving profile information including the user's profile, interest, and lifestyle. This information may be app information collected from the profile server 100 or device information collected through the resources of the user device 200. [ Also, the control unit 280 derives profile information including the user's profile, interest, and lifestyle based on the collected information. The operation of this control unit 280 will be described in more detail below.
Although not shown, the user device 200 according to an embodiment of the present invention includes a storage medium inserting unit for inserting an external storage medium such as a memory card to store data, a connection terminal for exchanging data with an external digital device, , A terminal for power supply or charging, and the like. In addition, the user device 200 may further include units (not shown) having additional functions such as an audio process for inputting or outputting an audio signal, a voice signal, or the like through a microphone and a speaker. Further, it may further comprise a clock module for obtaining and displaying the time at the current position based on the standard time. Although there are many variations of the portable device according to the convergence trend of the digital device, the user device 200 according to the present invention further includes the same level of units as the above-mentioned units It will be understood by those skilled in the art that various changes and modifications may be made without departing from the scope of the present invention.
A method for profiling a user according to an embodiment of the present invention will now be described in more detail. 4 is a flow chart illustrating a method for profiling a user of a profiling system. 5 and 6 are diagrams for explaining a method for profiling a user of the profiling system.
Referring to FIG. 4, the control module 130 of the profile server 100 collects an application list from the ESD server 300 through the communication module 110 in step S110. An example of the collected app list is shown in FIG. As shown, the collected app list includes identifiers, package names, and app names of each of a plurality of apps. This is all used as information to distinguish one app from another. On the other hand, for example, an app list can be collected by categories such as health, game, education, finance, weather, news, and books. In addition, the app list may be collected only for a list of apps in the top of the popular chart for each category, for example, an app having a predetermined number of downloads or more.
Next, in step S120, the control module 130 generates the app information for each of the apps in the app list collected earlier. An example of the app information is shown in Fig. As shown in the figure, the app information includes app profile information 61 that provides statistics of the profiles of the users who download and install the app from the ESD server 300, and a plurality of interest categories, And interest concern information (63) classified into the interest category. The profile information 61 is used as a basic data for deriving the profile of the user. The profile information 61 may classify the profiles of the users who download and install the app from the ESD server 300, and provide the statistics of the proportion of the profiles. For example, the profile information (61) for the age among the profiles of the users who use the app having the app identifier of App01 indicates that the age of downloading and using the app is 10 years old, 10 teenage students, 20 students, 20 students (5: 14: 20: 21: 22: 10: 8: 0), which are classified into social, 30s, 40s, 50s, 60s and over. Also, the profile information 61 of the gender among the profiles of the users using the app with the app identifier App02 classifies the gender as male and female, and provides the statistics (5: 95) do. Among the profiles of the users who use the app having the app identifier of App02, the profile information 61 about the marriage is classified as married and unmarried, and the ratio of the classified marriage as a whole (30: 70) It is provided as statistics.
The app interest information 63 is used as a basic data for deriving a user's interest. There are predefined interest categories, which are made up of a plurality of categories, such as learning, parenting, health, travel, shopping, finance, games, movies, music, The app interest information (63) indicates that the app is classified into a category in which the user is likely to be interested in the interest category when a specific user uses the specific app. For example, apps with app identifier of App08 are "civil servants, 700 free licensing exam Edu X passed apps", and users interested in using these apps are likely to be in the certification exam. Can be classified. That is, the app interest information 63 estimates the interests of users installing the app by downloading the app from the ESD server 300, and classifies the app according to a predetermined interest category.
App information as described above can be used to derive profile information. The data collection module 281 of the control unit 280 of the user device 200 may access the profile server 100 through the communication unit 210 and then download some or all of the app information in step S130. The data collection module 281 may store the downloaded app information in the storage unit 270. [
Then, the control unit 280 of the user device 200 derives the profile of the user in step S140. At this time, the control unit 280 can derive the user profile based on the application profile information 61, the application installed in the user device 200, the user's contact, and the user's settings. A method of deriving such a user's profile will be described in more detail below.
Then, the controller 280 derives interest of the user in step S150. At this time, the control unit 280 can derive the interest of the user through the app installed in the user device 200 by referring to the app interest information 63. [ In addition, in step S150, the user's interest may be sorted in a higher order of interest through the usage amount of the application installed in the user device 200 additionally and optionally. Optionally, the controller 280 may extract device information based on the resources of the user device 200 and derive the interest of the user by applying weights to the interests of the user.
Next, the controller 280 derives the lifestyle of the user in step S160. At this time, the controller 280 extracts the device information based on the resource of the user device 200, and derives the lifestyle of the user through the extracted device information.
In step S170, the controller 280 transmits the profile information including the user's profile, interest, and lifestyle derived to the profile server 100 in step S170. Then, the control module 130 of the profile server 100 stores the profile information of the user in the storage module 120 in step S180.
According to the present invention, the control module 130 of the profile server 100 receives profile information from a plurality of users through the same method as in the embodiment of FIG. 4, and can build a profile database using the received profile information have. As described above, according to the embodiment of the present invention, the profile information of the user is derived based on the app information about the app installed in the user device 200 and the device information derived according to the usage style of the user device 200 of the user Since the profile database is constructed, the user's taste can be accurately estimated. Big data built in this way can be effectively used for targeted marketing.
Hereinafter, a method of deriving profile information including a user profile, interest, and lifestyle in more detail will be described. First, a method of deriving the user's profile from the profile information will be described. 7 is a flowchart illustrating a method of deriving a profile according to an embodiment of the present invention. The embodiment of FIG. 7 is an example of step S140 in FIG. 4, and a method of deriving a profile using both the app information and the device information will be described.
6 and 7, the controller 280 checks the application installed in the user device 200 in step S210. For example, as a result of the confirmation, it is assumed that the app installed in the user device 200 has two apps with app identifiers App02 and App08.
Next, the controller 280 extracts the statistics of the apps installed in the user device from the app profile information 61 of the app information in step S220. 6, the control unit 280 extracts statistical values of two apps whose app identifiers are App02 and App08 from the app profile information 61 of Fig. 6, It is used as a statistic.
Then, in step S230, the control unit 280 estimates the user's profile from the device information, such as contact information and user setting information.
Here, the device information refers to information generated as a user uses the user device 200. [ For example, the device information includes contact information and setting information. A user may add a contact's contact menu, so-called, to another contact in the phone book, to facilitate communication with the other using the user device 200. At this time, the user can input the name of the other person to distinguish the contact of the added person from the contact of the other user. In an embodiment of the present invention, the contact information includes the name of the other person entered by the user in the contact. For example, if the contact has the title "XXX brother" or "OOO sister", the user's gender may be estimated to be "female". In another example, when a contact has a title such as a son-in-law, a daughter-in-law, a widow, a grandchild, or a granddaughter, the age of the user may be estimated to be 50 or more. The user may configure the user device 200 to suit his / her needs. In the embodiment of the present invention, the setting information includes information on what setting the user has made to his / her user device 200. [ For example, if the font size of the screen is set large, it can be estimated that the age of the user is 50, 60 or more.
