KR101842874B1 - Data visualization type recommendation method using meta information - Google Patents

Data visualization type recommendation method using meta information Download PDF

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KR101842874B1
KR101842874B1 KR1020150147023A KR20150147023A KR101842874B1 KR 101842874 B1 KR101842874 B1 KR 101842874B1 KR 1020150147023 A KR1020150147023 A KR 1020150147023A KR 20150147023 A KR20150147023 A KR 20150147023A KR 101842874 B1 KR101842874 B1 KR 101842874B1
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data
data visualization
meta information
type
source data
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KR1020150147023A
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Korean (ko)
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KR20170046881A (en
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정병준
임준원
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주식회사 뉴스젤리
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    • G06F17/30696—
    • G06F17/30991—
    • G06F17/30997—

Abstract

A data visualization type recommendation method using meta information is provided. The data visualization type recommendation method includes receiving source data, generating meta information of the source data defining characteristics of the source data, and generating meta information of the source data based on meta information and a matching rule of the source data. And recommending one or more types of data visualization for visualizing and representing the data.

Description

{DATA VISUALIZATION TYPE RECOMMENDATION METHOD USING META INFORMATION}

The present invention relates to data visualization, and more particularly, to a data visualization type recommendation method using meta information.

Data visualization refers to the transmission of information through visual means so that the results of data analysis can be easily understood. The purpose of data visualization is to convey information clearly and effectively through means such as charts or graphs. In response to changes in the presentation and acceptance of data, there is an increasing need for data visualization that visually depicts large amounts of information and efficiently provide the necessary information. Tools that support data visualization include tools designed for data management and charting, such as Microsoft's Excel and Google's Spreadsheets.

Japanese Patent Application Laid-Open No. 10-2015-0064312,

SUMMARY OF THE INVENTION It is an object of the present invention to provide a method for recommending a data visualization type suitable for clearly and effectively delivering analysis results of source data according to characteristics of source data.

The problems to be solved by the present invention are not limited to the above-mentioned problems, and other problems which are not mentioned can be clearly understood by those skilled in the art from the following description.

According to one aspect of the present invention, there is provided a method for performing a data visualization type recommendation method using meta information, the method comprising the steps of: receiving source data; Generating meta information of the data and recommending one or more types of data visualization for visualizing and representing the source data based on meta information and matching rules of the source data.

In some embodiments of the present invention, the meta information of the source data may include at least one of a size of data, a number of fields, or characteristics of each field.

In some embodiments of the present invention, the data visualization type recommendation method further comprises receiving from the user a selection of one or more of the data visualization types of the recommended data visualization type, and selecting the source data according to the selected data visualization type And visualizing and expressing it.

In addition, the data visualization representation may include an interactive element.

In some embodiments of the present invention, the data visualization type recommendation method further comprises generating meta information each of which defines a characteristic of a plurality of data visualization types, the method comprising the steps of: visualizing one or more data The step of recommending the visualization type may further comprise the step of, based on the meta information of the source data, the meta information of the plurality of data visualization types, and the matching rule between meta information of the source data and meta information of the plurality of data visualization types, One or more data visualization types may be recommended for visualizing and representing source data.

Also, recommending one or more types of data visualization for visualizing and representing the source data may include calculating each of the plurality of data visualization type recommendation indices, and performing data visualization with a maximum recommendation index among the plurality of data visualization types Type may be recommended as a data visualization type for visualizing and representing the source data.

The step of recommending one or more types of data visualization for visualizing and representing the source data may further include calculating a recommendation index for each of the plurality of data visualization types and selecting one of the plurality of data visualization types A data visualization type may be recommended as a data visualization type for visualizing and representing the source data.

Meanwhile, the meta information of the data visualization type may include at least one of a name, an applicable domain, an input property, and an output property.

In some embodiments of the present invention, the data visualization type recommendation method comprises receiving from a user a selection for one or more of the data visualization types of the recommended data visualization type, and comparing the meta information of the source data with the user ' Based on the selection of the visualization type, updating the matching rule.

