KR20140137653A - A Method and Device for Analyzing the Event log to extract co-occurrences - Google Patents

Abstract

If an event occurs in an electronic device, a processor collects information of the event, time in which the event occurs, and location data of the electronic device. The processor clusters the event log into at least one cluster. The information related to the cluster is created, and the cluster is labeled with a predetermined name based on the time and the location data contained in the event log. In addition, if a new event occurs in the electronic device, the processor collects the event log and determines the distance between the central value of the cluster and the event log newly collected. If the distance is equal to or less than a predetermined value, the event log, which is newly collected, is contained in the cluster, and the central value of the cluster is calculated. The number of the events contained in the cluster may be increased.

Description

Technical Field [0001] The present invention relates to an event log analyzing method and apparatus for an electronic device,

The following embodiments are directed to a method and apparatus for extracting and modeling a pattern representing a user's electronic device usage pattern and daily life by collecting and analyzing an event log generated according to usage of the electronic device.

Event logging is the recording of software and hardware events on electronic devices. The software module or the hardware module of the electronic device generates and transmits an event to the event log collection unit, and the event log collection unit stores the event log in the storage unit. The event log is a record of the sequence of operations of the processes running on the terminal.

Analyzing the event log stored in the electronic device, the user's interest, intention, and characteristics of the electronic device using the electronic device can be analyzed and utilized to provide a user-customized service or a user context aware service.

An object of the present invention is to provide an electronic device that collects event logs including event information, event occurrence time, and location data of electronic devices when an event occurs in an electronic device, clusters event logs, A method of analyzing an event log of an electronic device capable of predicting a user's electronic device usage pattern by adding a label name to a cluster.

It is another object of the present invention to provide an electronic device capable of improving the accuracy of pattern analysis for repeated activities in a user's daily life and providing a better user experience (UX) And an apparatus and method for analyzing an event log.

According to an exemplary embodiment, when an event occurs in an electronic device, collecting an event log including the event information, an event occurrence time and position data of the electronic device, clustering the event log into at least one cluster Generating information related to the cluster, and adding a label name to the cluster based on time and location data included in the event log.

The method may obtain a place name from the outside of the electronic device based on the location data, and cause the place name to be included in the label name. The clustering step may classify and cluster the event logs associated with the hardware of the electronic device and the event logs associated with the software of the electronic device.

 The information related to the cluster may include the center value of the cluster and the number of event logs constituting the cluster. The information associated with the cluster is accessible from an app running on the electronic device.

According to yet another exemplary embodiment, there is provided a method comprising: comparing a first cluster and a second cluster, each of which has a different center value, with an event log generated in response to an event occurrence in an electronic device; Determining a similarity between the first cluster and the second cluster based on position data of the apparatus, determining the first cluster and the second cluster as one group based on the similarity, The method comprising the step of storing the information.

The information on the group may include a group ID, each cluster ID constituting the group, and similarity-related information of each cluster. Information about the group is accessible from an app running on the electronic device.

According to another exemplary embodiment, there is provided an electronic device, comprising: collecting an event log when a new event occurs in the electronic device; determining a distance between the center value of the cluster and the collected event log; , Including the step of including the event log in the cluster, recalculating the center value of the cluster, and increasing the number of event logs included in the cluster .

The label name is editable by user input.

When an event occurs in an electronic device, an event log including event information, an event occurrence time and position data of the electronic device is collected, an event log is clustered, and a label name The electronic device usage pattern of the user can be predicted. Through this, it is possible to improve the accuracy of the pattern analysis of the activities repeated in the user's daily life, and thereby provide a better user experience (UX) in context awareness and customized services.

Figure 1 schematically depicts an electronic device of the present invention;
2 is a block diagram illustrating the hardware of the present invention.
3 is a block diagram of software of the present invention
4 is a block diagram conceptually showing a block for processing an event log in a processor when an event occurs
5 is a diagram showing event log information stored in an event log storage unit
6 is a view showing cluster information stored in the cluster information storage unit
7 is a diagram showing group information
FIG. 8 is a flowchart showing a processing procedure when an event occurs
9 is a flowchart showing a processing procedure when a new event occurs
10 is a flowchart showing a process of comparing two clusters to generate a group

An object of the present invention is to extract a contextual pattern group based on various types of data that have not been refined. Clusters are created by accumulating data based on events occurring according to activity and state change of electronic devices. The items constituting the cluster have different values for each cluster, which is meaningful for quantifying contextual information. Once the cluster is created, the cluster is updated whenever data is fetched. The result of extracting the similar data among the cluster information is referred to as a co-occurrence, and a contextual pattern group is generated considering a user situation in which a cluster having a result exceeding a threshold value is a member. K-means and nested-EM algorithms are used as the clustering method, and the user has a function of labeling in the contextual pattern group considering the clustering or the situation. It has logic that reflects the feedback so that a more accurate cluster can be created each time data is imported.

In the following, these and other aspects of the exemplary embodiments are described in detail with reference to the accompanying drawings. However, the present invention is not limited or limited by the embodiments. Like reference symbols in the drawings denote like elements.