In another example, the user's job can be estimated through the device information. The control unit 280 of the user device 200 periodically senses a change in the position of the user device 200 through the position information receiving unit 220 and detects a change in the movement speed and a change in the air pressure through the sensor unit 230 Periodically detects a change in the number of APs to be searched through the communication unit 210 and a change in the call volume to detect a change in position, a change in motion speed, a change in air pressure, a change in the number of APs to be searched, In the storage unit 270. The control unit 280 estimates the sleep time as a sleep time when the stop state in which there is little change in the movement speed through the sensor unit 230 continues for a predetermined time or more and estimates the time when the change in the movement speed occurs again as the wake time. The controller 280 analyzes the user's sleep pattern to estimate whether the user is a shift worker.
The control unit 280 can estimate the movement state of the user or the user device 200 by sensing the speed at which the user device 200 moves through the position information receiving unit 220 and the sensor unit 230. The motion state includes a stop state, a walking state, a beating state, a bicycle running state, and a vehicle running state and a state in which the user apparatus 200 is picked up. The stop state is a state in which the speed and position of the user device 200 change to zero. The walking state is a state in which the speed of the user device 200 is within the walking speed range when the walking speed range is set from the statistics of the walking speed of the general person. The beating state is a state in which the speed of the user device 200 is within the speed range when the speed range for running is set from the statistics of the speed at which the general user is running. The bicycle traveling state is a state in which the speed of the user device 200 is within the bicycle speed range when the bicycle speed range is set from the statistics of the speed of the traveling means having a speed similar to that of the bicycle and the bicycle. The vehicle running state is a state in which the speed of the user device 200 is within the vehicle speed range when the vehicle speed range is set from the statistics of the speed of the vehicle such as an automobile, a train or a train. The state of lifting up the user device 200 is determined by a change in the position of the user device 100 sensed through an accelerometer, a gyroscope, or a magnetometer of the sensor unit 230, To a second position higher than the first position.
Accordingly, if the vehicle driving state for a predetermined time or more and the walking state for a predetermined time or more are periodically repeated, the control unit 280 estimates that the user is engaged in the delivery business. Further, the control unit 280 estimates that the user is engaged in the transportation business when the vehicle traveling state is repeated for a predetermined time or more, but the walking state is less than the predetermined time. In addition, the controller 280 estimates that the user is a full-time housewife if the user is in a house estimated as a residence through a change of location, and there is a round-trip pattern at a place where the house is not home. The control unit 280 estimates that the user is a salesperson if there are many calls with a large number of people who are not specified during business hours through a change in the call volume.
As another example, the user's religion can be estimated through the device information. The control unit 280 periodically records a change in the position of the user apparatus 200 through the position information receiving unit 220 and periodically detects the number of APs searched through the communication unit 210, If you visit the same place at a certain time of the year, it is assumed to belong to the religion searched at that location.
If the user's profile is estimated from the device information, the control unit 280 assigns a weight to the statistic corresponding to the profile estimated in step S240. These weights may be derived using the device information collected through the resources of the user device 200. [ For example, if the user's gender is assumed to be female, the female statistic is weighted. For example, for users using App08 apps, the statistics for male and female are 50 and 50, respectively. If the contact has the title 'XXX brother' or 'OOO sister', the gender of the user is assumed to be 'female' and weights the female statistics. We assume that the pre-set weights corresponding to the terms 'XXX brother' and 'OOO sister' are -20% for males and + 20% for females. Then, the control unit 280 assigns weights to the statistics of women, and the statistics of male and female are 40 and 60, respectively.
After assigning the weight, the controller 280 determines the profile having the maximum value in the weighted statistics as the profile of the user in step S250. For example, if the profile is gender, assuming that the weighted male and female statistic values are 40 and 60, respectively, since the female statistic has the maximum value, the control unit 280 determines that the sex of the user is 'female' You can choose. As another example, if the profile is older, the statistics for the weighted teenage students, teenagers, 20s, 20s, 30s, 40s, 50s, and 60s are 0, 0, 15, 19, 22, 20, 15 and 9, respectively. Then, since the statistics of 30 generations have the maximum value, the controller 280 can select the age of the user's profile as '30 generations'.
After determining the profile of the user, the controller 280 calculates the accuracy of the determined profile in step S260. Here, the accuracy of the profile can be calculated according to the following equation (1).
Here, the maximum value is the maximum value in the weighted statistics, the average value is the average value of the weighted statistics, and the standard deviation is the standard deviation of the weighted statistics.
On the other hand, the profile of the user can be derived using only the device information. Such a method will be described. Typically, a profile derived using only device information may illustrate a residence area. The control unit 280 may sense the speed of movement of the user device 200 through the sensor unit 230. The control unit 280 may sense the displacement and the velocity of the motion of the user device 200 and estimate the motion state of the user according to the sensed velocity and displacement. The movement state may be a stop state in which the user is in a stopped state, a walking state in which the user is walking, a beating state in which the user is running, a bicycle traveling state in which the user rides on a vehicle A state in which the user is traveling on a vehicle such as a vehicle, a train, a train, etc., and a state in which the user picks up the user apparatus 200.
In order to derive the residence of the user, the control unit 280 uses the position information obtained when the pause state continues for a predetermined time or more within a preset sleeping time (for example, from 10 pm to 8 am the following morning) Can be determined.
For example, the control unit 280 continuously receives position information from the GPS signal through the position information receiving unit 220, and when the intensity of the GPS signal falls below a predetermined value, the intensity of the GPS signal falls below a predetermined value Position information in the stopped state can be obtained through the displacement of the motion of the user device 200 sensed through the sensor unit 230 from the position extracted from the last received GPS signal. The control unit 280 may transmit identification information of an access point (AP) accessed by the user apparatus 200 through the communication unit 210 in a paused state within a predetermined sleeping time through the sensor unit 230 And acquires the location information of the access point (AP) by accessing a database server that stores location information of the access point through the communication unit 210. On the other hand, the location information can be obtained by combining two examples. That is, the GPS signal and the position information obtained through the displacement detected by the sensor may be corrected to the position information obtained through the connection point, or the position information may be obtained through the reverse.
In another example, a profile derived using only device information may illustrate a residential type. The control unit 280 of the user device 200 may sense a variation in the atmospheric pressure through the sensor unit 230 and periodically store the change in the number of APs detected through the communication unit 210 in the storage unit 270 . The control unit 280 can extract the user's housing type through the change of the number of the APs and the variation of the atmospheric pressure. For example, if a user who lives in a group apartment type apartment starts to work, there will be a change in the number of searched APs, and a change in barometric pressure will occur because it falls to the first floor. Then, the control unit 280 can estimate whether the user lives in the apartment through the change of the number of the APs and the variation of the atmospheric pressure.