In some embodiments of the present invention, the data visualization type recommendation method includes receiving a selection for one or more data visualization types of a data visualization type that is not recommended from a user, Based on the selection for the visualization type, adding a new matching rule.

According to the present invention, meta information for receiving source data and defining its characteristics is generated, and an appropriate data visualization type is recommended using meta information and matching rules of the source data to analyze the source data according to the characteristics of the source data You can recommend a type of data visualization that is appropriate for delivering results clearly and effectively.

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

1 is a block diagram schematically illustrating a system to which a data visualization type recommendation method using meta information according to an embodiment of the present invention is applicable.
2 is a block diagram schematically illustrating a detailed configuration of a server for performing a data visualization type recommendation method using meta information according to an embodiment of the present invention.
3 is a flowchart schematically illustrating a data visualization type recommendation method using meta information according to an embodiment of the present invention.
4A through 4J are views schematically showing a data visualization type applicable to a method of recommending a data visualization type using meta information according to an embodiment of the present invention.
5 is a block diagram schematically showing a detailed configuration of a user terminal performing a data visualization type recommendation method using meta information according to an embodiment of the present invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS The advantages and features of the present invention and the manner of achieving them will become apparent with reference to the embodiments described in detail below with reference to the accompanying drawings. However, it is to be understood that the present invention is not limited to the disclosed embodiments, but may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. It is to be understood by those of ordinary skill in the art that the present invention is not limited to the above embodiments, but may be modified in various ways. Like reference numerals refer to like elements throughout the specification.

Unless defined otherwise, all terms (including technical and scientific terms) used herein may be used in a sense commonly understood by one of ordinary skill in the art to which this invention belongs. In addition, commonly used predefined terms are not ideally or excessively interpreted unless explicitly defined otherwise.

The terminology used herein is for the purpose of illustrating embodiments and is not intended to be limiting of the present invention. In the present specification, the singular form includes plural forms unless otherwise specified in the specification. The terms " comprises "and / or" comprising "used in the specification do not exclude the presence or addition of one or more other elements in addition to the stated element.

1 is a block diagram schematically illustrating a system to which a data visualization type recommendation method using meta information according to an embodiment of the present invention is applicable.

Referring to FIG. 1, a system 1000 includes a data visualization type recommendation service server 100 and a user terminal 200.

The data visualization type recommendation service server 100 and the user terminal 200 are connected to each other via a network. Although only one user terminal 200 is shown in FIG. 1, a plurality of user terminals 200 may be connected to the data visualization type recommendation service server 100. The data visualization type recommendation service server 100 and the user terminal 200 can exchange various data and / or information with each other. The network includes a wired or wireless network. A wireless network includes wireless networks of various communication types such as mobile communication, WiBro, short range communication, sound wave communication, optical communication, radio communication, satellite communication and the like.

The data visualization type recommendation service server 100 provides a data visualization type recommendation service to the user. The data visualization type recommendation service server 100 receives the source data from the user, generates meta information defining the characteristics thereof, and recommends an appropriate data visualization type using meta information and matching rules of the source data.

The user terminal 200 represents a computer system used by a user. For example, the user terminal 200 may be provided as a mobile computer system such as a smart phone, a tablet, a PDA (Personal Digital Assistant) and the like. However, the present invention is not limited thereto, and the user terminal 200 may be provided as another type of computer system such as a desktop, a laptop, or the like.

In order to perform the data visualization type recommendation method using the meta information according to the embodiment of the present invention, when the user terminal 200 transmits specific information to the data visualization type recommendation service server 100 or when the user terminal 200 transmits data A software module (for example, an application or the like) may be provided for receiving specific information from the visualization type recommendation service server 100 and notifying the user of the information, and the user terminal 200 may transmit the software module to an external server And can be performed.

2 is a block diagram schematically illustrating a detailed configuration of a server for performing a data visualization type recommendation method using meta information according to an embodiment of the present invention.

2, the server 100 includes a communication unit 110, an input unit 120, an output unit 130, a storage unit 140, a visualization type meta information database 150, a matching rule database 160, A power supply unit 170, and a power supply unit 180.