Also, the singular forms used in this specification and the appended claims are intended to include the plural forms as well, unless the context clearly dictates otherwise. It is also to be understood that the term "and" as used herein refers to and includes all possible combinations of one or more of the listed related items.

Also, the methods described in connection with the flowcharts may be altered by reordering the steps shown in the flowchart, or by repeating or omitting certain steps.

Hereinafter, the present disclosure will be described with reference to the accompanying drawings.

1 schematically illustrates an electronic device 100 according to an exemplary embodiment.

Referring to FIG. 1, the electronic device 100 may include hardware 110 or software 120. A description of one embodiment of the hardware 110 is provided in connection with FIG. The software 120 may include a kernel 121, a middleware 122, an application programming interface (API) 123, or an application 124, Is provided in connection with FIG.

The electronic device 100 may be any electronic device such as an electronic watch, a refrigerator, an air conditioner, a vacuum cleaner, an artificial intelligent robot, a TV, a DVD (digital video disk) player, an audio oven, a microwave oven, (E.g., magnetic resonance angiography (MRA), magnetic resonance imaging (MRI), computed tomography (CT), ultrasound), a navigation device, a black box, An electronic dictionary, an automobile device, a shipbuilding device, an aviation device, a security device, an electronic apparel, an electronic key, a concentrated fishery device, a desktop personal computer, a laptop personal computer, A personal digital assistant (PDA), a portable multimedia player (PMP), a tablet personal computer, a mobile phone, a videophone, a smartphone, an electronic book reader, a camera, a wearable device, (wireless device), GPS reception A global positioning system receiver, a hand-held device, an MP3 player, a camcorder, game consoles, a wrist watch, a head-mounted display (HMD) A digital panel, a flat panel device, a digital picture frame, an electronic board, an electronic signature receiving device or a projector. It will be apparent to those skilled in the art that the electronic device according to the present disclosure is not limited to the devices described above.

FIG. 2 schematically illustrates hardware 200 (e.g., hardware 110) according to an exemplary embodiment. Referring to FIG. 2, the hardware 200 may include one or more processors 201. 2, the processor 201 may include one or more application processors (APs) 201A and one or more communication processors (CP) 201B, for example. . The AP 201A is a processor capable of controlling a plurality of hardware or software components connected to the AP 201 by driving an operating system or an application program and performing various data processing and calculation including multimedia data, For example, a system on chip (SoC). In some implementations, the processor 201 may further include a graphics processing unit (GPU) (not shown).

The CP 201B is a processor capable of performing the communication function of an electronic device (e.g., the electronic device 100) including the hardware 200 (e.g., the hardware 110), for example, . In some implementations, the CP 201B may perform at least some of the multimedia control functions. In addition, the CP 201B performs identification and authentication of terminals in a communication network using a subscriber identification module such as a SIM card (subscriber identification module card) 221, and provides the user with a voice call, a video call, a text message, And may provide services such as packet data. In addition, the CP 201B can control data transmission / reception of a radio frequency unit (RF unit) 205. 2, components such as the CP 201B, the power management unit 203, or the memory 204 are shown as separate components from the AP 201A. However, according to some embodiments, the AP 201A May include at least a portion of the above-described components (e.g., CP 201B).

 The RF unit 205 is responsible for transmitting and receiving data, for example, an RF signal or a transmitted and received electronic signal. The RF unit 205 may include, for example, a transceiver, a power amplifier module (PAM), a frequency filter, or a low noise amplifier (LNA). The RF unit 205 may further include a component for transmitting and receiving electromagnetic waves in a free space in a wireless communication, for example, a conductor or a conductor.

The hardware 200 may include an internal memory 204A or an external memory 204B. The built-in memory 204A may be a nonvolatile memory such as a dynamic RAM (DRAM), a static RAM (SRAM), a synchronous dynamic RAM (SDRAM), or a nonvolatile memory such as an OTPROM one-time programmable ROM), programmable ROM (PROM), erasable and programmable ROM (EPROM), electrically erasable and programmable ROM (EEPROM), mask ROM, flash ROM, and the like. According to one embodiment, the AP 201A or the CP 201B may load and process commands or data received from at least one of the nonvolatile memory or other components connected to the AP 201A or 201B into the volatile memory . Also, the AP 201A or the CP 201B may store data received or generated from the other components in the nonvolatile memory.

The external memory 204B may be a compact flash (CF), a secure digital (SD), a micro secure digital (SD), a mini secure digital (SD), an extreme digital And the like.

The power management unit 203 can manage the power of the hardware 200. [ Although not shown, the power management unit 203 may include, for example, a PMIC (power management integrated circuit), a charger integrated circuit (IC), or a battery gauge. The PMIC can be mounted, for example, in an integrated circuit or a SoC semiconductor. The charging method can be classified into wired and wireless. The charging IC can charge the battery, and can prevent an overvoltage or an overcurrent from the charger. At this time, the charging IC may include a charging IC for at least one of a wired charging method and a wireless charging method. Examples of the wireless charging system include a magnetic resonance system, a magnetic induction system or an electromagnetic wave system, and additional circuits for wireless charging, for example, a coil loop, a resonant circuit, a rectifier, have. The battery gauge may measure at least one of the remaining amount of the battery 223, the voltage during charging, the current, or the temperature. The battery 223 may generate electricity to supply power, for example, a rechargeable battery.