Next, a method of deriving a user's interest among the profile information will be described. 8 is a flowchart illustrating a method of deriving a concern according to an embodiment of the present invention.
Referring to FIGS. 6 and 8, the controller 280 checks the application installed in the user device 200 in step S310. For example, as a result of the confirmation, it is assumed that the app installed in the user device 200 has eight apps, namely App03, App04, App05, App06, App07, App08, App09 and App10.
Next, in step S320, the control unit 280 derives interests of the user from the apps installed in the user device 200 using the app interest information 63 of the app information. For example, according to the app interest information 63, each of the eight apps whose App identifiers installed in the user device 200 are App03, App04, App05, App06, App07, App08, App09, , Travel, learning, learning, performance, and performance, the control unit 280 can derive user's interests as learning, traveling, and performing.
Next, the controller 280 may calculate the degree of interest of the user's interest using at least one of the number of installed apps and the usage time in step S330. For example, since the interest categories of the eight apps having the app identifiers App03, App04, App05, App06, App07, App08 and App09 installed in the user device 200 are five for learning, one for travel, and two for performance , The control unit 280 can calculate interest of each of learning, travel, and performance as 5/8, 1/8 and 2/8. As another example, assuming that the user uses an average of 120 minutes, 40 minutes, and 10 minutes a day for each of the categories of learning, travel, and performance, the control unit 280 sets 120, 170, 40/170 and 10/170, respectively. On the other hand, as another example, the interest can be calculated using both the number of apps and the usage time. The number of apps to learn, travel, and performances are 5/8, 1/8, and 2/8, respectively, and interest in learning, travel, and performance is 120/170, 40/170, 10/170. Then, the interest (5/8 ㅧ 120/170), (1/8 ㅧ 40/170), (2/8 ㅧ 10/170) of interest in learning, travel and performance using both the number of apps and the usage time .
In step S340, the controller 280 arranges interests of the user according to the degree of interest. For example, if there are 5 learning, 5 travel, and 2 performances, the interest categories of the seven apps are as follows: You can sort. As another example, if users spend an average of 120 minutes, 40 minutes, and 10 minutes on each day of learning, travel, and performance apps, the user's interests are considered to be more interesting and more aligned with learning, travel, and performance can do. As another example, when considering both the number of apps and the amount of time spent, the interests of each of the learning, travel, and performance (5/8 ㅧ 120/170), (1/8 ㅧ 40/170), (2/8 ㅧ 10 / 170), the user's interests can be sorted into learning, traveling, and performing according to the degree of interest.
On the other hand, interest can be adjusted by weighting the above-mentioned interests. The weight of this interest can be extracted through the device information. For example, when the game app is installed, the battery replacement period is short, and the screen of the display unit 260 is turned on, the control unit 280 continuously changes the tilt of the user device 200 through the sensor unit 230 If detected, the interest of the game of interest can be weighted. As another example, if the capacity of the controller 280 is larger than the number of videos stored in the storage unit 270, the battery replacement cycle is short, and the earphone connection time is longer than a predetermined time, . As another example, the control unit 280 can weight the interest level of interest music when the music file of the user has a predetermined capacity or more and the earphone connection time is longer than a predetermined time. As another example, if the number of APs retrieved through the communication unit 210 is equal to or greater than a predetermined number, and the time during which the user is walking is longer than a predetermined time and the number of financial (payment) characters increases, Weights can be given to the degree of interest. As described above, according to the present invention, since the interest is weighted through the device information, the ranking of the user's interest can be more accurately estimated.
Next, a method of deriving the user's lifestyle from the profile information will be described. Lifestyle in an embodiment of the present invention refers to a user's lifestyle and behavior that can be derived from the user device 200. That is, in the embodiment of the present invention, the lifestyle is basically derived based on the device information. In the embodiment of the present invention, the lifestyle includes a sleeping time, a sleeping time, a weather time, a working time, a time required for commuting, a time at work, do. In order to derive such a lifestyle, an event for deriving a specific lifestyle is preset. The set event may include at least one of time and position as its attribute. And the location and time at which the event occurred can be derived through the device information. When the location and time of occurrence of such an event are derived, the lifestyle of the user is derived from the location and time at which the event occurred. For example, the control unit 280 can obtain the location of the event through the location information derived from at least one of the communication unit 210, the location information receiving unit 220, and the sensor unit 230. The control unit 280 includes a clock module including a crystal oscillator in the user device 200 and a time information or position information receiver 220 included in a signal received from the base station through the communication unit 210. [ The time of occurrence of the event of the user device 200 can be obtained through the time information included in the signal received from the GPS satellite through the GPS satellite. Thus, the time and location of the event occurrence can be obtained through the device information.
More specifically, at least one event related to time and position is set for each of the sleeping time, the rising time and the sleeping time of the user's lifestyle as follows, and the control unit 280 sets the time and position of the set event After the derivation, the following lifestyle can be derived based on this. The control unit 280 can derive the settlement area from the user's profile, as described above. In this way, the controller 280 is located in the residence area of the user through at least one of the communication unit 210, the location information receiving unit 220, and the sensor unit 230, (For example, between 10 pm and 8 am the following day), the time at which the stop state starts is estimated as the sleep time. The control unit 280 estimates the time when the alarm is set and the alarm sounds or the time when the user device 200 is picked up through the sensor unit 230 as the weather time. Further, the control unit 280 can estimate the time from the estimated sleeping time to the rising time as the sleeping time.
Then, when at least one event related to the time and location of the user's lifestyle, such as the time of work, the time required for the work, the time of the work, the time required for the work and the working time, is set, Can be derived. First, location information of the work place is additionally required in addition to the location information of the residence to derive the work time, the work time, the work time, and the commute time. Accordingly, the control unit 280 derives the position information of the workplace. For example, the control unit 280 can determine the workplace using the acquired location information when the pause state continues for a predetermined time or more within a predetermined work expectation time (for example, from 9:00 am to 6:00 pm on the same day). The control unit 280 can acquire the position information of the workplace through at least one of the position information receiving unit 220, the sensor unit 230, and the communication unit 210, as in the case of deriving the residence. In this way, the controller 280 obtains the location information of the residence and the workplace using the location information of the communication unit 210, the location information receiving unit 220, and the sensor unit 230, 200) departs from the user's residence and enters the user's workplace, the time from departure from the residence to the time when the user enters the workplace is estimated as the time required to go to work, and when the user enters the workplace, do. The control unit 280 may also use the location information of at least one of the communication unit 210, the location information receiving unit 220 and the sensor unit 230 to allow the user device 200 to depart from the user's workplace and enter the user's home , The time from departure from the workplace to the time when the worker enters the residence is estimated as the time required for leaving work and the time when the worker leaves the workplace is estimated as the work time. Then, the control unit 280 estimates the time from the estimated time of work to the workout time as the working time.
