KR20180131221A - Apparatus for user analysis and control method thereof, and service providing apparatus - Google Patents

Abstract

The present invention provides a user analysis apparatus, an operating method thereof, and a service providing apparatus capable of increasing a targeting service effect and user satisfaction by analyzing an accumulation state for a plurality of behavior logs which are collected in association with a user for a specific period and classified and accumulated according to a plurality of categories and designating an interest category for a user based on a change period of the accumulation state derived as an analysis result to be used for a targeting service.

Description

TECHNICAL FIELD [0001] The present invention relates to a user analysis apparatus, an operation method thereof, and a service providing apparatus,

The present invention analyzes an accumulated state of a plurality of behavior logs collected in association with a user for a specific period and classified and accumulated in a plurality of categories, And a method for specifying a category of interest for the user.

As the market for applications running on mobile devices such as smart phones and tablet pads is rapidly expanding, the related application service market is rapidly expanding.

In a mobile device (hereinafter referred to as a "terminal"), when an application is executed or a service page (for example, a web page) is accessed, an application service provided from the service providing device is received and displayed on an application execution screen or a service page connection screen have.

The application service provided from the service providing apparatus can be considered as a representative case of the advertisement.

On the other hand, in the service providing apparatus, in order to increase the satisfaction of the service, it is general to adopt a targeting service technique to provide a suitable service to the user, that is, to select and provide the targeting service.

In such a targeting service technique, for example, a method of providing a targeting service for a user based on fixed information such as information (e.g., age, sex, residence, interest) input by a user when joining a service is generally performed.

However, such a method of using fixed information has a limitation in positively reflecting the user tendency (interest) that may vary with time, which may result in lowering the user satisfaction with the targeting service.

SUMMARY OF THE INVENTION The present invention has been made in view of the above circumstances, and it is an object of the present invention to provide a method and apparatus for collecting a plurality of action logs collected in association with a user for a specific period, And designating an interest category for the user on the basis of the fluctuation period of the cumulative state derived as an analysis result, thereby utilizing the service as a targeting service for the user.

According to an aspect of the present invention, there is provided a user analysis apparatus comprising: a processor for processing an operation to designate an interest category for a user; And a memory in which at least one instruction executed by the processor is stored, wherein the at least one instruction is collected in association with the user for a particular period of time and comprises a plurality of behavior logs A confirmation command for confirming the cumulative state of the terminal device; And selecting an action log indicating an attribute of the user for the specific period among the plurality of action logs based on the cumulative state of the plurality of behavior logs so that a specific category to which the selected action log belongs is classified into the interest category And a selection command to be designated to be specified.

More specifically, the selection command may include an autocorrelation operation on the cumulative states of the plurality of behavior logs to derive an autocorrelation value of each of the plurality of behavior logs, A specific action log having the largest autocorrelation value among the plurality of behavior logs and having a set ratio relationship with respect to the autocorrelation value of another behavior log is selected as a result of comparing the correlation values.

More specifically, the setting ratio relationship is set such that the second behavior log having the largest autocorrelation value among the plurality of behavior logs excluding the first behavior log having the largest autocorrelation value in the plurality of behavior logs, Wherein a difference between an autocorrelation value of the first behavior log and an autocorrelation value of the second behavior log is equal to or greater than a first threshold ratio for the behavior log and an autocorrelation value of the first behavior log and an autocorrelation value of the third behavior log And a difference in autocorrelation value is equal to or greater than a second threshold ratio that is larger than the first threshold ratio.

More specifically, the selection command may be configured to apply the maximum accumulated number of times during the specific period to a predetermined reference action log in the plurality of behavior logs, And the reference action log may be excluded in the process of selecting an action log.

More specifically, the plurality of behavior logs are divided into at least two subcategories for each of the plurality of categories, and the cumulative status for the plurality of behavior logs is calculated by accumulating the cumulative number of each of the two or more subcategories during the specific period And a graph obtained by rearranging the graphs in a predetermined order.

More specifically, the at least one command is characterized by further comprising a classification instruction to classify the two or more users into a similar user group if there are two or more users whose interest categories match.

According to an aspect of the present invention, there is provided a service providing apparatus including: a processor for processing an operation for providing a targeting service; And a memory in which at least one instruction executed through the processor is stored, the at least one instruction being a confirmation command for causing a user analysis device to confirm service selection information for the user upon a request from the user; And a selection command for selecting a targeting service based on the service selection information so that the selected targeting service is provided to the user.

More specifically, the advertisement selection information includes at least one of an interest category designated for the user and a similar user group to which the user belongs, and the selection command selects the targeting service specified in the interest category , Or selects a targeting service previously provided to another user in the similar user group.

According to another aspect of the present invention, there is provided a method for operating a user analysis device, the method comprising: collecting a plurality of action logs collected in association with a user for a specific period, ; And selecting an action log indicating an attribute of the user during the specific period among the plurality of action logs based on the cumulative state of the plurality of behavior logs, So as to be able to be specified.

More specifically, the selecting step may include an autocorrelation operation on the cumulative states of the plurality of behavior logs to derive an autocorrelation value of each of the plurality of behavior logs, The specific action log having the largest autocorrelation value among the plurality of behavior logs and having a set ratio relationship with respect to the autocorrelation value of another behavior log is selected.

More specifically, the setting ratio relationship is set such that the second behavior log having the largest autocorrelation value among the plurality of behavior logs excluding the first behavior log having the largest autocorrelation value in the plurality of behavior logs, Wherein a difference between an autocorrelation value of the first behavior log and an autocorrelation value of the second behavior log is equal to or greater than a first threshold ratio for the behavior log and an autocorrelation value of the first behavior log and an autocorrelation value of the third behavior log And a difference in autocorrelation value is equal to or greater than a second threshold ratio that is larger than the first threshold ratio.

More specifically, in the selecting step, the maximum number of accumulation times during the specific period is applied to a predetermined reference activity log in the plurality of behavior logs, and the maximum number of accumulation times during the specific period is calculated based on the autocorrelation value corresponding to the maximum accumulation number, And the reference action log may be excluded in the process of selecting an action log.

More specifically, the method may further include classifying the two or more users into a similar user group if there are two or more users whose interest categories match.

Accordingly, according to the user analysis apparatus, the operation method, and the service providing apparatus according to an embodiment of the present invention, a plurality of action logs collected in association with a user during a specific period, Analyzing the cumulative state of the cumulative state, and designating an interest category for the user based on the cumulative state fluctuation period derived as an analysis result, the present invention can be applied to a targeting service, thereby enhancing the effect of the targeting service and the user satisfaction.

1 is a schematic configuration diagram of a targeting service system according to an embodiment of the present invention;
2 is a schematic configuration diagram of a terminal according to an embodiment of the present invention;
3 is an exemplary diagram of a hardware system for implementing a terminal according to an embodiment of the present invention.
4 is a schematic configuration diagram of a user analysis apparatus according to an embodiment of the present invention;
5 to 7 are diagrams for explaining a category selection process according to an embodiment of the present invention;
Figure 8 is an illustration of a hardware system for implementing a user analysis device in accordance with an embodiment of the present invention;
9 is a schematic configuration diagram of a service providing apparatus according to an embodiment of the present invention;
10 is an exemplary diagram of a hardware system for implementing a service providing apparatus according to an embodiment of the present invention;
FIG. 11 is a schematic flowchart for explaining an operational flow in a targeting service system according to an embodiment of the present invention; FIG.
FIG. 12 is a schematic flowchart for explaining an operation flow in a user analysis apparatus according to an embodiment of the present invention; FIG.
FIG. 13 is a schematic flowchart for explaining an operation flow in a service providing apparatus according to an embodiment of the present invention; FIG.