The interface 206 is connected to an interface such as an HDMI (mHL) 206A, a universal serial bus 206B, a projector 206C, a D-subminiature 206D, / Multi-media card (MMC) (not shown), or IrDA (infrared data association, not shown).

The communication unit 230 may provide a wireless communication function using a radio frequency and may transmit at least one of a WiFi 207A, a Bluetooth (BT) 207B, a GPS 207C or a near field communication (NFC) . Additionally or alternatively, the communication unit 230 may communicate the hardware 200 with a network (e.g., the Internet, a LAN, a WAN, a telecommunication network, a cellular network, old telephone service, etc.), or a modem (e.g., a LAN card).

The user input unit 208 may receive various commands from the user. The user input 208 may include at least one of, for example, a touch screen panel 208A, a (digital) pen sensor 208B, a key 208C or an ultrasonic input device 208D . The touch screen panel 208A can recognize a touch input in at least one of an electrostatic, a pressure sensitive, an infrared, or an ultrasonic manner, for example. In addition, the touch screen panel 208A may further include a controller (not shown). In the case of electrostatic type, proximity recognition is possible as well as direct touch. The touch screen panel 208A may further include a tactile layer. In this case, the touch screen panel 208A may provide a tactile response to the user. The (digital) pen sensor 208B can be implemented using the same method as receiving the touch input of the user or using a separate recognizing sheet, for example. As the key 208C, for example, a keypad or a touch key may be used. The ultrasonic wave input device 208D is a device that can confirm data by sensing a sound wave from a terminal to a microphone (e.g., a microphone 215D) through a pen that generates an ultrasonic signal, and can recognize wirelessly. According to various embodiments, the hardware 200 may use the communication unit 230 to receive user input from an external device (e.g., a network, a computer or a server) connected thereto.

The display unit 209 is an apparatus for displaying images or data to a user and may be, for example, a panel 209A or a hologram 209B. As the panel 209A, for example, a liquid crystal display (LCD) or an active matrix organic light-emitting diode (AM-OLED) may be used. At this time, a controller for controlling the panel 209A may be further configured. The panel 209A may be embodied, for example, in a flexible, transparent or wearable manner. The panel 209A may be composed of a touch screen panel and one module. The hologram 209B can display stereoscopic images in the air using interference of light.

The camera unit 210 may capture an image and a moving image and may include one or more image sensors (e.g., a front lens or a rear lens), an image signal processor (ISP), or a flash LED , Not shown).

The indicator 211 may indicate a specific state of the hardware 200 or a part thereof (e.g., the AP 201A), for example, a boot state, a message state, or a charged state. The motor 212 may convert the electrical signal to mechanical vibration.

The sensor unit 213 includes a gesture sensor 213A, a gyro sensor 213B, a barometer sensor 213C, a magnetic sensor 213D, An acceleration sensor 213E, a grip sensor 213F, a proximity sensor 213G, an RGB (red, green, blue) sensor 213H, a biometric sensor, A temperature / humidity sensor 213J, an illuminance sensor 213K, an ultraviolet sensor 213L, an olfactory sensor (not shown), an electromyography sensor An electroencephalogram sensor (not shown), an electrocardiogram sensor (not shown), or a fingerprint sensor. In some implementations, the hardware 200 may further include a micro controller unit (MCU) 214 for controlling the sensor unit 213.

The audio codec 215 can convert audio and electrical signals in both directions. The audio codec 215 can convert audio information input or output through, for example, a speaker 215A, a receiver 215B, an earphone 215C, or a microphone 215D. Although not shown, the hardware 200 may include a processing unit (e.g., a GPU) for mobile TV support. The processing device for supporting the mobile TV can process media data conforming to standards such as digital multimedia broadcasting (DMB), digital video broadcasting (DVB), or media flow.

The names of the above-described components of the hardware according to the present disclosure may vary depending on the type of electronic device, and the hardware according to the present disclosure may be configured to include at least one of the components described above, Or < / RTI > additional other components.

FIG. 3 schematically illustrates software 300 (e.g., software 120) in accordance with an exemplary embodiment. The software 300 may be implemented in hardware (e.g., the hardware 200) to control an operating system (OS) that controls resources associated with an electronic device (e.g., the electronic device 100) Application 340). The operating system may be, for example, Android, iOS, Windows, Symbian, Tizen, or Bada.

The kernel 310 may include a system resource manager 311 or a device driver 312 that can manage resources. For example, the system resource manager 311 may include a process management unit 311A, a memory management unit 311B, or a file system management unit 311C, and may perform control, assignment, or recovery of system resources have.