Likewise, the time at home, the time of outdoor activity and the time of outdoor activity during the user's lifestyle can be derived as follows. The control unit 280 uses the positional information of at least one of the positional information receiving unit 220, the sensor unit 230, and the communication unit 210 in a state of acquiring the position information of the residence and the work location, Estimate the time at home by calculating the time in the residence. The control unit 280 calculates the time not in the residence area and not at the workplace by using the positional information by at least one of the position information receiving unit 220, the sensor unit 230 and the communication unit 210, Respectively. In particular, the control unit 280 uses the positional information of at least one of the position information receiving unit 220, the sensor unit 230, and the communication unit 210 on weekends to calculate the time not in the place of residence, Estimate it as outdoor time.
In the meantime, the lifestyle in the embodiment of the present invention is not limited to those listed above. In the above-described embodiment, an event related to at least one of time and position is set in advance to derive a lifestyle, and the time and position of the event are derived through the device information. Then, The user's lifestyle is derived. In other words, in the embodiment of the present invention, the lifestyle includes the user's lifestyle and behavior. Accordingly, in accordance with the embodiment of the present invention, in addition to the lifestyle derived through the event, the device information that can be directly derived through the user device 200 may be a lifestyle itself. For example, the lifestyle of a user may include a daily average call time, a daily average number of outgoing calls, a daily average number of incoming calls, a call top3 concentration (%), It can also be derived directly from device information such as a number of time zones, number of contacts, number of male contacts, number of female contacts, and so on. Furthermore, the control unit 280 can derive the degree of networking management of the user through a large number of calls, letters, and contacts. That is, in the embodiment of the present invention, the lifestyle further includes network connection management information.
As described above, the profile server 100 can construct a profile database based on profile information received from a plurality of users through the same method as the embodiment of FIG. Accordingly, the profile server 100 can compare the profile information of one user with the profile information of a plurality of users. Such a method will be described. 9 is a flowchart illustrating a method of providing profile information according to an embodiment of the present invention. FIG. 10 is a view for explaining interest comparison information in an embodiment of the present invention, and FIG. 11 is a view for explaining lifestyle comparison information according to an embodiment of the present invention.
Referring to FIG. 9, it is assumed that a profile database including profile information of a plurality of users is constructed in the storage module 120 of the profile server 100 in step S410.
The control unit 280 of the user device 200 accesses the profile server 100 through the communication unit 210 and requests profile information in step S420. The control module 130 of the profile server 100 processes the profile information included in the profile database of the storage unit 120 in step S430 so that the user of the user device 200 can obtain profile information of another user And compares at least one of interest comparison information and lifestyle comparison information.
10, the control module 130 constructs interest comparison information in which users' interest and interests of a plurality of other users having at least one profile identical to the user's profile are listed in order of interest, based on the profile database . More specifically, first, the control module 130 extracts interests of the users listed in order of interest from the profile database, and incorporates them into interest comparison information. Here, it is assumed that the user's profile is in her 30s, female, and single. Accordingly, the control module 130 extracts interests of a plurality of other users having the same profile and at least one profile so that the user can compare interests of the users with those of other users. That is, the profile extracts interests of other users whose profiles are in the 30s, at least one of the women and the unmarried have the same profile. In the example of FIG. 10, it is possible to compare with the interests of other users in the three groups, including the other users with a profile of thirty, thirties, other users who are female, and other users who are female, Respectively. The control module 130 accumulates the number of interests of the extracted plurality of other users and determines the order of interest in descending order of the number of accumulated interests. For example, interest marriages, budgets, travel, health, and leisure in the other groups of users with profiles of 30 are 57, 48, 45, 15, and 10 interests, respectively. Accordingly, the order of interest is marital, financial, travel, health, leisure.
11, the control module 130 determines whether or not the overall average of the lifestyles of a plurality of other users having at least one profile identical to the profile of the user based on the profile database, Can be configured as lifestyle comparison information. More specifically, first, the control module 130 basically extracts the user's lifestyle from the profile database. Here, it is assumed that the user's profile is in her 30s, female, and single. In addition, the control module 130 extracts lifestyle of a plurality of other users having at least one profile that is the same as the profile of the user so that the lifestyle of the user can be compared with the lifestyles of other users. In the example of FIG. 11, it can be compared with the lifestyle of other users belonging to three groups, including 30 other users, 30 other users, female users, and 30 other users, Respectively. The control module 130 then obtains an overall average of the lifestyles of a plurality of other users having at least one profile with the user's profile. For example, in the case of a 30-year-old female, or an unmarried person, the average sleeping time is 6 hours. In addition, the control module 130 obtains a ranking of the user's lifestyle occupied in the overall average obtained previously. For example, in the case of 30s, female, and unmarried, the average sleeping time is 6 hours, and when the user's sleeping time is 5 hours, it corresponds to the top 10%. Accordingly, the control module 130 compares lifestyle comparison information with the ranking of the overall average of the lifestyle of the plurality of other users having at least one profile identical to the profile of the user, the lifestyle of the user, and the overall average.
Next, the control module 130 transmits at least one of the interest comparison information and the lifestyle comparison information to the user device 200 through the communication module 110 in step S440. Then, the control unit 280 of the user device 200 displays at least one of the interest comparison information and the lifestyle comparison information received in step S450 through the display unit 260. [ Accordingly, the user can compare his or her interests or lifestyle with other users having profiles similar to themselves through the interest comparison information and the lifestyle comparison information.
Meanwhile, in the above-described embodiment, the profile server 100 has configured the interest comparison information and the lifestyle comparison information in a predetermined format and provided to the user device 100, but the present invention is not limited thereto. According to an embodiment of the present invention, a user may set a different group of users that want to compare interests or lifestyle or want to know. That is, if the profile factor includes sex, age, marital status, etc., the user can select sex, age, and marital status. For example, the user may request the profile server 200 to compare information of interest and lifestyle of other users having profiles of male, 30, unmarried person by operating the user device 100. [ Then, the profile server 200 configures interest comparison information and lifestyle comparison information according to the request, and provides the comparison information to the user device 100.
According to the embodiment of the present invention, since a user is profiled based on information extracted from an app installed and used by a user and a user device 200 used by a user, not only basic information about the user but also information about the user The taste can be accurately estimated. Further, according to the embodiment of the present invention, since the database constructed by receiving the profile information of a plurality of users is statistical information of a plurality of users, i.e., groups, not a person, the database can be more accurately represented . The statistical information according to the profiling technique according to the present invention can be reworked and utilized in various fields such as advertisement, target marketing, and the like.