It is noted that the technical terms used herein are used only to describe specific embodiments and are not intended to limit the invention. It is also to be understood that the technical terms used herein are to be interpreted in a sense generally understood by a person skilled in the art to which the present invention belongs, Should not be construed to mean, or be interpreted in an excessively reduced sense. Further, when a technical term used herein is an erroneous technical term that does not accurately express the spirit of the present invention, it should be understood that technical terms that can be understood by a person skilled in the art are replaced. In addition, the general terms used in the present invention should be interpreted according to a predefined or prior context, and should not be construed as being excessively reduced.

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings, wherein like reference numerals refer to like or similar elements throughout the several views, and redundant description thereof will be omitted. In the following description, well-known functions or constructions are not described in detail since they would obscure the invention in unnecessary detail. It is to be noted that the accompanying drawings are only for the purpose of facilitating understanding of the present invention, and should not be construed as limiting the scope of the present invention with reference to the accompanying drawings. The spirit of the present invention should be construed as extending to all modifications, equivalents, and alternatives in addition to the appended drawings.

Hereinafter, an embodiment of the present invention will be described with reference to the accompanying drawings.

1 is a diagram illustrating a targeting service system according to an embodiment of the present invention.

1, a targeting service system according to an exemplary embodiment of the present invention includes a terminal 10 receiving a targeting service, a user analysis device 20 analyzing a user's interest category, And a service providing apparatus 30 for providing a targeting service to the service providing apparatus.

Here, the targeting service provided from the service providing apparatus 30 refers to a service for providing various customized contents to the terminal 10, which may correspond to advertisements, product information, news, publications, academic information, and the like .

In this regard, it is assumed that the targeting service according to an embodiment of the present invention is a targeting advertisement service that provides advertisements as user-customized contents for convenience of description.

The terminal 10 refers to a user's mobile device capable of performing a series of operations such as receiving an advertisement through an advertisement medium and accessing a service page through selection of an advertisement.

For example, the terminal 10 may be a smart phone, a portable terminal, a mobile terminal, a personal digital assistant (PDA), a portable multimedia player (PMP) A telematics terminal, a navigation terminal, a personal computer, a notebook computer, a slate PC, a tablet PC, an ultrabook, a wearable device, (Including a Smartwatch, a Smart Glass, and a HMD (Head Mounted Display)), a Wibro terminal, an IPTV (Internet Protocol Television) terminal, a smart TV, a digital broadcasting terminal, a television A 3D television, a home theater system, an AVN (Audio Video Navigation) terminal, an A / V (Audio / Video) system, a flexible terminal, and the like. Any device capable of receiving advertisements via any advertising medium may be included.

Here, the advertisement medium that enables the reception of the advertisement of the terminal 10 includes, for example, an application executed in the terminal 10 itself or a service page (e.g., a web page) accessible by calling the browser from the terminal 10 .

Such an advertisement medium includes an SDK (Software Development Kit) related to the advertisement reception in the course of its development. As a result, the terminal 10 can receive a series of advertisements through the SDK included in the advertisement medium, Operation can be performed.

For reference, the advertisement medium may support collection of per-user behavior logs cumulatively managed in the user analysis apparatus 20 as well as the above-described series of functions leading to advertisement request, reception and display.

Here, the behavior log includes, for example, a CPS (Campaign Sequence) ID, an ADT (AD Type), a BLT (Bill Type), a TGS (Target Sequence), an MDS (Media Sequence), a CCB (Eg, heathy, music, sport), user id, conversion rate, ad request and reception, and display and selection, service page (eg, web page, advertiser page) And may include all information that can be transmitted through the terminal 10, such as user behavior information (e.g., purchase, browse, inquiry, search).

Accordingly, in the terminal 10, for example, when an advertisement is received and displayed in an application or a service page and an advertisement selection is made, or when an advertiser page is accessed when an advertisement is selected, or the like, And transfers all relevant information to the user analysis device 20 as an action log.

In addition, the terminal 10 according to the embodiment of the present invention can receive advertisement through a pull method of requesting and receiving an advertisement to the service providing device 30 using its device identification information, It is needless to say that the advertisement can be received through a push method in which an advertisement provided by the service providing device 30 is received without a separate advertisement request for the service providing device 30. [

The user analysis device 20 refers to a data management platform for analyzing an interest category corresponding to a user's interest. The user analysis device 20 includes a user's behavior log collected (received) from the terminal 10 and accumulated Analysis can be used to analyze and specify interest categories for users.

The service providing device 30 refers to an advertisement platform for providing advertisements as part of a targeting service for the terminal 10. The service providing device 30 selects an advertisement based on the analysis result of the interest category in the user analysis device 20 .

As described above, each of the user analysis apparatus 20 and the service providing apparatus 30 adopted as a system configuration in the embodiment of the present invention can be implemented in the form of a web server, a database server, a proxy server, Load balancing mechanism, and various software that allows the service device to operate on the Internet or other network, and may be implemented as a computerized system. The network may also be an http network and may be a private line, an intranet, or any other network, and the connection between each of the configurations in the targeting service system according to an embodiment of the present invention may be any data And may be connected to a secure network so as not to be attacked by a hacker or other third party.

Further, each of the user analysis apparatus 20 and the service providing apparatus 30 may include a plurality of database servers, and these database servers may be connected to a user analysis apparatus (not shown) via any type of network connection including a distributed database server architecture 20 and the service providing apparatus 30, respectively.

Meanwhile, the targeting service system according to an embodiment of the present invention follows an advertisement targeting technique for selectively providing advertisements suitable for a user.

In such an advertisement targeting technique, for example, a method of selecting and providing an advertisement suitable for a user based on fixed information such as an application installed or an information (e.g., age, sex, residence, interest) It is common.

However, the method of using fixed information for advertisement selection has a limitation in positively reflecting the user tendency (interest) that can be changed over time, and in the end, the result of not only the effect of the targeting service but also the user satisfaction .

Accordingly, in an embodiment of the present invention, a method for designating an interest category for a user based on a cumulative state variation period derived by analyzing an accumulated state of a user behavior log, and a method for providing an advertisement based on a specified interest category Hereinafter, each configuration in the targeting service system for realizing this will be described in more detail.

FIG. 2 shows a configuration of a terminal 10 according to an embodiment of the present invention.

2, the terminal 10 according to an embodiment of the present invention may have a configuration including an app advertiser 11 and a web advertiser 12.

The application advertisement unit 11 refers to a configuration for performing a series of operations related to an advertisement when an application is executed in the terminal 10, which can be understood as an SDK (Software Development Kit) embedded in an application.

The web advertisement unit 12 is another advertisement medium existing in the terminal 10 and is configured to perform a series of operations related to an advertisement when a service page (for example, a web page) is accessed. Browser. ≪ / RTI >

Here, when accessing a service page (web page), the browser can perform a series of operations related to the advertisement through a method of reading the source code of the SDK inserted in the service page.

As described above, in the case of a browser serving as the web advertisement unit 12, an OS-based browser provided by an operating system (OS) of the terminal 10, or an application itself provided by an application executed in the terminal 10 Based browser.

Here, an application capable of providing a browser by itself can be generally called a hybrid application (e.g., a mobile exclusive shopping mall application).

All or at least a part of the configuration of the terminal 10 including the above-mentioned application advertisement unit 11 and the web advertisement unit 12 may be implemented in the form of a software module or a hardware module executed by the processor, A combination of a module and a hardware module may be implemented.

The terminal 10 according to an embodiment of the present invention includes a display unit 13 for displaying advertisements, an input / output unit 14 for supporting input / output functions such as display and selection of advertisements, And a communication unit 15 for supporting communication with the user analysis apparatus 20 and the service providing apparatus 30, respectively.

The configurations of the display unit 13, the input / output unit 14 and the communication unit 15 are the same as those of the display unit 1321, the input / output unit 1320, and the communication unit 1310 And the detailed description thereof will be omitted.

The terminal 10 according to the embodiment of the present invention receives and displays the advertisement from the service providing device 30 through the core configuration including the application advertisement part 11 and the web advertisement part 12, The user can access the separate advertiser page provided by the advertiser device (not shown), and the action log for each user according to the series of processes can be transmitted to the user analysis device 20. Hereinafter, Will be described in detail with reference to FIG.