The communication unit 110 can communicate with an external device (or a server or the like) by wire or wirelessly. The communication unit 110 may transmit data and / or information received from the external device to the control unit 170 and may transmit the data and / or information transmitted from the control unit 170 to the external device.

The input unit 120 receives various information from the server operator. The input unit 120 may include input means such as a keypad, a button, a switch, a touch pad, and a jog wheel.

The output unit 130 notifies the server operator of various information. The output unit 130 may output information in the form of a text, an image, or a voice. To this end, the output unit 130 may include a display module 131 and a speaker module 132. The display module 131 may be a plasma display panel (PDP), a liquid crystal display (LCD), a thin film transistor (TFT) LCD, an organic light emitting diode (OLED), a flexible display, May be provided in any form well known in the art. The output unit 130 may further comprise any type of output means well known in the art.

The storage unit 140 stores various data and commands. The storage unit 140 may store system software and various applications for the operation of the server 100. The storage unit 140 may be a storage unit such as a RAM (Random Access Memory), a ROM (Read Only Memory), an EPROM (Erasable-Programmable ROM), an EEPROM (Electrically EPROM), a flash memory, a hard disk, a removable disk, Lt; RTI ID = 0.0 > computer-readable < / RTI >

The visualization type meta information database 150 and the matching rule database 160 store various information for data visualization type recommendation. The visualization type meta information database 150 stores meta information defining properties of a plurality of visualization types. The matching rule database 160 stores a matching rule between the source data and the visualization type. The visualization type meta information database 150 and the matching rule database 160 can provide data management such as retrieving and accessing stored information, adding / changing / deleting information. The plurality of databases 160, 170 may include flash memory, a hard disk, a removable disk, or any form of computer readable recording medium known in the art.

The control unit 170 controls other components to control the overall operation of the server 100. [ The control unit 170 can execute the system software stored in the storage unit 140 and various applications.

The control unit 170 includes a source data meta generation module 171, a visualization type meta generation module 172, a visualization type recommendation module 173, a visualization module 174, And a rule management module 175. Each module may comprise a hardware module, a software module, or a combination thereof. The source data meta-generating module 171 may analyze the source data received from the user and generate meta information defining the characteristics (or attributes) of the source data. The visualization type meta-generating module 172 may analyze a plurality of data visualization types, generate meta information defining characteristics of each data visualization type, and store the meta information in the visualization type meta information database 150. [ The visualization type recommendation module 173 may recommend a data visualization type suitable for the source data for visualizing and representing the source data. The visualization type recommendation module 173 may each calculate a recommendation index of a plurality of data visualization types for the source data, and use the result of the calculation to recommend an appropriate data visualization type. The visualization module 174 can visualize and represent the source data according to the data visualization type selected by the user. The matching rule management module 175 generates a matching rule for data visualization type recommendation and updates a matching rule according to a user's behavior pattern using a probability-based machine learning (Machine Algorithm) model or adds a new matching rule to match Rules can be managed.

The power supply unit 180 includes a communication unit 110, an input unit 120, an output unit 130, a storage unit 140, a visualization type meta information database 150, a matching rule database 160, To the power supply. The power supply unit 180 is supplied with power from the outside, and can supply the power to the internal components appropriately converted into the server 100.

Although not explicitly shown, the server 100 may further include components not shown in FIG. 2, or may not include some components shown in FIG. 2, some of the components may be separated into a plurality of detailed components, or a plurality of components may be provided by being combined into one component.

1, the data visualization type recommendation service server 100 may be provided separately from a plurality of servers physically, spatially or functionally separated. In this case, each server may or may not include some of the components shown in FIG.

3 is a flowchart schematically illustrating a data visualization type recommendation method using meta information according to an embodiment of the present invention. Referring to FIG. 3, a description will be made of a case where a method of recommending a data visualization type using meta information is performed by the server 100 according to an embodiment of the present invention.