The device driver 312 allows various components of the hardware (e.g., the hardware 200) of the electronic device (e.g., the electronic device 100) to be accessed and controlled in a software manner. To this end, the device driver 312 may be divided into, for example, an interface and individual driver module parts provided by respective hardware vendors, though not shown. For example, the device driver 312 may include a display driver 312A, a camera driver 312B, a Bluetooth driver 312C, a shared memory driver 312D, a USB driver 312E, a keypad driver 312F, a WiFi Driver 312G, an audio driver 312H, or an inter-process communication (IPC) driver (not shown).

The middleware 320 may include a plurality of modules previously implemented in order to provide functions commonly required in various applications. The middleware 320 may provide functions that are commonly required through the API 330 so that the application 340 can efficiently use limited system resources in the electronic device. The middleware 320 includes an application manager 320A, a window manager 320B, a multimedia manager 320C, a resource manager 320D, A power manager 320E, a database manager 320F, or a package manager 320G, as shown in FIG.

The application manager 320A can manage a life cycle of at least one application among the applications 340. [ The window manager 320B can manage GUI resources used on the screen. The multimedia manager 320C can recognize a format required for reproducing various media files and can encode or decode a media file using a codec according to the format. The resource manager 320D can manage resources such as a source code, a memory or a storage space of at least one of the applications 340. [ The power manager 320E operates in conjunction with a basic input / output system (BIOS) or the like to manage a battery or a power source and provide power information necessary for the operation. The database manager 320F can manage a database to be used in at least one of the applications 340 to create, search, or change the database. The package manager 320G can manage installation or update of an application distributed in the form of a package file.

The middleware 320 may include a connectivity manager 320H, a notification manager 320I, a location manager 320J, a graphic manager 320K, ) Or a security manager (320L).

The connection manager 320H can manage a wireless connection, such as WiFi or Bluetooth, for example. The notification manager 320I may display or notify events such as arrival messages, appointments, proximity notifications, etc. in a manner that does not disturb the user. The location manager 320J may manage the location information of the electronic device. The graphic manager 320K may manage a graphical effect to be provided to a user and a user interface related thereto. The security manager 320L may provide security functions necessary for system security or user authentication.

When the electronic device (e.g., the electronic device 100) has a telephone function, the middleware 320 further includes a telephony manager (not shown) for managing the voice or video call function of the electronic device can do.

According to an exemplary embodiment, the middleware 320 may include a runtime library 325 or other library modules (not shown). The runtime library 325 is a library module used by the compiler to add new functions through a programming language while the application is running. For example, the runtime library 325 may perform functions such as input / output, memory management, or arithmetic functions. The middleware 320 can generate and use a new middleware module through various functional combinations of the internal component modules. The middleware 320 may provide a module specialized for each type of operating system to provide a differentiated function.

In addition, the middleware 320 may dynamically delete some existing components or add new components. Accordingly, the components described in the embodiments of the present disclosure may be partially replaced with other components, or may be replaced with components having other names that perform similar functions.

The API 330 is a set of API programming functions and can be provided in different configurations depending on the operating system. For example, in the case of Android or iOS, for example, one API set can be provided for each platform, and in the case of Tizen, for example, two or more API sets can be provided.

The application 340 represents at least one application program (s) implemented in a corresponding electronic device (e.g., the electronic device 100) using the API 330. [ The application 340 may include, for example, a preloaded application or a third party application. The application 340 may be configured to return to the home screen 340A, a dialer 340B, a short message server (SMS) / multi-media message service (MMS) 340C, an IM an instant message 340D, a browser 340E, a camera 340F, an alarm 340G, contacts (or address book) 340H, a voice dial 340I An email 340J, a calendar 340K, a media player 340L, an album 340M, or a clock 340N.

The names of the above-mentioned components of the software according to the present disclosure may vary depending on the type of operating system. In addition, the software according to the present disclosure may include at least one or more of the above-described components, some of which may be omitted, or may further include other additional components.

FIG. 4 is a block diagram illustrating a process of processing an event log in a processor when an event occurs. 2 and 4, a sensor unit 402, a communication unit 404, a timer 406, a processor 400, and a storage unit 430 are illustrated. The processor 400 can read the program code in the storage unit 430, create a process, and process data according to the process. The processor 400 may include an app information collecting unit 408, an event log collecting unit 410, a cluster generating unit 412, and a group generating unit 414. [ The app information collecting unit 408, the event log collecting unit 410, the cluster generating unit 412, and the group generating unit 414 are processes. The process may be generated for a short time in the processor 400 and may disappear at the end of the process.

The sensor unit 402 can generate an event when a sensor value changes. For example, the ambient light sensor 213K can detect an ambient brightness change of an electronic device and generate an event. The communication unit 404 may generate an event when data is received from the outside of the electronic device. Timer 406 may provide time information as an event.

The storage unit 430 may include an internal memory 204A and an external memory 204B. The storage unit 430 includes an event log storage unit 416, a cluster information storage unit 418, and a group information storage unit 420. The event log storage unit 416, the cluster information storage unit 418, and the group information storage unit 420 may be formed by dividing only the storage area in the same storage unit 420. In addition, the event log storage unit 416, the cluster information storage unit 418, and the group information storage unit 420 may be separate storage spaces.