The application advertisement unit 11 performs a function of receiving an advertisement.

More specifically, the application advertisement unit 11 requests an advertisement to the service providing apparatus 30 according to the execution of the application. When an advertisement is received from the service providing apparatus 30 according to the advertisement request, The received advertisement is displayed in the designated advertisement display area.

At this time, the application advertisement unit 11 can request the service providing apparatus 30 to advertise using the device identification information (e.g., MDN, IMEI) of the terminal 10 according to the execution of the application.

In addition, the app advertising unit 11 performs a function of requesting a connection to an advertiser device (not shown).

More specifically, after the advertisement advertisement unit 11 displays the advertisement received from the service providing device 30 in the designated advertisement display area in the application execution screen, if the click of the advertisement is confirmed, A connection to the advertiser apparatus (not shown) is requested to the web advertisement unit 12 corresponding to the browser in the terminal 10 according to an embodiment.

In this case, the selected advertisement may include address information of an advertiser device (not shown). If the click of the advertisement is confirmed, the app advertiser 11 transmits the address information included in the advertisement to the web advertisement unit 12 to request access to an advertiser device (not shown).

In addition, after the advertisement advertisement unit 11 displays the advertisement received from the service providing device 30 in the advertisement display area in the application execution screen, the connection to the advertiser device (not shown) is performed through the click of the advertisement The user may transmit the action log to the user analysis device 20. [

Meanwhile, the application advertisement unit 11 can transmit an action log related to the application, as well as an action log related to the advertisement, to the user analysis device 20.

Here, the behavior log delivery method may be, for example, a real time delivery method or a batch transmission method of collectively transmitting accumulated action logs for a predetermined time.

The web advertisement unit 12 performs a function of accessing a service page.

More specifically, when a click on the in-application advertisement is confirmed through the application advertisement unit 11, the web advertisement unit 12 transmits the advertisement information to the advertiser device (Not shown), thereby making it possible to use various services (for example, purchase of goods) provided by the advertiser apparatus (not shown).

On the other hand, the web advertisement unit 12 is an advertisement medium different from the application advertisement unit 11, and is a configuration capable of performing a series of operations related to an advertisement according to a service page (for example, a web page) connection.

The web advertisement unit 12 may request an advertisement to the service providing apparatus 30 in accordance with a connection to a service page (for example, a web page) separately from the application advertisement unit 11. In response to the advertisement request, The advertisement can be displayed in the advertisement display area on the service page.

In addition, as in the case of the application advertisement unit 11, the web advertisement unit 12 displays an advertisement received from the service providing apparatus 30 in the advertisement display area in the service page, and if a click of the advertisement is confirmed , Various services (e.g., merchandise sales) provided by the advertiser device (not shown) can also be used by accessing the advertiser device (not shown) using the address information embedded in the advertisement.

The web advertisement unit 12 displays the advertisement received from the service providing apparatus 300 in the advertisement display area of the service page as in the case of the application advertisement unit 11, (Not shown) is connected to the user analysis device 20, it is of course possible to transmit the behavior log to the user analysis device 20. [

The web advertisement unit 12 can transmit an action log related to the advertisement as well as an action log of the entire user in the web environment to the user analysis apparatus 20 as in the web advertisement unit 11. [

In each of the configurations of the terminal 10 described above, it is noted that the present invention can be implemented in the form of a software module or a hardware module executed by a processor, or a combination of a software module and a hardware module.

As such, a form of software module, hardware module, or combination of software module and hardware module executed by a processor may be implemented in a real hardware system (e.g., a computer system).

Therefore, a hardware system 1000 for implementing the terminal 10 according to an embodiment of the present invention will be described with reference to FIG.

For reference, it should be noted that the following description is an example for implementing each configuration in the terminal 10 described above in the hardware system 1000, and that each configuration and operation thereof may be different from an actual system something to do.

3, a hardware system 1000 according to an embodiment of the present invention includes a processor unit 1100, a memory interface unit 1200, and a peripheral device interface unit 1300 .

Each such configuration in the hardware system 1000 may be a separate component or integrated into one or more integrated circuits, and each of these components may be coupled by a bus system (not shown).

Here, in the case of a bus system, any one or more individual physical buses, communication lines / interfaces, and / or multi-drop or point-to-point links connected by appropriate bridges, adapters, and / And abstraction that represents point-to-point connections.

The processor unit 1100 executes various software modules stored in the memory unit 1210 by communicating with the memory unit 1210 through the memory interface unit 1200 to perform various functions in the hardware system .

2 may be stored in the memory unit 1210 in the form of a software module. In addition, the memory 1210 may store the application advertisement unit 11 and the web advertisement unit 12, which are components of the terminal 10, (OS) may be additionally stored.

In the case of an operating system (for example, an embedded operating system such as I-OS, Android, Darwin, RTXC, LINUX, UNIX, OS X, WINDOWS, or VxWorks), typical system tasks (such as memory management, , Power management, and the like), a set of instructions, a software component, and / or a driver, and facilitates communication between various hardware modules and software modules.

For reference, the memory unit 1210 may include a memory hierarchy including, but not limited to, a cache, a main memory, and a secondary memory, such as RAM (e.g., SRAM, (E.g., DRAM, DDRAM), ROM, FLASH, magnetic and / or optical storage devices such as disk drives, magnetic tape, compact discs, and digital video discs.

The peripheral device interface unit 1300 serves to enable communication between the processor unit 1100 and a peripheral device.

Here, in the case of a peripheral device, the hardware system 1000 is provided for providing different functions. In an embodiment of the present invention, for example, a communication unit 1310 and an input / output unit 1320 may be included.

Here, the communication unit 1310 performs a function of providing a communication function with another device. For example, an antenna system, an RF transceiver, one or more amplifiers, a tuner, one or more oscillators, a digital signal processor, CODEC) chipset, and memory, and the like, and may include known circuits that perform this function.

Examples of the communication protocol supported by the communication unit 1310 include a wireless LAN (WLAN), a DLNA (Digital Living Network Alliance), a Wireless Broadband (Wibro), a World Interoperability for Microwave Access ), Code Division Multiple Access (CDMA), Code Division Multi Access (CDMA2000), Enhanced Voice-Data Optimized or Enhanced Voice-Only (EV-DO), Wideband CDMA (WCDMA) , HSDPA (High Speed Downlink Packet Access), HSUPA (High Speed Uplink Packet Access), IEEE 802.16, Long Term Evolution (LTE), Long Term Evolution-Advanced (LTE-A) Wireless Mobile Broadband Service (WMBS), Bluetooth, Radio Frequency Identification (RFID), Infrared Data Association (IrDA), Ultra-Wideband (UWB), ZigBee, Near Field Communication NFC, Ultra Sound Communication (USC), visible light Shin: could include (Visible Light Communication VLC), Wi Fi (Wi-Fi), Wi Fi Direct (Wi-Fi Direct). The wired communication network may be a wired LAN, a wired WAN, a power line communication (PLC), a USB communication, an Ethernet, a serial communication, Cables, and the like, and may include any protocol that can provide a communication environment with other devices, which is not limited at present.

In addition, the input / output unit 1320 serves as a controller for controlling an I / O device interlocked with other hardware systems. In an embodiment of the present invention, an application execution screen display, an advertisement selection (click) And can control the display unit 1321 that supports display of the page connection screen and the like.

Here, it goes without saying that the display unit 1321 supports a touch interface for confirming an advertisement selection (click).

The display unit 1321 may be a liquid crystal display (LCD), a thin film transistor LCD (TFT-LCD), a light emitting diode (LED), an organic light emitting diode OLED, Organic LED, AMOLED, Active Matrix OLED, Retina Display, Flexible Display, and 3 Dimension Display.

