KR102269207B1 - Method for data analytics visualization and apparatus thereof based on high speed communication - Google Patents

Abstract

A data visualization method and apparatus are provided. The data visualization method according to some embodiments of the present disclosure is a method performed by a computing device, comprising: obtaining network data composed of a node and an edge connecting the nodes; obtaining user interest information of a first user; , generating VR data in which the network data is visualized; generating custom VR data of the first user by adjusting the VR data by reflecting the user interest information of the first user; It may include transmitting the custom VR data of the first user to the terminal of the first user.

Description

Data analysis visualization method and apparatus based on high-speed communication {METHOD FOR DATA ANALYTICS VISUALIZATION AND APPARATUS THEREOF BASED ON HIGH SPEED COMMUNICATION}

The present disclosure relates to a data analysis visualization method and apparatus in a high-speed communication environment such as 5G. In more detail, by visualizing the network data and reflecting the user's interest information in the visualized VR data, the network data can be visualized according to the user's interest, thereby providing a vast amount of big data simply. It relates to a data visualization method and apparatus for realizing possible telepresence.

Telepresence is a technology that allows users to experience virtual reality (VR) together and conduct a meeting. Data or shapes to be presented can be visualized to the user through a head mounted display (HMD) equipped with a display. have. In order to implement telepresence, an infrastructure capable of effectively transmitting and receiving multimedia data is essential, and it can be effectively implemented under high-speed data communication such as the 5G environment that has recently been commercialized. That is, such high-speed data communication can ensure a QoS-guaranteed network capable of transmitting and receiving large-capacity multimedia traffic, and an optimal network environment to maintain security for a long meeting time and implement a seamless communication environment. In particular, telepresence is relatively safe from external hacking and various information security threats, and provides a natural communication space with immediacy and efficiency between people who are far away. Therefore, telepresence is expected to be able to broaden its application to not only businesses, but also education, medical care, public service, shopping, and entertainment, while increasing intimacy and simultaneity, which were the major limitations of online dating.

Such telepresence provides realistic multimedia, and in order to perform in-depth analysis through massive data, it is necessary to provide massive data such as big data. However, the conventional telepresence does not efficiently recognize the vast amount of data to the meeting attendees because it merely organizes or provides it even if it provides a large amount of data, but rather confuses the participants. In addition, no matter how advanced communication technology such as 5G is, in a communication state that is not completely settled, simply organizing or providing massive data often causes a delay in VR data visualization in a telepresence environment.

In addition, when the number of nodes increases, the connected edges (or links) are overlapped, making it difficult to distinguish the VR data in which the conventional network data is visualized. In addition, detailed edges can be checked through the zoom function, but complex data can be processed at once. As it was expressed, there was a problem in that it was difficult to identify an edge in a macroscopic dimension.

In order to overcome the problems of the conventional telepresence environment, a method capable of simply expressing network data is required, and in order to express network data simply, network data reflecting the user's interest is visualized and provided, and the visualized network There is a need for a technology capable of efficiently using data used for telepresence by modifying data by a user, and making data simpler by modifying data by a user participating in telepresence.

Registered Patent Publication No. 10-1659849 "Method for providing telepresence using avatar, system for performing the method, and computer-readable recording medium" (published on July 19, 2016)

A technical problem to be solved through some embodiments of the present disclosure is to provide a data visualization method and apparatus capable of simply expressing complex and vast network data in telepresence implemented through a high-speed communication environment such as 5G. have.

The technical problem to be solved through some embodiments of the present disclosure is to easily perform analysis, clustering, etc. of information as a vast amount of data is simply acquired, and thus a telepress that can easily broaden the field of view or insight for viewing information It can provide a battle environment.

Another technical problem to be solved through some embodiments of the present disclosure is to provide a data visualization method and apparatus capable of visualizing network data reflecting a user's interest in order to simply express network data.

Another technical problem to be solved through some embodiments of the present disclosure is to provide a data visualization method and an apparatus for enabling a user participating in telepresence to edit visualized network data while attending a conference.