Referring to FIG. 3, in step S310, the server 100 generates meta information defining characteristics of a plurality of data visualization types. Here, the meta information of the data visualization type may include a name, an applicable domain, an input property, and an output property. A domain may be about sectors that require data visualization, such as stocks, bios, and commercials. Whether or not a keyword related to a specific field is found in the meta information of the source data can be considered in a recommendation step described later. The input characteristics may include information related to the input, such as the size of the input data, the type of data that can be input or the type of the field. The output characteristics may include information related to the output such as the basic visualization type, the expressible range (numerical value or value), whether or not it includes the interactive element, the presentation characteristic (time series, comparison, summary, relation, map, etc.).

Subsequently, in step S320, the server 100 generates a matching rule between the source data and the data visualization type.

Subsequently, in step S330, the server 100 receives the source data from the user terminal 200. [

Subsequently, in step S340, the server 100 generates meta information defining the characteristics of the source data. Here, the meta information of the source data may include a size of data (for example, a size of a row and a column, a total number of cells, etc.), a number of fields, and characteristics of each field. A field is an item of data, and may include a specific kind of data. The characteristics of a field may include various types of information such as a field type, a statistical characteristic, a structural characteristic, and an analysis technique. For example, the field type may include, but is not limited to, a numerical type, a categorical type, a time series type, a coordinate type, a text type, and the like. The field type may be further subdivided by a plurality of subtypes. For example, numeric types can be delimited into integer or decimal types. In order to determine the field type, the type of data of each cell can be identified, and the type of the plurality of data belonging to one field can be determined as the type of the field. However, the present invention is not limited to this, and various methods such as referencing the field type provided in the database of the source data, determining whether the value of the data is converted into a numerical value, May be used to determine the field type. Depending on the characteristics of the data, an arbitrary field may have a plurality of field types. Statistical properties may include total, mean, median, maximum, minimum, standard deviation, ratio, number, and so on. Depending on the field type, any field may or may not have some statistical properties. Statistical properties associated with a plurality of field types may be provided. The data structure may relate to which fields are associated with other fields, or which fields have a hierarchical structure, and so on. In the case of the time series type, it may further include meta information about units, periods, periods, and the like.

Then, in step S350, the server 100 recommends a data visualization type that best suits the source data for visualizing and representing the source data. At this time, the server 100 recommends one or more types of data visualization based on meta information of the source data, meta information of a plurality of data visualization types, and a matching rule. The server 100 may each calculate a recommendation index of a plurality of data visualization types. For example, the recommendation index may be calculated based on, but not limited to, whether the field type of the source data matches the inputtable data type of each data visualization type, how many matching fields are, and the like. Then, the server 100 can recommend a data visualization type having a maximum recommendation index among a plurality of data visualization types. Alternatively, the server 100 may recommend a data visualization type having a recommendation index that is greater than or equal to a reference value among a plurality of data visualization types.

Then, in step S360, the server 100 receives a selection of one or more data visualization types from the user. The user may select any one or more data visualization types of data visualization types recommended by the server 100, or may select any one or more data visualization types of data visualization types not recommended by the server 100.

Subsequently, in step S370, the server 100 visualizes and expresses the source data according to the data visualization type selected by the user. The data visualization representation may be provided to the user terminal 200. At this time, the data visualization representation may include an interactive element (e.g., clickable or zoomable, etc.).

Subsequently, in step S380, the server 100 updates the matching rule or adds a new matching rule based on the selection of the meta information of the source data and the data visualization type of the user. If the user selects any data visualization type from among the data visualization types recommended by the server 100, the server 100 may update the matching rules. If the user selects any of the data visualization types that are not recommended by the server 100, the server 100 may add a new matching rule.

Although not explicitly shown, in the data visualization type recommendation method using meta information according to the embodiment of the present invention, some steps may be performed in a different order from the illustrated order, or, Step < / RTI > Alternatively, in the method, as shown in FIG. 3, some steps may be modified so that they are omitted.

4A through 4J are views schematically showing a data visualization type applicable to a method of recommending a data visualization type using meta information according to an embodiment of the present invention.