As a result, each configuration in the terminal 10, which is stored in the memory unit 1210 in the form of a software module according to the above configuration, is stored in the memory interface unit 1200 and the peripheral device 1010 in the form of a command executed by the processor unit 1100. [ The communication unit 1310 and the input / output unit 1320 communicate with each other via the interface unit 1300 to process advertisements received from the service providing apparatus 30 and connection to the advertiser page, It is possible to transmit the overall behavior log to the user analysis device 20. [

The configuration of the user analysis apparatus 20 will be described below with reference to the terminal 10 according to an embodiment of the present invention.

Prior to a specific description of the user analysis device 20, it is assumed that the user analysis device 20 has accumulated a behavior log collected during a specific period (for example, one month) for a user who has the terminal 10 .

FIG. 4 shows a schematic configuration of a user analysis apparatus 20 according to an embodiment of the present invention.

4, the user analysis apparatus 20 according to the embodiment of the present invention includes a checking unit 21 for checking an accumulated state of an action log, a selecting unit 22 for selecting an action log, A classification unit 24 for classifying similar user groups, and a providing unit 25 for providing service selection information (advertisement selection information).

All or at least a part of the configuration of the user analysis apparatus 20 including the verification unit 21, the selection unit 22, the specification unit 23, the classification unit 24, May be implemented in the form of a software module to be executed or a hardware module, or a combination of a software module and a hardware module.

Here, the software module can be understood as an instruction executed, for example, by a processor that controls an operation in the user analysis apparatus 20, and the instruction can have a form embedded in a memory in the user analysis apparatus 20 There will be.

The user analysis apparatus 20 according to an embodiment of the present invention may further include a communication unit 26 for supporting communication between the terminal 10 and the service providing apparatus 30 in addition to the above- Lt; / RTI >

For reference, the configuration of the communication unit 26 corresponds to the configuration of the communication unit 2310 to be described with reference to FIG. 8, and a detailed description thereof will be omitted.

The user analysis apparatus 20 according to an embodiment of the present invention includes an identifying unit 21, a selecting unit 22, a determining unit 23, a classifying unit 24, and a providing unit 25 The interest category for the user can be designated through the core configuration. Hereinafter, each of the core components in the user analysis device 20 will be described in detail.

The confirmation unit 21 performs a function of confirming an accumulated state of a plurality of behavior logs.

More specifically, when the user designates an interest category for the user of the terminal 10, the confirmation unit 21 determines whether or not the user of the terminal 10 has a plurality of behaviors that are collected and accumulated for a specific period (for example, 30 days) You will see the cumulative status of the logs.

At this time, a plurality of behavior logs are categorized into a plurality of predefined categories (eg, age, sex, residence area, purchase goods), and furthermore, It is classified into three.

For example, if a particular category is 'age', the subcategories are '1 to 10 years old', '11 to 20 years old, '21 to 30 years old', '31 to 40 years old', .. .., and '91 to 100 years old', and when a specific category is 'sex', it can be classified into two subcategories 'M' and 'F'.

If a particular category is a 'vehicle' associated with a 'purchase item', the sub-category may be classified as 'car', 'motorcycle', 'bicycle', and the like.

In this regard, in the case of the cumulative status of such a plurality of behavior logs, the accumulated number of the behavior logs for each sub-category for a specific period (for example, 30 days) . ≪ / RTI >

For example, if the total sum of the number of subcategories classified by category is 1000, the cumulative state for a plurality of action logs is a graph form having 1000 sampling rates as shown in FIG. 5 Can be expressed as.

The selection unit 22 performs a function of selecting a category indicating the attribute (interest) of the user.

More specifically, when the cumulative state of a plurality of action logs is confirmed, the selecting unit 22 selects an action log that can display the attributes of the user during a specific period (for example, 30 days) based on the checked cumulative state do.

At this time, the selector 22 processes an autocorrelation operation on the ascertained cumulative state, and uses the magnitude of the autocorrelation value for each sub-category derived from the operation result as a result of the operation to determine a specific period (for example, : 30 days) to select a category that can represent the attribute of interest (interest).

For example, FIG. 6 shows an example of an operation processing result (b) in which an autocorrelation operation is performed on the cumulative state (a) of a plurality of behavior logs.

Here, in the case of behavior logs such as 'age' and 'sex' among the plurality of behavior logs, there is no possibility of fluctuation during a specific period (for example, 30 days). Therefore, the cumulative number of the behavior logs is the largest, It can be expected that the autocorrelation value derived as the maximum value can also have the largest value.

However, even though the largest autocorrelation value is derived for an activity log that is not likely to fluctuate over a certain period of time (eg, 30 days), the effect on user attribute (interest) decisions over a specific period of time Will be lacking.

For reference, in FIG. 6, which is illustrated in FIG. 6, it is an action log corresponding to a 'motorcycle' that substantially affects the user's tendency (interest) for a specific period (for example, 30 days).

Accordingly, the selector 22 selects an autocorrelation operation for the identified cumulative state in the order of predefined subcategories among the non-changeable behavior logs for a specific period (for example, 30 days) By defining the emerging behavior log (eg, gender) as the baseline behavior log and applying the maximum number of accuracies (eg, 30 times, reference value) over a specific period (eg 30 days) The category to which the reference action log belongs can be excluded in the process of selecting an action log based on the maximum autocorrelation value corresponding to the cumulative count.

In addition, the selecting unit 22 deletes the cumulative counts for the remaining behavior logs (for example, the age) excluding the reference behavior log among the behavior logs that are unlikely to change during a specific period (for example, 30 days) In the selection process, the category to which the action log belongs can also be excluded.

In addition, when the exclusion process for the behavior log having no possibility of fluctuation for a specific period (for example, 30 days) is completed, the selector 22 processes an autocorrelation operation on the cumulative state of the remaining behavior logs, The category to which the action log having the largest autocorrelation value belongs is selected.

For example, FIG. 7 shows an example of the processing result (b) obtained by performing an autocorrelation operation on the cumulative state (a) of the remaining behavior logs.

Here, it is a behavior log corresponding to a 'motorcycle' which has a substantial effect on a user's propensity (interest) for a specific period (for example, 30 days) Value) is located in the 21 sampling sequence from the set reference action log, which can be understood as having an autocorrelation period of 21 sampling cycles as a result of autocorrelation operation.

In this way, according to the result of the autocorrelation operation process, the category of the 'motorcycle' to which the 'motorcycle' belongs can be selected.

On the other hand, in order to verify the validity of the action log having the largest autocorrelation value before selecting the category to which the action log having the largest autocorrelation value belongs, the selector 22 selects an action log having the largest autocorrelation value It is determined whether or not the activity log has a set rate relationship with the behavior log, and a category to which the behavior log having the largest autocorrelation value belongs is selected only when the set ratio relationship with the other behavior log has a relationship.

Here, the set ratio relation means a ratio relation between autocorrelation values. For example, the second behavior (the second largest) in which the autocorrelation value is largest among the remaining behavior logs excluding the first behavior log having the largest autocorrelation value Log and a third (largest) third behavior log in the order of rank, the difference between the autocorrelation value of the first behavior log and the autocorrelation value of the second behavior log is greater than a first threshold ratio (e.g., 30 %), And the autocorrelation value of the first behavior log and the autocorrelation value of the third behavior log are equal to or greater than a second threshold ratio (e.g., 60%) larger than the first threshold ratio.

For reference, the calculation formulas of the first threshold ratio and the second threshold ratio are respectively as shown in [Expression 1] and [Expression 2].

[Equation 1]

The first threshold ratio = {first behavior log (autocorrelation value) - second behavior log (autocorrelation value)} / first behavior log (autocorrelation value)

[Equation 2]

The second threshold ratio = {first behavior log (autocorrelation value) - third behavior log (autocorrelation value)} / first behavior log (autocorrelation value)

As a result, the selector 22 compares the autocorrelation values of the plurality of behavior logs with each other. As a result, the selection unit 22 generates a specific behavior log having the largest autocorrelation value among the plurality of behavior logs, Can be selected.