Another technical problem to be solved through some embodiments of the present disclosure is data visualization that can be refined or completed into network data with improved quality by efficiently correcting incomplete network data or network data lacking information through collaboration. A method and an apparatus can be provided.

The technical problems of the present disclosure are not limited to the technical problems mentioned above, and other technical problems not mentioned will be clearly understood by those skilled in the art from the following description.

In order to solve the above technical problem, the data visualization method according to some embodiments of the present disclosure is a method performed by a computing device, the step of obtaining network data consisting of a node and an edge connecting between the nodes, a first Obtaining user interest information of the user, generating VR data in which the network data is visualized, and adjusting the VR data to reflect the user interest information of the first user, thereby providing a custom VR of the first user It may include generating data and transmitting the custom VR data of the first user to the terminal of the first user.

In order to solve the above technical problem, a data visualization method according to another embodiment of the present disclosure includes obtaining user interest information of a second user, and comparing user interest information of the first user with user interest information of the second user. to analyze whether the interest information is similar, and if the interest information is similar, matching the first user and the second user as a first group, and generating custom VR data of the first user. The step may include generating collaborative VR data for visualizing the same custom VR data on terminals of the first user and the second user.

In order to solve the technical problem, the data visualization method according to another embodiment of the present disclosure includes a processor, a network interface, a memory, and a computer program loaded into the memory and executed by the processor, The computer program includes an instruction to obtain network data composed of a node and an edge connecting between the nodes, an instruction to obtain user interest information of the first user, and VR data in which the network data is visualized. An instruction for generating the custom VR data of the first user by adjusting the VR data by reflecting the user interest information of the first user, and the custom VR data of the first user are transmitted to the terminal of the first user It may contain instructions to

In order to solve the above technical problem, a data visualization method according to another embodiment of the present disclosure is coupled with a computing device, obtaining network data consisting of a node and an edge connecting between the nodes, the user interest of the first user Obtaining information, generating VR data in which the network data is visualized, and adjusting the VR data to reflect the user interest information of the first user, thereby generating custom VR data of the first user and transmitting the custom VR data of the first user to the terminal of the first user may be stored in a computer-readable recording medium.

1 is a configuration diagram for explaining a data visualization system according to some embodiments of the present disclosure.
2 is a flowchart illustrating a data visualization method according to some embodiments of the present disclosure.
FIG. 3 is a flowchart for describing in detail some configurations of FIG. 2 .
4 is a flowchart for explaining an example of a partial configuration of FIG. 2 .
5 is an example for explaining custom VR data that is differently visualized according to a user's point of view.
6 is a flowchart for explaining another example of a partial configuration of FIG. 2 .
7A to 7D are exemplary views for explaining custom VR data that is differently visualized according to user interest information.
8 is an exemplary diagram for explaining a data visualization method according to another embodiment of the present disclosure.
9 is an exemplary diagram for explaining collaborative VR data in which network data is modified.
10 is a hardware configuration diagram of a data visualization server according to another embodiment of the present disclosure.

Hereinafter, preferred embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. Advantages and features of the present disclosure, and methods for achieving them, will become apparent with reference to the embodiments described below in detail in conjunction with the accompanying drawings. However, the technical spirit of the present disclosure is not limited to the following embodiments, but may be implemented in various different forms, and only the following embodiments complete the technical spirit of the present disclosure, and in the technical field to which the present disclosure belongs It is provided to fully inform those of ordinary skill in the scope of the present disclosure, and the technical spirit of the present disclosure is only defined by the scope of the claims.

In adding reference numerals to the components of each drawing, it should be noted that the same components are given the same reference numerals as much as possible even though they are indicated on different drawings. In addition, in describing the present disclosure, if it is determined that a detailed description of a related known configuration or function may obscure the gist of the present disclosure, the detailed description thereof will be omitted.

Unless otherwise defined, all terms (including technical and scientific terms) used herein may be used with the meaning commonly understood by those of ordinary skill in the art to which this disclosure belongs. In addition, terms defined in a commonly used dictionary are not to be interpreted ideally or excessively unless clearly defined in particular. The terminology used herein is for the purpose of describing the embodiments and is not intended to limit the present disclosure. As used herein, the singular also includes the plural unless specifically stated otherwise in the phrase.