Meanwhile, according to the embodiment of the present invention, the personality and tendency of the user can be derived using at least one of the interests, lifestyle and device information derived above. First, a method for deriving the characteristics of a user according to an embodiment of the present invention will be described. 12 is a flowchart illustrating a method of deriving a user's characteristic according to an embodiment of the present invention. The following Tables 1 to 4 are examples of the device information used to derive the characteristics of the user according to the embodiment of the present invention.
menu
Collection Items
telephone
Average call duration per second (seconds)
Daily average outgoing call time (seconds)
Daily average call duration in seconds
Average number of outgoing calls per day (cases)
Average number of incoming calls per day (number of calls)
Daily average number of missed (cases)
Average number of rejections per day (cases)
Number of Unknown Numbers per Day (case)
Currency Top3 Concentration (%)
Many hours of calls (24 hours)
Average number of outgoing calls per day (cases)
Average number of recipients per day (cases)
Average number of financial characters per day (cases)
Financial characters Many times (24 o'clock)
Person
Number of contacts (thing)
Men's contact (gun)
Woman contacts (Gun)
Marriage contact (thing)
Over 50 contacts (case)
60 (Contact)
Work experience contact (case)
20 Contact information (case)
10 elementary school students contact (case)
Contact for teenager middle and high school students (case)
Buddhist contact (thing)
Catholic contact (case)
Christian contact (thing)
Average daily number of appointments (cases)
Most appointments during the week (24 hours)
Most weekend appointment time (24:00)
menu
Collection Items
media
Total photos (events)
Total Photo Capacity (MByte)
Average daily photo capacity (MByte)
Average number of photos per day (cases)
Photo Weekend Concentration (%)
Photo Rear Resolution (pixels)
Photo front resolution (pixels)
Photo Self-Percentage (%)
Lots of photos taken (24 hours)
Total music (cases)
Total Music Capacity (Gun)
Average music capacity per day (MByte)
Average music per day (cases)
Listening to music Top3 Intensity (%)
Music Artist Top3 Intensity (%)
Music Album Top3 Intensity (%)
Music downloads Many hours (24 hours)
Listening to music Recent (Sunday)
Total videos (events)
Total video capacity (cases)
Average Video Size per Day (MByte)
Average video capacity (MByte)
Average video duration (minutes)
Average number of videos per day (cases)
Video downloads Many hours (24 hours)
menu
Collection Items
Smartphone
Set font size
Android version
No average daily data connections (hours)
Average mobile connection time per day (hours)
Average daily Wi-Fi connection time (hours)
Daily average Bluetooth time (hours)
Daily average Bluetooth on time (hours)
Daily average Bluetooth connected time (hours)
Daily average GPS time (hours)
Daily average GPS on time (hours)
Daily average GPS connected time (hours)
Daily average screen on time (hours)
Weekday screen on Lots of time (24 hours)
Weekend screen on Lots of time (24 hours)
Large screen during weekday Many hours (24 hours)
Weekend screen grows a lot of time (24 hours)
Average daily headset connection time (hours)
Connecting headset during the week Many hours (24 hours)
Weekend headset connection Many hours (24 o'clock)
Daily average sound mode Time (hours)
Daily average silent mode time (hours)
Daily average vibration mode time (hours)
Mode sound -> Vibrant time (24 hours)
Mode Vibration -> Sound Lots of time (24 hours)
Mode sound -> Silence Much time (24 o'clock)
Mode Silence -> Loud sound (24 hours)
Average number of weekly day-to-day increases (cases)
Average number of days down on weekdays (cases)
Average daily weekly pressure
Daily average weekday down pressure
The most time (24 hours)
Most down time (24 hours)
Highest pressure
Highest pressure
Daily average stop time (hours)
Daily average moving time (hours)
A lot of time (24 o'clock)
Many times during weekdays (24 hours)
Weekend stop Many hours (24:00)
Weekend moves a lot of time (24 o'clock)
Average daily charge time (hours)
Charging during the week (24 hours)
Weekend charge many hours (24 hours)
Daily average battery replacement count (case)
Battery Replacement Many hours (24 hours)
Average WiFi per day (thing)
Weekly average WiFi count (case)
Weekly average WiFi count (thing)
Weekly Vehicle Average Wi-Fi Number (case)
Weekly Vehicle Average WiFi Number (Gun)
Still average WiFi per day (thing)
Weekly Still Average WiFi count (Gun)
Weekend Still Average WiFi Number (Gun)
Average number of WiFi at 03:00 in the house (thing)
Daily Wi-Fi a lot of times Average number (thing)
Daily Wi-Fi less time average number (case)
Daily Wi-Fi a lot of times (24 o'clock)
Daily Wi-Fi less time (24 hours)
Many Wi-Fi during the week (24 hours)
Weekday Wi-Fi less time (24 hours)
Weekend Wi-Fi a lot of times (24 o'clock)
Weekend Wi-Fi less time (24 hours)
Daily average Walking hours (24 hours)
Walking a lot of time during weekdays (24 o'clock)
Weekend Walking Many hours (24 hours)
Daily Average Vehicle Much time (24 hours)
Weekday Vehicle Many hours (24 hours)
Weekend Vehicle Much Time (24 o'clock)
Daily average Running a lot of time (24 hours)
Weekday Running Many hours (24 hours)
Weekend Running Many hours (24 hours)
menu
Collection Items
step
Average number of steps per day
Average daily walking distance (Km)
Average daily walking time (minutes)
Average daily calorie consumption (calories)
Daily average running time (minutes)
Average Bike Time per Minute (Minutes)
Average daily vehicle travel time (minutes)
Vehicle driving Weekend concentration (%)
Average vehicle driving time (min)
Sleep
Daily average sleep time (hours)
Average bedtime (24 hours)
Average weather time (24 hours)
Average weekday bedtime (24 hours)
Weekday average weather time (24 hours)
Weekend average bedtime at 24 o'clock)
Weekend average weather time (24 hours)
Sleep weekend concentration (%)
Work
Out time
House time
Home time zone
12 and Table 1 through Table 4, the control unit 280 determines the number of contacts registered in the user device 200, the average daily appointment number registered in the calendar application, If the number of times (average number of daily calls and average number of daily calls received) is greater than the predetermined number, it is classified as outgoing personality. On the other hand, the control unit 280 controls the number of contacts registered in the user device 200, the daily average number of appointments registered in the calendar application, and the average number of calls (the average number of daily calls, Average number of receptions) is less than the predetermined number, and the call Top3 concentration (%) is equal to or greater than a predetermined value.
Referring to FIG. 12, in step S510, the controller 280 collects at least one predetermined information to determine the personality. Hereinafter, at least one piece of information set in advance to determine the personality is referred to as " personality information ". The personality information is preset to at least one of interest, lifestyle and device information. This personality information can be a parameter used as a measure of two contrasting characteristics. For example, the two contrasting characteristics may be extroverted, introverted, active, passive, optimistic, and pessimistic. For example, the embodiment of the present invention can determine whether it is extroverted personality or introverted personality. Personality information that can be used as a measure to determine this personality is the number of contacts, the average number of appointments per day (people menu in Table 1), the average number of daily calls, the average number of calls received per day, ), Outgoing time, return time (one menu in Table 4), and the like. In addition, the personality information can be a lifestyle such as an average time to go out per week, a change in home time, and the like. Moreover, the personality information can be whether or not the interest is sports, and whether the interest and interest are drama and the interest thereof.