The designation unit 23 performs a function of designating an interest category.

More specifically, when the category is selected on the basis of the cumulative state for a plurality of behavior logs, the specifying unit 23 designates the selected category as an interest category for the terminal 10 user.

The classification unit 24 performs a function of classifying similar user groups.

More specifically, the classifying unit 24 classifies the users whose interest categories match as similar user groups when there are users whose interest categories match, as a result of assigning interest categories to a plurality of users including the user of the terminal 10 .

The providing unit 25 performs a function of providing service selection information (advertisement selection information).

More specifically, the providing unit 25 provides the service providing apparatus 30 with the interest category designated for the user of the terminal 10 as the service selection information (advertisement selection information), and if the similar user If the group is classified, information on the similar user group together with the interest category designated to the user of the terminal 10 is provided to the service providing apparatus 30 as service selection information (advertisement selection information).

In this case, when the service selection information (advertisement selection information) for the user of the terminal 10 is received from the user analysis device 20, the service providing device 30 uses the received service selection information (advertisement selection information) And provide the selected advertisement to the terminal 10 as a targeted advertisement.

Meanwhile, in each of the configurations of the user analysis apparatus 20 described above, it is noted that the present invention can be implemented in the form of a software module or a hardware module executed by a processor, or a combination of a software module and a hardware module have.

As such, a form of software module, hardware module, or combination of software module and hardware module executed by a processor may be implemented in a real hardware system (e.g., a computer system).

Therefore, a hardware system 2000 that implements each configuration in the user analysis apparatus 20 according to an embodiment of the present invention will be described with reference to FIG.

On the other hand, among the configurations of the hardware system 2000 shown in Fig. 8, configurations whose names coincide with those in the hardware system 1000 described with reference to Fig. 3 can be regarded as having the same configuration, A specific example or description of the same configuration will be omitted.

8, a hardware system 2000 for implementing a user analysis apparatus 20 according to an embodiment of the present invention includes a processor unit 2100, a memory interface unit 2200, (2300). ≪ / RTI >

The processor unit 2100 communicates with the memory unit 2210 through the memory interface unit 2200 to execute various software modules stored in the memory unit 2210 to perform various functions in the hardware system .

Here, the memory unit 2210 is provided with an identifying unit 21, a selecting unit 22, a specifying unit 23, a classifying unit 24, and a providing unit 25 in the user analyzing apparatus 20 described with reference to FIG. ) May be stored in the form of a software module, and other operating systems may be additionally stored.

The peripheral device interface unit 2300 serves to enable communication between the processor unit 2100 and the peripheral device.

Here, in the case of a peripheral device, the hardware system 2000 is provided for providing different functions. In an embodiment of the present invention, for example, a communication unit 2310 may be included.

Here, the communication unit 2310 performs a function of providing a communication function with other devices. For example, an antenna system, an RF transceiver, one or more amplifiers, a tuner, one or more oscillators, a digital signal processor, a codec CODEC) chipset, and memory, and the like, and may include known circuits that perform this function.

As a result, each configuration in the user analysis apparatus 20 stored in the memory unit 2210 in the form of a software module is stored in the memory interface unit 2100 and the peripheral device interface unit 2100 in the form of instructions executed by the processor unit 2100. [ The interface with the communication unit 2310 is processed through the communication unit 2300, thereby allowing the user to specify a category of interest for the user.

Hereinafter, each configuration of the user analysis apparatus 20 will be described in connection with the hardware system 2000 with reference to FIG.

The confirmation unit 21 performs a function of confirming an accumulated state of a plurality of behavior logs.

More specifically, when a request for category of interest for a user of the terminal 10 is requested from the service providing apparatus 30 through the communication unit 2310, the confirmation unit 21 sends a request to the user of the terminal 10 for a specific period (for example, 30 days), and transmits the result of the check to the selection unit 22. The selection unit 22 determines the cumulative state of a plurality of action logs that are collected and accumulated.

At this time, a plurality of behavior logs are categorized into a plurality of predefined categories (eg, age, sex, residence area, purchase goods), and furthermore, It is classified into three.

In this regard, in the case of the cumulative status of such a plurality of behavior logs, the accumulated number of the behavior logs for each sub-category for a specific period (for example, 30 days) . ≪ / RTI >

The selection unit 22 performs a function of selecting a category indicating the attribute (interest) of the user.

More specifically, when the cumulative state of a plurality of behavior logs is received, the selecting unit 22 selects an action log capable of representing the attributes of the user for a specific period (for example, 30 days) based on the confirmed cumulative state , And transmits the selection result to the designation unit 23.

At this time, the selector 22 processes an autocorrelation operation on the ascertained cumulative state, and uses the magnitude of the autocorrelation value for each sub-category derived from the operation result as a result of the operation to determine a specific period (for example, : 30 days) to select a category that can represent the attribute of interest (interest).

However, the selecting unit 22 may perform an autocorrelation operation on the ascertained cumulative state before the processing of the first predetermined time period (for example, 30 days) By defining the emerging behavior log (eg, gender) as the baseline behavior log and applying the maximum number of accuracies (eg, 30 times, reference value) over a specific period (eg 30 days) The category to which the reference action log belongs can be excluded in the process of selecting an action log based on the maximum autocorrelation value corresponding to the cumulative count.

In addition, the selecting unit 22 deletes the cumulative counts for the remaining behavior logs (for example, the age) excluding the reference behavior log among the behavior logs that are unlikely to change during a specific period (for example, 30 days) In the selection process, the category to which the action log belongs can also be excluded.

In addition, when the exclusion process for the behavior log having no possibility of fluctuation for a specific period (for example, 30 days) is completed, the selector 22 processes an autocorrelation operation on the cumulative state of the remaining behavior logs, It is possible to select a specific action log having the largest autocorrelation value as a result of arithmetic processing and having a set ratio relationship with the autocorrelation value of another behavior log.

The designation unit 23 performs a function of designating an interest category.

More specifically, when the category selection result based on the cumulative status for a plurality of behavior logs is received, the specifying unit 23 designates the selected category as an interest category for the user of the terminal 10, And supplies it to the feeder 25.

The classification unit 24 performs a function of classifying similar user groups.

More specifically, the classifying unit 24 classifies the users whose interest categories match as similar user groups when there are users whose interest categories match, as a result of assigning interest categories to a plurality of users including the user of the terminal 10 And delivers the classification result to the providing unit 25.

The providing unit 25 performs a function of providing service selection information (advertisement selection information).

More specifically, the providing unit 25 provides the service providing apparatus 30 with the interest category designated for the user of the terminal 10 as the service selection information (advertisement selection information) through the communication unit 2310, If the similar user group to which the user belongs is classified, the information on the similar user group together with the interest category designated to the user of the terminal 10 is transmitted as service selection information (advertisement selection information) through the communication unit 2310, (30).

The configuration of the service providing apparatus 30 will be described below with reference to the configuration of the user analysis apparatus 20 according to the embodiment of the present invention.

FIG. 9 shows a schematic configuration of a service providing apparatus 30 according to an embodiment of the present invention

9, the service providing apparatus 30 according to an embodiment of the present invention includes a confirmation unit 31 for confirming service selection information (advertisement selection information) for a user of the terminal 10, A selecting unit 32 for selecting a desired content, and a providing unit 33 for providing an advertisement.

All or at least a part of the configuration of the service providing apparatus 30 including the above-described confirmation unit 31, the selection unit 32 and the service provider 33 may be implemented in the form of a software module executed by a processor or a hardware module Or software modules and hardware modules may be implemented in a combined form.

The service providing apparatus 30 according to an embodiment of the present invention may further include a communication unit 34 for supporting communication between the terminal 10 and the user analysis apparatus 20 in addition to the above- .