 The electronic device can receive the reference time through the communication unit 404 and calculate the current time based on the reference time and an event occurring in the timer. Further, the electronic device can receive the current time through the communication unit 404. In addition, various changes in hardware and software that occur in electronic devices can be events. For example, an event may occur depending on the ON / OFF state of the display unit, the unlock state, the camera control button, the search button, whether or not the SD card is mounted, the battery charging state, the storage space usable, and the user gesture detection.

The app information collecting unit 408 collects information related to the executed app. For example, when a particular app launches, it can collect date, time, app name, and location data at the time it launches. In addition, the app information collecting unit 408 can collect information on other currently running apps and information on previously executed apps.

The event log collecting unit 410 collects an event log when an event occurs in the sensor unit 402, the communication unit 404, the timer 406, and the app information collecting unit 408. The collected event logs are stored in the event log storage unit 416 or sent to the cluster generator for analysis.

The event log storage unit 416 may be configured as a database.

The cluster generating unit 412 analyzes and clusters the event log received from the event log collecting unit 410. The cluster generating unit 412 may analyze the event log stored in the event log storing unit 416 and perform clustering.

The cluster information storage unit 418 stores the cluster information analyzed by the cluster generating unit. The cluster information storage unit 418 may be constituted by a database.

The group generating unit 414 groups the similar clusters into one group by referring to the cluster information stored in the cluster generating unit 412 and the cluster information storing unit 418 and transmits the related group information to the group information storing unit 420 . The group information storage unit 420 may be configured as a database. The cluster information generated by the cluster generating unit 412 and the group information generated by the group generating unit 414 are provided as APIs so that the app can directly access the group information when the app is executed in the electronic device.

The event log storage unit 416, the cluster information storage unit 418 and the group information storage unit 420 may be included in the same storage unit 430 or may be configured as separate storage units.

The cluster generating unit 412, the group generating unit 414, the cluster information storing unit 418, and the group information storing unit 420 may be provided in a server (not shown) separate from the electronic device. In this case, the event log collected by the event log collecting unit may be provided to the server through the communication unit. The server analyzes the collected event logs and provides the related cluster information and group information to the electronic device through the communication unit.

5 is a diagram illustrating event log information stored in the event log storage unit. 4 and 5, the event log may include an event log ID 502, event information 504, event related time information 506, and location information 508. Event logs 510, 512, 514, 516, 518, and 520 are stored in the event log storage unit 416 in the form of a database.

The event log ID 502 may be given as a serial number according to the event occurrence order. For example, the event log ID 502 may be assigned a serial number such as 'E1', 'E2', 'E3', .... The event log ID 502 may be given by the event log collecting unit 410 and may be given by another process. Each event log may have its own event log ID 502.

The event information can be given by reflecting the characteristics of the generated event. The event characteristic can be divided into a hardware event generated by the hardware and a software event generated by the software. Events generated by hardware can be events generated by sensors and hardware modules. At this time, the event information may include the name of the sensor and the hardware module that generated the event. For example, the event information may include hardware module names such as 'BT (Blue Tooth)', 'WiFi', 'MAGNETIC', and 'GPS'. Events generated by the software can be generated when the app is launched. For example, if you run 'Map app', an event may occur. In this case, the event information may include the name of the app that generated the event. Event information can include app names like 'Map', 'Phone book', 'Play'.

The event-related time information may be the time, date, and day of the week when the event occurred. For example, the time information could be like '2010-11-09 18:07:35 WED'.

The location information is the location data of the electronic device when the event occurs. The location information may be provided in coordinates including longitude and latitude. The location information may be data received from GPS satellites. The location information may be a cell ID received from a communication base station (not shown) or a WiFi AP (access point). For example, the location information may be '127.0517465, 37.2390389'.

When an event occurs, the event log collecting unit 410 collects an event log generated by hardware and software. For example, when the user executes the 'Map application', the event log collection unit 410 stores the event log 510 in the event log storage unit 416. When the user executes the 'Phone book application', the event log collecting unit 410 stores the event log 512 in the event log storing unit 416. When the user turns on the 'WiFi', the event log collection unit 410 stores the event log 518 in the event log storage unit 416.

6 is a diagram illustrating cluster information stored in the cluster information storage unit. 4 and 6, the cluster information includes a cluster ID 602, a label name 604, event log information 606, a center value 608, a distance 610, and an event log number 612 ). The cluster information storage unit 418 stores cluster information 614, 616, 618, and 620 in the form of a database.

The cluster ID 602 may be assigned a serial number. For example, the cluster ID may be assigned a serial number such as 'C1', 'C2', 'C3', 'C4', ... The label name 604 may be information for identifying the cluster. The label name 604 can be automatically assigned by the processor 400 based on the center value 608 included in the cluster information. When the center value is the position information, the place name where the electronic device is located may be given as the label name. For example, if the center value of the cluster 'C1' is '127.03, 37.51', the processor 400 obtains from the map data that the corresponding position is 'Gangnam-gu', and determines the label name of the cluster C1 as 'Gangnam-gu'. The map data may be provided from a server (not shown) external to the electronic device or embedded in the electronic device. Label names may be assigned by the user. The user can view the location of 'Gangnam-gu' and modify the label name to 'office'.