The control unit 280 may determine the nature of the user according to the collected personality information in step S520. For example, when the number of contacts, the average number of daily appointments, the average number of daily calls and the average number of daily receipts are equal to or greater than a predetermined value, the currency Top3 concentration is less than a predetermined value, , The change of home time is not less than a predetermined value, the interest is sports, and the interest is not less than a predetermined value, the user is determined to be outgoing personality. As another example, when the number of contacts, the average number of daily appointments, the average number of daily calls and the average number of daily receipts are less than a predetermined value, the currency Top3 concentration is equal to or greater than a predetermined value, , The change in home time is less than a predetermined value, the interest is a drama, and the interest is greater than or equal to a predetermined value, the user is determined to be introverted. In step S530, the control unit 280 displays the determined user's nature through the display unit 260. [
On the other hand, it is possible to determine whether the above-described introvert personality or extrovert personality is determined through comparison of a plurality of users. Such an embodiment will be described. 13 is a flowchart illustrating a method of deriving a user's characteristic according to another embodiment of the present invention.
Referring to FIG. 13, in step S610, the control module 130 of the profile server 100 acquires the characteristics of interest, lifestyle, and device information from user devices 200 of a plurality of other users through the communication module 110 It is assumed that personality information, which is at least one piece of information set in advance, is accumulated and stored in the storage module 120, and a personality information statistic is generated according to the accumulation. This personality information is as described in Fig. For example, the personality information required to determine outgoing personality and introverted personality includes the number of contacts, the average daily appointment number (person menu in Table 1), the average daily number of calls, the average number of daily calls received, A lifestyle such as an average time to go out, a change in home time, and the like, if the interest is sports, the interest and the interest are drama , A concern including the interest, and the like. Thus, personality information statistics may be statistics that can be obtained from personality information received from each of a plurality of other users' user devices 200.
The controller 280 of the user device 200 may provide personality information to the profile server 100 in step S620. This personality information is the same as the personality information described in the steps of FIG. 12 and S610.
Upon receiving personality information from the user device 200, the control module 130 of the profile server 100 compares the received personality information with the personality information statistics in step S630 in step S630, .
For example, the control module 130 determines whether the number of contacts of the received personality information, the number of daily average appointments, the average number of calls per day, the average number of outgoing hours per week, When the top 3 concentration is within the lower 30%, the personality of the user is determined to be outgoing personality. On the other hand, the control module 130 determines whether or not the number of contacts of the received device information, the number of daily average appointments, the average number of calls per day, the average amount of outgoing time per week, If the concentration is within the top 30%, the personality of the user is determined to be introverted.
In step S640, the control module 130 transmits the user characteristics determined by the communication module 110 and statistical information on the user to the user device 200. [ Here, the statistical information about the user may be information indicating the top percentage of the number of contacts, the average number of daily appointments, the average daily number of calls, the top 3 concentration of the currency, the average time spent per week, Next, the control unit 280 of the user device 200 may display the user's personalities and statistical information about the user determined through the display unit 260 in step S650.
Next, a method for deriving the tendency according to the embodiment of the present invention will be described. 14 is a diagram for explaining a method of deriving a propensity according to an embodiment of the present invention. According to an embodiment of the present invention, a user's tendency can be derived according to a predetermined criterion by using a user's profile, interest, lifestyle, and device information. As shown in FIG. 14, the embodiment of the present invention classifies users into groups according to the derived tendencies, and each group is expressed as a "family ". Such a group may include a large group, a medium group, a small group, and the like. That is, a group may have a higher group and a lower group. As shown in the example of FIG. 14, the tour group includes domestic tourists and overseas tourists as subgroups, and domestic tourists include campers as subgroups.
Hereinafter, a method for deriving a tendency of a user according to an embodiment of the present invention will be described. 15 is a flowchart illustrating a method of deriving a tendency of a user according to an embodiment of the present invention.
Referring to FIG. 15, in step S710, the controller 280 collects at least one predetermined information to determine the propensity. The information required to determine such a tendency may be at least one of a user's profile, interest, interest in interest, lifestyle, and device information. This information is used as a measure to determine whether there is a tendency or not. That is, a group of users having similar inclinations (hereinafter, referred to as 'inclinable groups') is defined in advance, and information that can be used as a scale for determining whether there is a tendency related to the inclination group or not is set in advance. This information can be selected from at least one of the user's profile, interest, interest of interest, lifestyle and device information. In particular, lifestyle or device information can be processed into information for measuring the measure of propensity. According to the embodiment of the present invention, the user can be classified into the incentive group based on the collected at least one information. For this purpose, the controller 280 determines a weight for the corresponding inclinable group ('group') according to the information collected in step S720, and assigns the determined weight to the corresponding inclinable group ('group') . Thus, various examples of determining the weights and assigning the determined weights to the corresponding tendency groups (' ~ group) are as follows.
1. Travel
Travel includes domestic tourists and overseas tourists. Domestic tourists include campers. The control unit 280 moves to a position spaced apart from the user's residential area by a predetermined distance or more through the position information receiving unit 220 and the sensor unit 230. The greater the number of times that the user is asleep, can do. In addition, the control unit 280 assigns a high weight to the traveling family as the user is interested in the travel (when the app has the travel category such as camping, lodging, rental car, etc.). The control unit 280 assigns a high weight to domestic tourists as the number of times that the sleeping position is domestically is greater in the traveling family. As the number of times that the sleeping position is out-of-home is greater, the control unit 280 can assign a higher weight to the overseas traveling family. The control unit 280 assigns a high weight to the overseas tourists as the interest of the user is the foreign tour (the case where the travel category, the overseas stay, the guidebook, etc., . If your interests are camping (if the interest category has camping apps installed), the higher the interest in interest camping, the higher the weight is given to campers.
2. Shoppers
Shoppers include online and offline shoppers. The control unit 280 assigns a high weight to the shopping group when the user is interested in shopping (in a case where an app of interest category such as 11th, Kupang, auction, department store, etc. is installed). In addition, the control unit 280 determines whether the online shop is interested in the online shopping (the online shop is installed in the interest categories such as 11th, Kupang, and auction), and the online shopping Give the family a high weight. The control unit 280 determines the number of steps (Table 4), which is device information acquired through the sensor unit 230, in a location where the number of AP searched through the communication unit 210 is large, And gives a high weight to the offline shopping group.