For reference, the configuration of the communication unit 34 corresponds to the configuration of the communication unit 3310 to be described below with reference to FIG. 10, and a detailed description thereof will be given below.

The service providing apparatus 30 according to an embodiment of the present invention may be configured to receive an advertisement suitable for the user of the terminal 10 through the core configuration including the identifying unit 31, the selecting unit 32, . Hereinafter, each configuration in the service providing apparatus 30 for implementing this will be described in detail.

The confirmation unit 31 performs a function of confirming information about the user group.

More specifically, when an advertisement request is received from the terminal 10, the confirmation unit 31 transmits service selection information (advertisement selection information) for the user of the terminal 10 for the purpose of selecting an advertisement suitable for the user of the terminal 10 ) To the user analysis device 20 and confirms it through a method of receiving it.

In this regard, the user analysis apparatus 20 analyzes the cumulative state of the action log for the terminal 10 users accumulated over a specific period (3 months) , And provides the information as service selection information (advertisement selection information) for the terminal 10 user.

Meanwhile, in the embodiment of the present invention, the user analysis apparatus 20 provides the service selection information (advertisement selection information) at the request of the service providing apparatus 30. However, It goes without saying that the user analysis apparatus 20 may periodically provide service selection information (user selection information) for each user to the service providing apparatus 30 without any request from the apparatus 30.

The selection unit 32 performs a function of selecting an advertisement.

More specifically, when the service selection information (advertisement selection information) is received from the user analysis device 20, the selection unit 32 selects the advertisement using the received service selection information (advertisement selection information).

At this time, the selecting unit 32 may select the advertisement specified in the interest category in the service selection information (advertisement selection information), or may select the advertisement provided to other users in the similar user group.

However, in order to select the advertisement provided to other users in the similar user group, it is needless to say that the advertisement providing history for each user must be managed.

The providing unit 33 performs a function of providing an advertisement.

More specifically, the provider 33 provides the selected advertisement to the terminal 10 as a targeting advertisement when the advertisement selection based on the service selection information (advertisement selection information) is completed.

In the meantime, each configuration in the above-described service providing apparatus 30 may be implemented by a software module, a hardware module, or a combination of a software module and a hardware module executed by a processor, in a real hardware system (e.g., a computer system) .

Therefore, a hardware system 3000 implementing each configuration in the service providing apparatus 30 according to an embodiment of the present invention will be described with reference to FIG.

On the other hand, among the configurations of the hardware system 3000 shown in FIG. 10, configurations whose names coincide with those in the hardware system 1000 described with reference to FIG. 3 may be regarded as having the same configuration, A specific example or description of the same configuration will be omitted.

10, a hardware system 3000 for implementing a service providing apparatus 30 according to an embodiment of the present invention includes a processor unit 3100, a memory interface unit 3200, (3300). ≪ / RTI >

The processor unit 3100 communicates with the memory unit 3210 through the memory interface unit 3200 to execute various software modules stored in the memory unit 3210 to perform various functions in the hardware system .

Here, the identification unit 31, the selection unit 32, and the provider 33, which are the components of the service providing apparatus 30 described with reference to FIG. 9, can be stored in the memory unit 3210 in the form of a software module And other operating systems can be additionally stored.

The peripheral device interface unit 3300 serves to enable communication between the processor unit 3100 and the peripheral device.

Here, in the case of a peripheral device, the hardware system 3000 is provided for providing different functions. In an embodiment of the present invention, for example, a communication unit 3310 may be included.

Here, the communication unit 3310 performs a function of providing a communication function with other devices. For example, an antenna system, an RF transceiver, one or more amplifiers, a tuner, one or more oscillators, a digital signal processor, a codec CODEC) chipset, and memory, and the like, and may include known circuits that perform this function.

As a result, each configuration in the service providing apparatus 30 stored in the memory unit 3210 in the form of a software module is stored in the memory interface unit 3100 and the peripheral device interface unit 3100 in the form of a command executed by the processor unit 3100. [ The user can provide the advertisement to the user of the terminal 10 by processing the interface with the communication unit 3310 via the Internet 3300.

Hereinafter, each configuration of the service providing apparatus 30 will be described in connection with the hardware system 3000, with reference to Fig. 10 described above.

The confirmation unit 31 performs a function of confirming information about the user group.

More specifically, when the advertisement request is received from the terminal 10 through the communication unit 3310, the confirmation unit 31 transmits a service for the user of the terminal 10 to the terminal 10 for the purpose of selecting an advertisement suitable for the user of the terminal 10 (Advertisement selection information) to the user analysis apparatus 20 through the communication unit 3310, and transmits the confirmation result to the selection unit 32. [

In this regard, the user analysis apparatus 20 analyzes the cumulative state of the action log for the terminal 10 users accumulated over a specific period (3 months) , And provides the information as service selection information (advertisement selection information) for the terminal 10 user.

The selection unit 32 performs a function of selecting an advertisement.

More specifically, when the confirmation result of the service selection information (advertisement selection information) is received, the selection unit 32 selects the advertisement using the received service selection information (advertisement selection information) (33).

At this time, the selecting unit 32 may select the advertisement specified in the interest category in the service selection information (advertisement selection information), or may select the advertisement provided to other users in the similar user group.

The providing unit 33 performs a function of providing an advertisement.

More specifically, when the advertisement selected based on the service selection information (advertisement selection information) is received, the providing unit 33 transmits the received advertisement to the terminal 10 through the communication unit 3310 as a targeting advertisement for the terminal 10, .

As described above, according to each configuration in the targeting service system according to an embodiment of the present invention, a plurality of action logs collected in relation to a user during a specific period and classified into a plurality of categories, The target category for the user can be specified based on the fluctuation cycle of the cumulative state derived as the analysis result and utilized in the targeting service, thereby enhancing the effect of the targeting service and the user satisfaction.

Hereinafter, the operation of the targeting service system according to the embodiment of the present invention and the operation flow in each configuration in the system will be described.

FIG. 11 shows an operation flow in a targeting service system according to an embodiment of the present invention.

First, when receiving an advertisement request from the terminal 10 in accordance with step S11, the service providing apparatus 30 searches for a suitable advertisement for the user of the terminal 10, according to step S12, And requests the user analysis apparatus 20 for the service selection information (advertisement selection information).

On the other hand, when the service selection information (advertisement selection information) for the user of the terminal 10 is requested, the user analysis apparatus 20 determines whether or not the user of the terminal 10 is in a predetermined period (for example, 30 days) The cumulative state of a number of collected and accumulated behavior logs is confirmed.

At this time, a plurality of behavior logs are categorized into a plurality of predefined categories (eg, age, sex, residence area, purchase goods), and furthermore, It is classified into three.

In this regard, in the case of the cumulative status of such a plurality of behavior logs, the accumulated number of the behavior logs for each sub-category for a specific period (for example, 30 days) . ≪ / RTI >

Then, when the cumulative state of a plurality of behavior logs is confirmed, the user analysis apparatus 20 can display the property of the user for a specific period (for example, 30 days) based on the cumulative state determined according to steps S14 to S16 Select an action log.

At this time, the user analysis apparatus 20 processes an autocorrelation operation on the ascertained cumulative state, and uses the magnitude of the autocorrelation value for each sub-category behavior log derived as a result of the computation process, For example, you can select a category that can represent the attribute of interest (interest) for 30 days.

However, the user analysis apparatus 20 may perform an autocorrelation operation on the ascertained cumulative state in the order of predefined subcategories among the unobservable behavior logs for a specific period (for example, 30 days) By defining the first occurring behavior log (eg, gender) as the baseline behavior log and applying the maximum cumulative number of times (eg 30 times, reference value) over a specific period (eg 30 days) The category to which the reference action log belongs can be excluded in the process of selecting an action log based on the maximum autocorrelation value corresponding to the maximum cumulative count.