FIG. 4A is an Area Chart, FIG. 4B is a bar chart, FIG. 4C is a Bublle Chart, FIG. 4D is a Candlestick Chart, FIG. 4E is a Combo Chart, FIG. 4F shows a Geo Chart, FIG. 4G shows a histogram chart, FIG. 4H shows a line chart, FIG. 4I shows a Pie Chart and FIG. 4J shows a scatter chart Respectively.

The types of data visualization depicted in Figures 4A-4J are illustrative and data visualization type recommendation methods using meta information in accordance with embodiments of the present invention may be applied substantially the same to various other data visualization types not illustrated Those skilled in the art to which the present invention belongs, those skilled in the art will understand.

3, a method of recommending a data visualization type using meta information according to an embodiment of the present invention may be performed by the user terminal 200. [ In this case, the data visualization type recommendation method using the meta information according to the embodiment of the present invention is implemented as a software module (for example, application), and the control unit 280 of the user terminal 200 can do.

5 is a block diagram schematically showing a detailed configuration of a user terminal performing a data visualization type recommendation method using meta information according to an embodiment of the present invention.

5, an exemplary user terminal 200 includes a wireless communication unit 210, an A / V input unit 220, a user input unit 230, a sensing unit 240, an output unit 250, a storage unit 260, an interface unit 270, a control unit 280, and a power supply unit 290.

The wireless communication unit 210 may wirelessly communicate with an external device (or server). The wireless communication unit 210 may communicate with an external device using a wireless communication method such as mobile communication, WiBro, Bluetooth, WiFi, Zigbee, ultrasonic, infrared, Wireless communication is possible. However, the wireless communication method of the user terminal 200 is not limited to the specific embodiment. The wireless communication unit 210 may transmit data and / or information received from the external device to the control unit 280 and may transmit the data and / or information transmitted from the control unit 280 to the external device. For this, the wireless communication unit 210 may include a mobile communication module 211 and a short-range communication module 212.

In addition, the wireless communication unit 210 may acquire the location information of the user terminal 200 by including the location information module 213. The location information of the user terminal 200 may be provided from, for example, a GPS positioning system, a WiFi positioning system, a cellular positioning system or a beacon positioning system, but the present invention is not limited thereto, The location information may be provided from the positioning systems of the mobile terminal. The wireless communication unit 210 may transmit the position information received from the positioning system to the control unit 280. [

The A / V input unit 220 is for inputting video or audio signals, and may include a camera module 221 and a microphone module 222.

The user input unit 230 receives various information from the user. The user input unit 230 may include input means such as a keypad, a button, a switch, a touch pad, and a jog wheel. When the touch pad has a mutual layer structure with a display module 251 described later, a touch screen can be configured.

The sensing unit 240 senses the state of the user terminal 200 or the state of the user. The sensing unit 240 may include sensing means such as a touch sensor, a proximity sensor, a pressure sensor, a vibration sensor, a geomagnetic sensor, a gyro sensor, a velocity sensor, an acceleration sensor, and a biometric sensor. The sensing unit 240 may be used for user input.

The output unit 250 notifies the user of various information. The output unit 250 may output information in the form of a text, an image, or a voice. To this end, the output unit 250 may include a display module 251 and a speaker module 252. The display module 251 may be a plasma display panel (PDP), a liquid crystal display (LCD), a thin film transistor (TFT) LCD, an organic light emitting diode (OLED), a flexible display, May be provided in any form well known in the art. The output unit 250 may further comprise any type of output means well known in the art.

The storage unit 260 stores various data and commands. The storage unit 260 may store system software and various applications for the operation of the user terminal 200. The storage unit 260 may be a storage unit such as a RAM (Random Access Memory), a ROM (Read Only Memory), an EPROM (Erasable-Programmable ROM), an EEPROM (Electrically EPROM), a flash memory, a hard disk, a removable disk, Lt; RTI ID = 0.0 > computer-readable < / RTI >

The interface unit 270 serves as a channel with an external device connected to the user terminal 200. The interface unit 270 receives data and / or information from an external device or receives power and transmits the received data and / or information to the internal components of the user terminal 200, Or supply internal power. The interface unit 270 may include, for example, a wired / wireless headset port, a charging port, a wired / wireless data port, a memory card port, a universal serial bus An audio input / output port, a video input / output (I / O) port, and the like.