3. Entertainment Family
Entertainment groups include game groups, movie families, and musical groups, and movie families include movie theaters and VODs. Music families also include downloading families and streaming families. The control unit 280 gives a higher weight to the game as the interest of the user is a game (the interest category is an online shopping app) and the interest of the game is higher. The control unit 280 controls the display unit 260 so that the greater the number of times the shake is detected through the sensor unit 230 while the screen of the display unit 260 is turned on while the battery replacement period of the user device 200 is short, do. The control unit 280 may be configured to allow a user to pay attention to a movie with a high interest in a movie family (such as Lotte Cinema, CGV, GomTV, NETFLIX, and a movie / . The control unit 280 assigns a high weight to the musical group as the interest of the user is music (a musical piece having a musical interest category such as musical piece, melon, bug, genie, and sylvia) is installed. The control unit 280 gives a high weight to musical groups as the earphone connection time becomes longer.
4. Health
The Hells include Walking, Running, Bicycling, Golf, and Mountaineering. The control unit 280 assigns a high weight to the health group when the user is interested in the exercise (in the case where a mobile unit has an exercise app, such as Mi-pit, S health, and fitness). The control unit 280 assigns a high weight to the walking group as the average number of treads per day or the time during which the movement state is in the walking state is longer. The control unit 280 assigns a high weight to the running group as the time for which the daily average user is running in the health group is longer. The control unit 280 gives a higher weight to the bicycle group as the daily average user of the health group is in the bicycle traveling state in the moving state. The control unit 280 has a golf course in which a golf course of interest is a golf course, and is interested in golf, and the higher the interest level, the higher the weight of the golf club. The control unit 280 assigns a weight to a mountain climbing as the user's interest is climbing (when a rambler, a mountain road, an oxygen tank, and a climbing-related app are installed) and the degree of interest is high. The control unit 280 gives a high weight to mountain climbers as the number of times of staying for one hour or longer in an area where the atmospheric pressure is 990 or less and the altitude is 300 m or more.
5. Couples / Singles / Naholic / Earlybird / Owl / Yard
The control unit 280 assigns a high weight to the couple as the interest of the user is a date (in the case where a date, a play, a date pop, or a date related app is installed), and a degree of interest is high.
If the user is unmarried, the control unit 280 gives a predetermined weight to the singles. If the user is not a couple, the control unit 280 gives the singles a predetermined weight. In addition, the control unit 280 gives a higher weight to the singles as the concentration of the call Top3 is higher.
The control unit 280 gives a higher weight to a solo group as the interest of the user is a delivery food (when a delivery app such as a nation of delivery, a delivery cradle, a yogi yodo, or the like is installed). In addition, the control unit 280 assigns a higher weight to the solo group as the frequency of use of the convenience store application is higher. In addition, the control unit 280 assigns a predetermined weight to a group of VODs or a group of games. In addition, the control unit 280 is provided with apps for playing games such as a direct game room, a coffee room, and the like, and the higher the frequency of use, the higher the weight is given to the solo group.
The control unit 280 assigns a high weight to the Early Birds as the average time of the user's work is fast.
The control unit 280 gives a higher weight to the owl group as the average sleep time of the user is delayed.
The control unit 280 gives a higher weight to the establishment of the yard as the number of promises of the user, the number of contacts, the number of new contacts added to the monthly average, and the average number of calls per day increases.
6. Early Adapters / Selphy / Allied / Readers / Self-help / Fishing
The control unit 280 assigns a high weight to the early adopter group as the user is interested in the early adopter (if Mi pit, S health, Moto 360, or a Bluetooth connection app is installed). In addition, the control unit 280 assigns high weight to early adopters as the average Bluetooth connection time becomes longer. The control unit 280 assigns a high weight to the early adopters as the number of Bluetooth connection lists increases.
The control unit 280 assigns a high weight to the SELFI family when the user is interested in the user's interest (when a photograph application such as a candy camera, a camera 360, a camera, or the like is installed). The control unit 280 assigns a higher weight to the self-peer group as the self-car ratio is higher among all the photographs of the user. The control unit 280 assigns a higher weight to the SELFI group as the SELKA ratio is higher among the daily average photographs.
The control unit 280 assigns a high weight to an alien family when the interest of the user is discounted (when a discounted app is installed, such as a mobile agent membership, a CLiP, a time ticket, a daily hotel, etc.) and the degree of interest is high.
The control unit 280 assigns a high weight to the reading group as the interest level is high when the interest of the user is a reading interest (in a case where a reading interest category such as Yes24, Aladdin, Reader's Book, Kyobo Book, etc. is installed).
The control unit 280 is a device that carries the interest of the user in the automobile (navigation, OBD, car system, used car app, app developed for sales of automobile, etc.) Give the family a high weight.
The control unit 280 assigns a high weight to the fishing group when the user is interested in fishing (in the case where a fishing app is installed in a concern category such as a sea fishing person, a waterfall, fishing, or a fishing point).
7. Uptown / Downtown / Apartment / Parenting / Pet / Family
If the number of APs detected in the residence area is less than the predetermined number, the control unit 280 gives a predetermined weight to the uptown group. The control unit 280 gives a predetermined weight to the uptown group when the time of the work is longer than a predetermined time. The control unit 280 assigns a predetermined weight to the uptown group when it is determined that the user is going to commute to work by using the car (from the residential area to the company).
The control unit 280 assigns a predetermined weight to the downtown group when the number of APs detected in the residence area is equal to or greater than a predetermined number, and when the work time is less than the predetermined time.
The control unit 280 gives a predetermined weight to apartment families when the number of APs detected in the residential area is a predetermined number or more. In addition, when the measured pressure values measured through the sensor unit 230 are different from each other by two or more before entering the house, the control unit 280 assigns a predetermined weight to the apartments.
The control unit 280 assigns a high weight to the nursing family as the interest of the user is child care (Pororo, do not cry, baby, child care assistant, and child care related application are installed). In addition, the control unit 280 gives a predetermined weight to the nursing family when the outgoing time is less than the predetermined time. If the user's interest is child care, the time spent is less than a predetermined time, and the average number of pictures is five or more, the control unit 280 assigns a predetermined weight to the nursing family.
The control unit 280 assigns a high weight to the pet dog as the interest of the user is a pet dog (pet box, pet market, dog note, or a pet related app).
The control unit 280 assigns a high weight to the Aomi family when the interest of the user is an interest (when a cat is raised, when a cat is raised, when an app for appetizing is installed) and the degree of interest is high.
In summary, the control unit 280 may determine a weight for the incentive group based on the degree of interest and interest of the interest, and assign the weight to the incentive group. In particular, when the weight is determined based on the degree of interest and the degree of interest of the interest, the control unit 280 may assign a higher weight to the tendency group as the degree of interest is higher while having a concern related to the particular tendency group. For example, when the interest category is an application having a movie and the user's interest is a movie, the control unit 280 may determine the weight according to the degree of interest and give the determined weight to the movie family. As described in step S330, the degree of interest is proportional to the number of installed apps and the usage time, and the higher the degree of interest, the higher the weight is given. For example, it is assumed that a weight of 5 is assigned to each of the number of apps, and a weight of 5 is given to every 20 minutes of use time of the app according to a predetermined rule. So, for the first example, if the number of apps is 4, and the usage time of the app is 120 minutes, the weight is 20 + 30 = 50. Also, as a second example, if the number of apps is 2, and the app use time is 260 minutes, the weight is 10 + 65 = 75. Thus, the second example is given a higher weight than the first example.