Electronic devices can use knowledge bases when labeling. For example, if the center value of the cluster is similar to the situation in which the user has performed a movement in the past, the electronic device may determine the label name to be 'motion'.

The configuration event log 606 is a plurality of event log IDs (IDs) included in the cluster. For example, the event log ID (ID) belonging to the cluster C1 is 'E1, E4, E5, E7, E10, E23, E32, ...'.

The center value 608 is the center value of each cluster. The center value of the cluster can be calculated using various algorithms. For example, an average of the time and location data included in the event log information constituting each cluster. The center value of cluster 'C1' 614 is '127.03, 37.51'.

Distance 610 may be the maximum distance from the cluster center value 608 to the time or location data of the event logs that make up the cluster. Distance 610 may be the size of the cluster. For example, the distance of cluster 'C1' is '0.9, 0.9'. The distance may vary depending on the type of event log that makes up the cluster. For example, if the event log that makes up the cluster is characterized by location, the distance can be a location. If the event log constituting the cluster is characterized by time, the distance 610 may be time.

The center value 608 and the distance 610 can be changed if a new event log is included in the cluster. The processor recalculates the center value 608 and distance 610 when a new event log is included in the cluster.

The number of event logs 612 is the number of event logs included in the cluster. For example, the number of event logs included in cluster 'C1' 614 is '80'.

The cluster information may be stored in the storage unit 430 in the form of a database. For example, cluster information 'C1, C2, C3, C4, ...' is stored in the storage unit 430. E5, E7, E10, E23, E32, ..., ', the center value is' 127.03, 37.51', and the distance between the cluster 'C1''0.9,0.9', and the number of event logs is '80'. The label name of the cluster 'C2' 616 is 'home' and the configuration event log is 'E23, E34, E53, ..., E171', the center value is '125.3, 36.2' The number of event logs is '120'. The label name of the cluster 'C3' 618 is 'motion', the configuration event log is 'E3, E7, E9, E11, E90, ..., E232' , The distance is '10: 00 ', and the number of event logs is'28'.

7 is a diagram showing group information. Referring to FIGS. 4 and 7, the group information 710, 712, and 714 may include a group name 702, a label name 704, a configuration cluster 706, and similarity determination information 708. The group information storage unit 420 stores group information 710, 712, and 714 in a database format.

The group name 702 may be given as a serial number. For example, the group name may be given as a serial number such as 'G1', 'G2', 'G3', .... The label name 704 may be given a serial number or may be assigned a name that characterizes each group well. The label name 704 may be automatically assigned by the processor 400. The label name 704 may be given based on the similarity judgment information 708. [ For example, if the similarity determination information 708 is determined to be 'sleeping', the processor 400 determines the label name to 'sleep' and confirms the label name through the approval process of the user.

The configuration cluster 706 is information on the cluster constituting the group. For example, the clusters constituting the group 'G1' 710 are 'C1' and 'C2'. The cluster constituting the group 'G2' (712) is 'C3'. The cluster constituting the group 'G3' 714 is 'C1', 'C5', and 'C9'.

The similarity judgment information 708 is information on similar data that each cluster constituting the group has. Similarity determination information 708 may be time, location, and frequency. For example, when the center values of the clusters 'C1' and 'C2' constituting the group 'G1' 710 are similar in time and position, the similarity determination information 708 may be time and position.

The similarity determination information 708 can be determined by comparing the center values of the respective clusters or by comparing the data constituting the event logs included in each cluster. For example, the clusters constituting the group 'G3' 714 are 'C1', 'C5', and 'C9'. Cluster 'C1' was clustered based on location. The center value of cluster 'C1' is '127.03, 37.51'. Cluster 'C5' was clustered based on time. The center value of cluster 'C5' is (MON, 22:20:21). Cluster 'C9' was clustered based on changes in ambient sensor values. The center value of cluster 'C9' is '20'. Processor 400 may obtain similarity determination information by analyzing clusters 'C1', 'C5', and 'C9'. For example, clusters 'C1', 'C5' and 'C9' occurred at the same time. Therefore, the similarity determination information of the group G3 714 may be 'time'. After a similar analysis process, the processor can determine the similarity determination information of the group G1 710 as 'time' and 'position', and determine the similarity determination information of the group G2 712 as the 'frequency number'.

FIG. 8 is a diagram illustrating a processing procedure when an event occurs. Referring to FIGS. 4 and 8, when an event occurs in the electronic device (step 802), the processor collects an event log including event information, an event occurrence time and position data of the electronic device (step 804). The event log may include an event log ID, event information, event related time information, and location information. The event-related time information may be the time, date, and day of the week when the event occurred. For example, the time information could be like '2010-11-09 18:07:35 WED'. The location information is location data of the electronic device when the event occurs. The location information may be provided in coordinates including longitude and latitude.

When an event occurs, the event log collecting unit 410 collects event logs generated by the sensor unit 402, the communication unit 404, the timer 406, and the app information collecting unit 408, (416).