The control unit 280 controls other components to control the overall operation of the user terminal 200. The control unit 280 can execute the system software stored in the storage unit 260 and various applications.

The power supply unit 290 includes a wireless communication unit 210, an A / V input unit 220, a user input unit 230, a sensing unit 240, an output unit 250, a storage unit 260, an interface unit 270, And supplies power necessary for the operation of the control unit 280. [ The power supply unit 290 may include an internal battery.

Although not explicitly shown, the user terminal 200 may further include components not shown in Fig. 5, or may not include some components shown in Fig. 5, some of the components may be separated into a plurality of detailed components, or a plurality of components may be provided by being combined into one component.

According to the data visualization type recommendation method using meta information according to the embodiment of the present invention described above with reference to FIG. 1 to FIG. 5, meta information for receiving the source data and defining its characteristics is generated, By recommending an appropriate type of data visualization using information and matching rules, a data visualization type suitable for delivering the analysis results of the source data clearly and effectively according to the characteristics of the source data can be recommended.

The methods described in connection with the embodiments of the present invention may be implemented with software modules executed by a processor. The software modules may reside in RAM, ROM, EPROM, EEPROM, flash memory, hard disk, removable disk, CD-ROM, or any form of computer readable recording medium known in the art .

While the present invention has been described in connection with what is presently considered to be practical exemplary embodiments, it is to be understood that the invention is not limited to the disclosed embodiments, but, on the contrary, It will be understood. Therefore, it should be understood that the above-described embodiments are illustrative in all aspects and not restrictive.

100: Data visualization type recommendation service server
200: User terminal

Claims (10)

A method performed by a computer system,
Receiving source data;
Generating meta information of the source data defining characteristics of the source data; And
And recommending one or more types of data visualization for visualizing and representing the source data based on meta information of the source data and a matching rule,
Wherein the meta information of the source data includes at least one of a name, a domain, an input property, and an output property,
Wherein the recommending of the visualization type comprises recommending whether or not a keyword related to a specific field is found in the meta information of the source data,
Recommendation method of data visualization type using meta information. The method according to claim 1,
Wherein the meta information of the source data includes at least one of a size of data, a number of fields, or characteristics of each field. The method according to claim 1,
Receiving a selection from the user for one or more of the data visualization types of the recommended data visualization type; And
Further comprising visualizing and representing the source data according to the selected data visualization type. The method of claim 3,
Wherein the data visualization representation comprises an interactive element. The method according to claim 1,
Further comprising generating meta information each defining characteristics of a plurality of data visualization types,
The method of claim 1, wherein recommending one or more data visualization types for visualizing and representing the source data comprises: comparing meta information of the source data, meta information of the plurality of data visualization types, and meta information of the source data with the plurality of data visualizations And recommends one or more data visualization types for visualizing and representing the source data based on a matching rule between the meta information of the type. 6. The method of claim 5,
Wherein recommending one or more data visualization types for visualizing and representing the source data comprises: calculating a recommendation index for each of the plurality of data visualization types, and generating a data visualization type having a maximum recommendation exponent of the plurality of data visualization types A method of recommending a data visualization type using meta information that is recommended as a data visualization type for visualizing and representing the source data. 6. The method of claim 5,
Wherein the recommending of one or more data visualization types for visualizing and representing the source data comprises: calculating each of the plurality of data visualization type recommendation indices for each of a plurality of data visualization types, And recommending the type as a data visualization type for visualizing and representing the source data. delete The method according to claim 1,
Receiving a selection from the user for one or more of the data visualization types of the recommended data visualization type; And
Further comprising updating the matching rule based on the meta information of the source data and the selection of the user's data visualization type. The method according to claim 1,
Receiving a selection for one or more data visualization types of a data visualization type that is not recommended from a user; And
Further comprising adding a new matching rule based on the selection of the source data meta information and the user ' s data visualization type.
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