In addition, in describing the components of the present disclosure, terms such as first, second, A, B, (a), (b), etc. may be used. These terms are only for distinguishing the components from other components, and the essence, order, or order of the components are not limited by the terms. When a component is described as being “connected”, “coupled” or “connected” to another component, the component may be directly connected or connected to the other component, but another component is between each component. It should be understood that elements may be “connected,” “coupled,” or “connected.”

As used herein, “comprises” and/or “comprising” refers to a referenced component, step, operation and/or element of one or more other components, steps, operations and/or elements. The presence or addition is not excluded.

Hereinafter, some embodiments of the present disclosure will be described in detail with reference to the accompanying drawings.

1 is a configuration diagram illustrating a data visualization system according to some embodiments of the present disclosure, and FIG. 2 is a flowchart illustrating a data visualization method according to some embodiments of the present disclosure.

Referring to FIG. 1 , a data visualization system according to some embodiments of the present disclosure may include a data visualization server 100 and user terminals 1 to 3 . Here, the data is information analysis data implemented in virtual reality (VR) images in telepresence, and may consist of reports, statistical data, graphs, diagrams, etc. including nodes and edges (or links), but these data is not limited to, and may consist of various visual and non-visual data that can be visualized as VR images in a telepresence environment.

The data visualization server 100 may acquire network data and generate VR data visually visualized in the user's terminals 1 to 3 by using the network data. When the network data is large, that is, when the number of nodes and edges belonging to the network is large, when the network is visualized in two dimensions, it is difficult to identify a connection relationship. When the network data is more massive, this difficulty cannot be solved even if the network is visualized in a three-dimensional space. On the other hand, when the network is visualized in the form of VR data, it is easy to check the network connection relationship in the virtual space even if the network data is huge.

VR data may refer to VR streaming data for providing video and audio, such as when users participating in telepresence in a virtual space experience an actual meeting. VR data includes analysis of specific nodes, links, or clustered groups in the 3D stereoscopic network analysis map implemented in the virtual space after the user's avatar is created in the virtual space, analysis of the given properties of detailed nodes or links, And it may be information that can be confirmed the original information of the literature linked thereto.

The data visualization server 100 may obtain the user's interest information from the user terminal connected to the network, generate custom VR data corresponding to the user's interest information, and transmit it to the user's terminals 1 to 3 . The user interest information is information indicating which data the user will check, and the details will be described later. In addition, the custom VR data is data adjusted according to the user's interest information, and will be described later along with the description of the interest information.

The user's terminals 1 to 3 are devices for visualizing VR data, and may be configured as a head mounted display (HMD), but is not limited thereto, and may include various display devices that can visualize VR data in a telepresence environment. can be implemented.

The data visualization system according to some embodiments of the present disclosure adjusts complex and vast VR data visualized in telepresence using the user's interest information, so that the user wants to view or experience the complex expressed data. It can be expressed simply based on the data.

In addition, the data visualization system according to some embodiments of the present disclosure provides a telepresence environment in which information analysis, clustering, etc. can be easily performed and thus a view of viewing information can be easily broadened by simply providing a large amount of data. can provide

The data visualization system according to some embodiments of the present disclosure provides a telepresence environment in which anyone can participate without user restrictions in a high-speed communication environment such as a 5G platform environment, and information analysis results (network graph, 3D axis graph, etc.) You can analyze information from multiple angles by looking at the data from multiple perspectives and accessing and confirming the original text (thesis, patent, report, etc.) related to the result.

Referring to FIG. 2 , the data visualization method according to the present disclosure may be performed by the data visualization server 100 , and in step S110 , network data composed of a node and an edge connecting between the nodes may be obtained. The network data may be input to the server or may be input by being connected to an external device through a wired/wireless network, and the input method is not limited.