In addition, the control unit 280 may determine a weight for the inclinable group based on the profile or the lifestyle, and assign the weight to the inclinable group. In particular, if the user has a profile or lifestyle associated with a specific incentive group, the control unit 280 may assign a predetermined weight to the incentive group. For example, if the profile of the user is unmarried, the control unit 280 may assign a predetermined weight (e.g., weight 50) to the singles.
In addition, the controller 280 may determine a weight for the inclinable group based on the device information, and assign the weight to the inclinable group. At this time, the control unit 280 calculates the number of occurrences of a typical behavior pattern of the users belonging to the propensity group through the device information, and the higher the occurrence frequency, the higher the weighting value can be given.
The control unit 280 moves to a position spaced apart from the user's residential area by a predetermined distance or more through the position information receiving unit 220 and the sensor unit 230. The greater the number of times that the user is asleep, can do. Here, according to the embodiment of the present invention, in order to classify a traveling group, a typical behavior pattern of a traveling family is set in advance such as "moving to a position away from a residential area by a predetermined distance and then going to bed." The control unit 280 can determine whether the user is away from the residential area by a predetermined distance or more and whether the user is going to sleep at the location through the location information receiving unit 220 and the sensor unit 230 as the device information. According to such device information, the control unit 280 can calculate the number of times a typical behavior pattern of a traveling person is generated. Then, the control unit 280 assigns a weight to the traveling family according to the calculated number of times. That is, the higher the number of times, the higher the weight will be given, and the lower the number, the lower the weight will be given.
After assigning a weight to each of the tendency groups, the controller 280 classifies the tendency of the user or the user as a tendency group in which the weights given in step S720 are greater than or equal to a predetermined value in step S730. For example, it is assumed that the standard value of the domestic travel group is 90 or more and the standard value of the camp group is 50 or more. At this time, if the weight of the user is 97 for domestic tourists and the weight for campers is 45, the user is classified as domestic tourists but not as campers.
In this manner, when the classification is completed, the controller 280 may display the tendency group ('family') classified by the user on the display unit 260 in step S740. An indication of this propensity group may include a description of the propensity group.
Meanwhile, according to another embodiment of the present invention, a user's tendency may be determined through comparison of a plurality of users. Such an embodiment will be described. FIG. 16 is a flowchart illustrating a method of deriving a tendency of a user according to another embodiment of the present invention. FIG. 17 is an exemplary screen for explaining a method of deriving a tendency of a user according to another embodiment of the present invention.
Referring to FIG. 17, in step S810, the control module 130 of the profile server 100 determines the tendency of the control module 130 from the weight for each of the tendency groups collected from the user devices 200 of the plurality of other users through the communication module 110 It is assumed that the group statistics are generated, and the tendency group statistics are stored. Here, it is assumed that the propensity group statistics are generated by collecting weights for each propensity group from each of the 2 million user devices 200 of users. For example, the tendency group statistics of the tendency group among the tendency group statistics include a weight for each of the two million users, a mean and a standard deviation of the weight for the two million users of the trip, and the like.
On the other hand, the controller 280 of the user device 200 calculates the weights of each propensity group in step S820. Such a method is as described in steps S710 and S720. Then, the control unit 280 of the user device 200 transmits the weights of each of the propensity groups calculated through the communication unit 210 to the profile server 100 in step S830.
Upon receiving the weights of each of the propensity groups calculated from the user device 200, the control module 130 of the profile server 100 includes the weights of the propensity groups received in step S840 in the propensity group statistics. In step S850, the control module 130 compares the propensity group statistics with the weights of the received propensity groups, and classifies the users into the propensity groups according to a predetermined criterion. Here, the predetermined criteria may be set to classify the tendency group into the tendency group when the weight of the tendency group has a weight within the upper 30% of the total tendency. For example, the weights of the tribes in the received propensity group weights are 93, which, when compared to the propensity group statistics, are weighted to the top 30%, then the users can be classified as traveling. On the other hand, these criteria may be set differently for each propensity group. For example, the top 10% of the domestic travel group and the top 40% of the overseas travel group. According to the trend group statistics, the weight of the top 10% of the domestic tourists is 91, the top 40% of the overseas tourists are foreign tourists, while the weight of the domestic tourists is 80, Is 39, the user is not a domestic travel member but can be classified as an overseas travel member.
Then, the control module 130 includes the incentive group classified in step S860 in the incentive group classification statistics. The tendency group group classification statistic is a statistic for a tendency group to which each of a plurality of users belongs (classified). Next, in step S870, the control module 130 extracts a propensity group classification statistic associated with the propensity group (user propensity group) classified by the user. The propensity group classification statistics associated with the user's propensity group include statistics among the plurality of propensity groups when there is a plurality of propensity groups of the user. For example, if the user is a group of propensity to classify is travel or overseas, the tendency group classification statistic associated with the user's propensity group is a statistical value between the tourists and the overseas tourists (for example, 32% of the tourists are overseas tourists). Thus, the propensity group classification statistics associated with a user's propensity group include the percentage or number of users who are traveling and traveling abroad.
In step S880, the control module 130 transmits the incentive group classified by the user and the incentive group classification statistic associated with the incentive group of the user to the user device 200 through the communication module 110 in step S880.
The control unit 280 of the user device 200 receives the tendency group classified by the user and the tendency group classification statistics related to the classified tendency group through the communication unit 210 in step S890, . ≪ / RTI > FIG. 17 shows an example of a screen in which the user is classified and the tendency group classification statistics 73 related to the classified tendency group are displayed.
As described above, according to the embodiment of the present invention, it is possible to extract various information from the user device 200, to grasp the personality and tendency of the user, and the detected information can be used as statistical data. Personality and propensity can also be used as marketing material.
Meanwhile, the method according to the embodiment of the present invention described above can be implemented in a form of a program readable by various computer means and recorded in a computer-readable recording medium. Here, the recording medium may include program commands, data files, data structures, and the like, alone or in combination. Program instructions to be recorded on a recording medium may be those specially designed and constructed for the present invention or may be available to those skilled in the art of computer software. For example, the recording medium may be a magnetic medium such as a hard disk, a floppy disk and a magnetic tape, an optical medium such as a CD-ROM or a DVD, a magneto-optical medium such as a floppy disk magneto-optical media, and hardware devices that are specially configured to store and execute program instructions such as ROM, RAM, flash memory, and the like. Examples of program instructions may include machine language wires such as those produced by a compiler, as well as high-level language wires that may be executed by a computer using an interpreter or the like. Such a hardware device may be configured to operate as one or more software modules to perform the operations of the present invention, and vice versa.
While the present invention has been described with reference to several preferred embodiments, these embodiments are illustrative and not restrictive. It will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit of the invention and the scope of the appended claims.