In addition, the user analysis device 20 deletes the cumulative number of the behavior logs (e.g., age) excluding the reference behavior log among the behavior logs that are not likely to change during a specific period (for example, 30 days) In the process of selecting a log, the category to which the action log belongs can also be excluded.

After the exclusion process for the behavior log having no possibility of fluctuation for a specific period (for example, 30 days) is completed, the user analysis apparatus 20 processes an autocorrelation operation on the cumulative state of the remaining behavior logs , It is possible to select a specific action log having the largest autocorrelation value as a result of the arithmetic processing and having a set ratio relationship with respect to the autocorrelation value of another behavior log.

Then, when the category is selected on the basis of the cumulative state of the plurality of behavior logs, the user analysis apparatus 20 designates the selected category as an interest category for the terminal 10 user according to step S17.

In addition, if the user category analysis unit 20 determines that the user category analysis unit 20 determines that the user category matches the interest category category, Group.

Subsequently, the user analysis apparatus 20 provides the service providing apparatus 30 with the interest category designated for the user of the terminal 10 as service selection information (advertisement selection information) in accordance with step S19, If the similar user group to which the user belongs is classified, information on the similar user group together with the interest category designated to the user of the terminal 10 is provided to the service providing apparatus 30 as service selection information (advertisement selection information).

On the other hand, when the service selection information (advertisement selection information) is received from the user analysis device 20, the service providing device 30 selects the advertisement using the received service selection information (advertisement selection information) do.

At this time, the selecting unit 32 may select the advertisement specified in the interest category in the service selection information (advertisement selection information), or may select the advertisement provided to other users in the similar user group.

After the advertisement selection based on the service selection information (advertisement selection information) is completed, the provider 33 provides the selected advertisement to the terminal 10 as a targeting advertisement according to step S21.

FIG. 12 shows an operation flow in the user analysis apparatus 20 according to an embodiment of the present invention.

First, the confirmation unit 21 acquires, for a predetermined period of time (for example, 30 days), the user of the terminal 10 in accordance with step S32, Check the cumulative status of a number of behavior logs in a state

At this time, a plurality of behavior logs are categorized into a plurality of predefined categories (eg, age, sex, residence area, purchase goods), and furthermore, It is classified into three.

In this regard, in the case of the cumulative status of such a plurality of behavior logs, the accumulated number of the behavior logs for each sub-category for a specific period (for example, 30 days) . ≪ / RTI >

Then, when the cumulative state of a plurality of behavior logs is confirmed, the selecting unit 22 can display the property of the user for a specific period (for example, 30 days) based on the cumulative state determined according to steps S33 to S38 Select the action log.

At this time, the selector 22 processes an autocorrelation operation on the ascertained cumulative state, and uses the magnitude of the autocorrelation value for each sub-category derived from the operation result as a result of the operation to determine a specific period (for example, : 30 days) to select a category that can represent the attribute of interest (interest).

However, the selecting unit 22 may perform an autocorrelation operation on the ascertained cumulative state before the processing of the first predetermined time period (for example, 30 days) By defining the emerging behavior log (eg, gender) as the baseline behavior log and applying the maximum number of accuracies (eg, 30 times, reference value) over a specific period (eg 30 days) The category to which the reference action log belongs can be excluded in the process of selecting an action log based on the maximum autocorrelation value corresponding to the cumulative count.

In addition, the selection unit 22 deletes the cumulative counts for the remaining behavior logs (e.g., age) excluding the reference behavior log among the behavior logs that are not likely to fluctuate during a specific period (for example, 30 days) In the selection process, the category to which the action log belongs can also be excluded.

In addition, when the exclusion process for the behavior log having no possibility of fluctuation for a specific period (for example, 30 days) is completed, the selector 22 processes an autocorrelation operation on the cumulative state of the remaining behavior logs, The category to which the action log having the largest autocorrelation value belongs is selected only when the autocorrelation value is the largest and the setting ratio relationship with the other action log is the result of the calculation process.

Here, the set ratio relation means a ratio relation between autocorrelation values. For example, the second behavior (the second largest) in which the autocorrelation value is largest among the remaining behavior logs excluding the first behavior log having the largest autocorrelation value Log and a third (largest) third behavior log in the order of rank, the difference between the autocorrelation value of the first behavior log and the autocorrelation value of the second behavior log is greater than a first threshold ratio (e.g., 30 %), And the autocorrelation value of the first behavior log and the autocorrelation value of the third behavior log are equal to or greater than a second threshold ratio (e.g., 60%) larger than the first threshold ratio.

Then, when the category is selected on the basis of the cumulative state of the plurality of behavior logs, the specifying section 23 designates the selected category as an interest category for the terminal 10 user according to step S39.

If there are users whose interest categories match, as a result of assigning interest categories to a plurality of users including the user of the terminal 10, the classifying unit 24 classifies the users whose interest categories match according to step S40, .

The providing unit 25 then provides the service providing apparatus 30 with the interest category designated for the user of the terminal 10 as service selection information (advertisement selection information) in accordance with step S41, If the similar user group is classified, the information on the similar user group together with the interest category designated to the user of the terminal 10 is provided to the service providing apparatus 30 as the service selection information (advertisement selection information).

In this case, when the service selection information (advertisement selection information) for the user of the terminal 10 is received from the user analysis device 20, the service providing device 30 uses the received service selection information (advertisement selection information) And provide the selected advertisement to the terminal 10 as a targeted advertisement.

The operation flow in the user analysis apparatus 20 according to the embodiment of the present invention is described above, and the operation flow in the service providing apparatus 30 will be described.

FIG. 13 shows an operation flow in the service providing apparatus 30 according to an embodiment of the present invention.

First, when an advertisement request is received from the terminal 10 in accordance with step S51, the confirmation unit 31 transmits the advertisement request to the user of the terminal 10 for the purpose of selecting an advertisement suitable for the user of the terminal 10 according to steps S52 and S53 And requests the user analysis device 20 for the service selection information (advertisement selection information).

In this regard, the user analysis apparatus 20 analyzes the cumulative state of the action log for the terminal 10 users accumulated over a specific period (3 months) , And provides the information as service selection information (advertisement selection information) for the terminal 10 user.

Meanwhile, in the embodiment of the present invention, the user analysis apparatus 20 provides the service selection information (advertisement selection information) at the request of the service providing apparatus 30. However, It goes without saying that the user analysis apparatus 20 may periodically provide service selection information (user selection information) for each user to the service providing apparatus 30 without any request from the apparatus 30.

Then, when the service selection information (advertisement selection information) is received from the user analysis device 20, the selection unit 32 selects the advertisement using the received service selection information (advertisement selection information) according to step S54.

At this time, the selecting unit 32 may select the advertisement specified in the interest category in the service selection information (advertisement selection information), or may select the advertisement provided to other users in the similar user group.

However, in order to select the advertisement provided to other users in the similar user group, it is needless to say that the advertisement providing history for each user must be managed.

After the advertisement selection based on the service selection information (advertisement selection information) is completed, the provider 33 provides the selected advertisement to the terminal 10 as a ticketing advertisement according to step S55.

As described above, according to the operation flow in the targeting service system and the system in the system according to the embodiment of the present invention, And the target category for the user is designated based on the cycle of the cumulative state derived as the analysis result and utilized in the targeting service, so that the effect of the targeting service and the user satisfaction can be improved.

It should be understood that the functional operations and subject matter implementations described herein may be implemented as digital electronic circuitry, or may be embodied in computer software, firmware, or hardware, including the structures disclosed herein, and structural equivalents thereof, . Implementations of the subject matter described herein may be implemented as one or more computer program products, i. E. One or more modules relating to computer program instructions encoded on a type of program storage medium for execution by, or control of, the operation of the processing system Can be implemented.

The computer-readable medium can be a machine-readable storage device, a machine-readable storage substrate, a memory device, a composition of matter that affects the machine readable propagation type signal, or a combination of one or more of the foregoing.