Processor 400 clusters event logs into at least one cluster (step 806). The processor 400 clusters the event logs if the number of event logs stored in the event log storage unit 416 is greater than a predetermined value. For example, the processor 400 clusters event logs stored in the event log storage unit 416 when the number of clusters stored in the event log storage unit 416 is 30 or more. The processor 400 generates information related to the cluster (step 808). The information related to the cluster includes a cluster ID 602, a label name 604, event log information 606 constituting a cluster, a center value 608, a distance 610 and an event log number 612 constituting a cluster . Clustering-related information is provided as an API and is accessible from an app running on an electronic device.

The processor 400 adds a label name to the cluster based on the time and location data contained in the event log (step 810). The label name can be automatically assigned by the processor 400 based on the center value included in the cluster information. The processor 400 may obtain a nomination from outside the electronic device based on the location data and cause the name to be included in the label name. For example, if the center value of the cluster is '127.03, 37.51', the processor 400 obtains from the map data that the corresponding location is 'Gangnam-gu', and determines that the label name of the cluster includes 'Gangnam-gu'. The map data may be provided from a server (not shown) external to the electronic device or embedded in the electronic device.

The processor 400 may separate and cluster the event logs associated with the hardware of the electronic device and the event logs associated with the software of the electronic device. For example, the processor 400 may configure the event log generated by the sensor unit 402, which is a hardware module, through one or more clusters through the event log collecting unit 410. The processor 400 may configure the event log generated by the app information collecting unit 408, which is a software module, through one or more clusters through the event log collecting unit 410.

9 is a flowchart showing a process when a new event is generated in a state where a cluster is created. Referring to FIGS. 4 and 9, when a new event is generated in a state where the cluster is created (step 902), the processor collects an event log (step 904). The processor 400 compares the center value of the cluster with the data contained in the new event log to determine the distance between the center value of the cluster and the event log (step 906). Here, the distance is the difference between the center value of the cluster and the value of each data included in the event log. The center value of the cluster may be location data, time data, sensor value, etc. depending on the type of the cluster. Depending on the type of cluster, the center value can be a variety of values. When the center value of the cluster is the position data, the processor 400 compares the position data included in the new event log with the center value of the cluster when a new event occurs. If the center value of the cluster is time data, the processor 400 compares the time data included in the new event log with the center value of the cluster when a new event occurs. The processor 400 determines whether the distance is less than or equal to a predetermined value (step 908). For example, if a new event occurs on Sunday at 21:52 with cluster 'C1' having a center value of 'SUN, 21:52:12', the processor 400 determines that the center value of cluster 'C1' And the new event log. Since the center value of C1 is 'SUN, 21:52:12', the processor includes an event log for the event occurring at 21:52 on Sunday in cluster 'C1'. The processor 400 recalculates the center value of the cluster and also increments the number of event logs (step 910). The number of clusters " C1 " increases by one and the center value is calculated again. If the data contained in the new event is greater than a predetermined distance from the center value of the cluster 'C1', the processor 400 does not include the new event in the cluster 'C1', but stores it as a separate event log.

10 is a flowchart illustrating a process of generating a group by comparing two clusters. The processor 400 comprises an event log generated according to an event occurrence in the electronic device, and compares the first cluster and the second cluster having different center values (step 1002). For example, the first cluster has been clustered based on location. The center value of the first cluster is '127.03, 37.51'. The second cluster was clustered on a time basis. The center value of the second cluster is 'MON, 22:20:21'. The first cluster includes a plurality of event logs. The location data of the event log included in the first cluster has a value within a predetermined distance centered on '127.03, 37.51' which is the center value of the first cluster. The time data of the event log included in the second cluster has a value within a certain distance centering on the central value of 'MON, 22:20:21' of the second cluster.

The processor 400 determines the similarity of the first cluster and the second cluster based on the time information related to the event and the location data of the electronic device (step 1004). The processor 400 first determines the similarity by comparing the center values of the first and second clusters. Since the center value of the first cluster and the center value of the second cluster are different types of data, the processor 400 determines that the center values of the clusters are not similar to each other. Next, the processor 400 judges the similarity based on the time information and the position data of the event log included in the first cluster and the second cluster. For example, the event log included in the first cluster was collected within a certain time on Monday at 22:20. At this time, the center value of the first cluster is '127.03, 37.51', but the time information included in the event log has a value within a certain time centered on Monday at 22:20. Since the center value of the second cluster is 'MON, 22:20:21', the time information included in the event log of the second cluster also has a value within a certain time centered on Monday 22:20:21. The processor 400 determines that the time information of the first cluster and the time information of the second cluster are similar.

The processor 400 determines the first cluster and the second cluster as a group based on the similarity (step 1006). Since the first cluster and the second cluster have similarity to the time information, the processor 400 determines the first cluster and the second cluster as one group based on the time information.

The processor 400 stores information about the group (step 1008). The processor 400 stores the information on the group in the group information storage unit 430. Information about the group is stored in the form of a database. The information on the group includes the group name, each cluster ID constituting the group, and similarity-related information of each cluster. The group name may be given as a serial number. For example, the group name may be given as a serial number such as 'G1', 'G2', 'G3', .... The cluster ID of the first cluster is 'C1'. The cluster ID of the second cluster is 'C2'. Each cluster ID constituting the group may be 'C1' and 'C2'. In this case, the similarity related information is 'time information'. Since the first cluster and the second cluster are formed into one group based on the time information, the processor 400 determines and stores the similarity related information as 'time'.