The term "system" or "device" as used herein encompasses all apparatuses, apparatus, and machines for processing data, including, for example, a programmable processor unit, a computer or a multiprocessor unit or a computer. The processing system may include, in addition to the hardware, code that forms an execution environment for the computer program upon request, such as, for example, code comprising the processor portion firmware, a protocol stack, a database management system, an operating system, have.

A computer program (also known as a program, software, software application, script or code) may be written in any form of programming language, including compiled or interpreted language, a priori or procedural language, Components, subroutines, or other units suitable for use in a computer environment. A computer program does not necessarily correspond to a file in the file system. The program may be stored in a single file provided to the requested program, or in multiple interactive files (e.g., a file storing one or more modules, subprograms, or portions of code) (E.g., one or more scripts stored in a markup language document). A computer program may be deployed to run on multiple computers or on one computer, located on a single site or distributed across multiple sites and interconnected by a communications network.

On the other hand, computer readable media suitable for storing computer program instructions and data include semiconductor memory devices such as, for example, EPROM, EEPROM and flash memory devices, such as magnetic disks such as internal hard disks or external disks, Non-volatile memory, media and memory devices, including ROM and DVD-ROM disks. The processor portion and the memory may be supplemented by, or integrated into, a special purpose logic circuit.

Implementations of the subject matter described herein may include, for example, a back-end component such as a data server, or may include a middleware component, such as an application server, or may be a web browser or a graphical user, for example a user, who may interact with an implementation of the subject- Front-end components such as client computers with interfaces, or any combination of one or more of such back-end, middleware, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication, such as, for example, a communications network.

While the specification contains a number of specific implementation details, it should be understood that they are not to be construed as limitations on the scope of any invention or claim, but rather on the description of features that may be specific to a particular embodiment of a particular invention Should be understood. Likewise, the specific features described herein in the context of separate embodiments may be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment may also be implemented in multiple embodiments, either individually or in any suitable subcombination. Further, although the features may operate in a particular combination and may be initially described as so claimed, one or more features from the claimed combination may in some cases be excluded from the combination, Or a variant of a subcombination.

It is also to be understood that although the present invention is described herein with particular sequence of operations in the drawings, it is to be understood that it is to be understood that it is to be understood that all such illustrated acts have to be performed or that such acts must be performed in their particular order or sequential order, Can not be done. In certain cases, multitasking and parallel processing may be advantageous. Also, the separation of the various system components of the above-described embodiments should not be understood as requiring such separation in all embodiments, and the described program components and systems will generally be integrated together into a single software product or packaged into multiple software products It should be understood that

As such, the present specification is not intended to limit the invention to the specific terminology presented. Thus, while the present invention has been described in detail with reference to the above examples, those skilled in the art will be able to make adaptations, modifications, and variations on these examples without departing from the scope of the present invention. The scope of the present invention is defined by the appended claims rather than the detailed description and all changes or modifications derived from the meaning and scope of the claims and their equivalents are to be construed as being included within the scope of the present invention do.

According to the user analysis apparatus, the operation method thereof, and the service providing apparatus of the present invention, an accumulated state is analyzed for a plurality of behavior logs collected in association with a user for a specific period and classified and accumulated in a plurality of categories, As the result of the analysis, the interest category for the user is specified based on the fluctuation cycle of the cumulative state. Therefore, as the limit of the existing technology is exceeded, not only the use of the related technology but also the sale or sale of the applied device This is an invention that is industrially applicable because it is not only possible but also practically possible to carry out clearly.

10: Terminal
11: App Advertisement Section 12: Web Advertising Section
20: user analysis device
21: Identification part 22:
23: Designating section 24:
25:
30: Service providing device
31: confirmation unit 32: selection unit
33: Offering

Claims (12)

A processor for processing an operation to specify an interest category for a user; And
Wherein at least one instruction executed via the processor comprises a stored memory,
Wherein the at least one instruction comprises:
A confirmation command for collecting a plurality of behavior logs collected in association with the user for a specific period and classified by a plurality of categories and accumulating; And
Selecting an action log indicating an attribute of the user during the specific period among the plurality of action logs based on the cumulative state of the plurality of action logs, Wherein the selection instruction includes a selection instruction to cause the user to select one of the plurality of users. The method according to claim 1,
The selection instruction includes:
The autocorrelation operation for the cumulative states of the plurality of behavior logs is processed to derive the autocorrelation values of the plurality of behavior logs, and as a result of comparing the autocorrelation values among the plurality of behavior logs, And selects a specific behavior log having the largest autocorrelation value among the behavior logs and having a set ratio relationship with the autocorrelation value of another behavior log. 3. The method of claim 2,
The set ratio relationship is set such that,
The second behavior log having the largest autocorrelation value among the remaining behavior logs excluding the first behavior log having the largest autocorrelation value in the plurality of behavior logs and the third behavior log having the largest autocorrelation value, And the autocorrelation value of the second behavior log is greater than or equal to the first threshold ratio and the difference between the autocorrelation value of the first behavior log and the autocorrelation value of the third behavior log is greater than the first threshold The second threshold ratio being greater than the second threshold ratio. 3. The method of claim 2,
The selection instruction includes:
Wherein in the step of selecting the specific action log based on the autocorrelation value corresponding to the maximum cumulative number of times, applying the maximum cumulative number of times during the specific period to a predetermined reference action log in the plurality of behavior logs, So that the log can be excluded. The method according to claim 1,
The plurality of behavior logs comprising:
Wherein the plurality of categories are divided into at least two subcategories,
Wherein the cumulative state for the plurality of behavior logs is determined by:
And a graph in which the cumulative number of each of the two or more sub-categories during the specific period is arranged in a predefined order. The method according to claim 1,
Wherein the at least one instruction comprises:
And classifying the two or more users into a similar user group when there are two or more users whose interest categories agree with each other. A processor for processing an operation for providing a targeting service; And
Wherein at least one instruction executed via the processor comprises a stored memory,
Wherein the at least one instruction comprises:
A confirmation command for causing the user analysis device to confirm the service selection information for the user according to a request from the user; And
And a selection command for selecting a targeting service based on the service selection information so that the selected targeting service is provided to the user. 8. The method of claim 7,
The advertisement selection information includes:
At least one of an interest category designated for the user and a similar user group to which the user belongs,
The selection instruction includes:
Selects a targeting service designated in the interest category, or selects a targeting service previously provided to another user in the similar user group. A confirmation step of confirming a cumulative state of a plurality of behavior logs collected in association with a user during a specific period and classified and accumulated in a plurality of categories; And
Selecting an action log indicating an attribute of the user during the specific period among the plurality of action logs based on the cumulative state of the plurality of action logs and designating the specific category to which the selected action log belongs as the interest category of the user The method comprising the steps of: (a) selecting a user to be analyzed; 10. The method of claim 9,
In the selecting step,
An autocorrelation operation on the cumulative states of the plurality of behavior logs is performed to derive an autocorrelation value of each of the plurality of behavior logs and a result of comparing the autocorrelation values of the plurality of behavior logs with each other, Wherein the specific action log having the largest autocorrelation value among the logs and having a setting ratio relationship with respect to autocorrelation values of other behavioral logs is selected. 11. The method of claim 10,
The set ratio relationship is set such that,
The second behavior log having the largest autocorrelation value among the remaining behavior logs excluding the first behavior log having the largest autocorrelation value in the plurality of behavior logs and the third behavior log having the largest autocorrelation value, And the autocorrelation value of the second behavior log is greater than or equal to the first threshold ratio and the difference between the autocorrelation value of the first behavior log and the autocorrelation value of the third behavior log is greater than the first threshold The second threshold ratio being greater than the second threshold ratio. 11. The method of claim 10,
In the selecting step,
Wherein in the step of selecting the specific action log based on the autocorrelation value corresponding to the maximum cumulative number of times, applying the maximum cumulative number of times during the specific period to a predetermined reference action log in the plurality of behavior logs, Wherein the log is excluded from the log.

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