Information about the group is accessible from an app running on the electronic device. Information about the group can be provided by the API. When an app runs on an electronic device, the app can access information about the group and provide related services.

The contents described above may be implemented in the form of program instructions that can be executed through various computer means and recorded in a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, and the like, alone or in combination. The program instructions recorded on the 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. Examples of computer-readable media include magnetic media such as hard disks, floppy disks and magnetic tape; optical media such as CD-ROMs and DVDs; magnetic media such as floppy disks; Magneto-optical media, and hardware devices specifically configured to store and execute program instructions such as ROM, RAM, flash memory, and the like. Examples of program instructions include machine language code such as those produced by a compiler, as well as high-level language code that can be executed by a computer using an interpreter or the like. The above hardware devices may be configured to operate as one or more software modules to perform the operations of the present invention, and vice versa.

While the invention has been shown and described with reference to certain preferred embodiments thereof, it will be understood by those of ordinary skill in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims. This is possible. Therefore, the scope of the present invention should not be limited to the described embodiments, but should be determined by the equivalents of the claims, as well as the claims.

100: electronic device 400: processor
408: App information collecting unit 410: Event log collecting unit
412: Cluster Generation Unit 414:
402: sensor unit 404: communication unit
406: timer 430: storage unit
416: Event log storage unit 418: Cluster information storage unit
420: Group information storage unit

Claims (20)

Collecting an event log including the event information, an event occurrence time and position data of the electronic device when an event occurs in the electronic device;
Clustering the event logs into at least one cluster;
Generating information related to the cluster;
And adding a label name to the cluster based on time and location data included in the event log. The method according to claim 1,
Acquiring a place name from the outside of the electronic device based on the position data, and storing the place name in the label name. The method according to claim 1,
Wherein the label name is editable by user input. The method according to claim 1,
Wherein the clustering comprises:
An event log related to the hardware of the electronic device and an event log related to the software of the electronic device are classified and clustered. The method according to claim 1,
Wherein the information related to the cluster includes a center value of the cluster and a number of event logs constituting the cluster. The method according to claim 1,
Wherein information related to the cluster is accessible from an app running on the electronic device. The method according to claim 1,
Collecting an event log when a new event occurs in the electronic device;
Determining a center value of the cluster and a distance of the collected event log;
If the distance is less than or equal to a predetermined value, including the event log in the cluster;
Recalculating the center value of the cluster; And
And increasing the number of event logs included in the cluster. Comparing the first cluster and the second cluster, each of which has a different center value, from the event log generated according to the event occurrence in the electronic device;
Determining similarity between the first cluster and the second cluster based on time information related to the event and location data of the electronic device;
Determining the first cluster and the second cluster as a group based on the similarity; And
And storing information about the group. 9. The method of claim 8,
Wherein the information on the group includes a group ID, each cluster ID constituting the group, and similarity-related information of each cluster. 9. The method of claim 8,
Wherein information about the group is accessible from an app running on the electronic device. A sensor unit for generating an event when a sensor value changes;
A communication unit for generating an event when data is received from outside of the electronic device; And
Collecting event logs including the event information, an event occurrence time and position data of the electronic device when the event occurs in the sensor unit and the communication unit, clustering the event logs into at least one cluster, And a processor for adding a label name to the cluster based on time and location data included in the event log. 12. The method of claim 11,
Wherein the processor obtains a place name from the outside of the electronic device based on the position data, and causes the place name to be included in the label name. 13. The method of claim 12,
Wherein the label name is editable by user input. 12. The method of claim 11,
Wherein the processor is configured to classify and cluster event logs associated with hardware of the electronic device and event logs associated with software of the electronic device. 12. The method of claim 11,
Wherein the information related to the cluster includes a center value of the cluster and an event log number constituting the cluster. 12. The method of claim 11,
Wherein the information associated with the cluster is accessible from an app running on the electronic device. 12. The method of claim 11,
Wherein the processor collects an event log when a new event occurs in the electronic device, determines a distance between the center value of the cluster and the collected event log, and if the distance is less than or equal to a predetermined value, And recalculates the center value of the cluster and increases the number of event logs included in the cluster. A sensor unit for generating an event when a sensor value changes;
A communication unit for generating an event when data is received from outside of the electronic device; And
And an event log generated based on an event occurring in the sensor unit and the communication unit, wherein the first cluster and the second cluster having different center values are compared, and time information related to the event and position data of the electronic device Determining a similarity between the first cluster and the second cluster, determining the first cluster and the second cluster as a group based on the similarity, and storing information on the group ≪ / RTI > 19. The method of claim 18,
Wherein the information on the group includes a group ID, each cluster ID constituting the group, and similarity-related information of each cluster. 19. The method of claim 18,
Wherein the information about the group is accessible from an app running on the electronic device.

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