In step S120, user interest information of the first user may be obtained. Information of interest may include various information such as statistics, genetics, data analysis, sports, psychology, mathematics, etc., and may be input in an unlimited number, not corresponding to a single number. Even if such interest information is not separately input, it may be automatically analyzed through the user's profile. For example, interest information may be automatically obtained through natural language processing by parsing the input information when the user's resume, career, and academic background are input. Also, interest information may not be limited to a name such as interest or preference.

Thereafter, in step S130 , VR data in which network data is visualized may be generated. It may be encoded in a format rendered to the user's terminal 1 using network data in step S130. The VR data generation method may generate VR data as it is encoded in various ways that can be transmitted to a user's terminal through high-speed communication such as 5G, but is not limited thereto.

In step S140 , the custom VR data 11 of the first user may be generated by adjusting the VR data to reflect the user interest information of the first user. The VR data generated in step S140 may reflect user interest information. In an embodiment, user interest information may be reflected in VR data in various ways, such as the direction in which the generated VR data is visualized, the type of data to be emphasized, the type of unnecessary data to be removed, etc. to be described later.

In step S150 , the custom VR data of the first user may be transmitted to the terminal 1 of the first user. Thereafter, although not shown, custom VR data is rendered in the terminal 1 of the first user, and the first user using the terminal 1 of the first user is customized for the field of interest of the first user in the telepresence environment. VR data can be viewed.

The data visualization method according to the present disclosure can provide a telepresence environment capable of easily performing information analysis, clustering, and the like, and broadening insight into information by simply providing vast amounts of data.

FIG. 3 is a flowchart for describing in detail some configurations of FIG. 2 .

Referring to FIG. 3 , when obtaining the user interest information of the first user in step S120 , the user's interest information may be obtained from the user by providing the classification list in which the network data is automatically clustered to the user's terminal 1 .

In an embodiment, the field of interest may be classified by clustering information included in the network data according to step S1201. Network data is composed of nodes and edges, and nodes are composed of data structures such as structures or classes, and various information can be included in the nodes. In an embodiment, nodes and edges of network data may include various types of information such as text with information, vectors, indexes, and sources of papers. In step S1201, the similarity between each node may be analyzed and clustered based on the text or vector of each node, the distance of the edge, and a weight assigned to the edge. In this case, clustering may be performed using a preset algorithm, and as network data is input, clustering may be performed using an algorithm learned through machine learning, but is not limited thereto.

In step S1203, the clustered classification may be listed and provided to the user's terminal 1 . In step S1205, the classifications listed on the user's terminal 1 may be selected by the user, and the list may be provided by running the telepresence app or the web on the user's terminal 1, but these It is not limited to the selection method, and may be selected by various operations that may be selected by the user terminal.

In another embodiment, instead of obtaining the user's interest information as performed in steps S1201 to S1203, the interest information may be automatically selected through the user's interest information obtained from the user's profile. Specifically, before step S1201 is performed, the user's profile may be obtained from the user's terminal 1 connected to the network. The obtained profile may include interest information indicating a field desired by the user, that is, an area of interest.

Thereafter, as in step S1201, information included in network data is clustered to classify text fields. Thereafter, instead of performing steps S1203 and S1205, a field closest to the interest information according to the user's profile may be automatically selected through a similarity analysis between the clustered field and the interest information obtained from the user's profile. According to the present embodiment, there is an advantage in that the user can automatically and clearly view data on a desired field when participating in telepresence even if he/she does not particularly input interest information.

4 is a flowchart for explaining an example of a partial configuration of FIG. 2 , and FIG. 5 is an example for explaining the custom VR data 11 that is differently visualized according to a user's point of view.

Referring to FIG. 4 , when the custom VR data 11 of the first user is generated in step S140 of FIG. 2 , steps S1401 to S1403 may be performed. A viewpoint at which a node and an edge for the information of interest are visible on the VR data visualized in step S1401 may be determined. The point of view is a point of view for looking at an area of interest when viewing a network rendered in a user's terminal, and may be a direction in which VR data is visualized in a direction that is not covered or obscured by other nodes, edges, or text. In operation S1403, the rendering direction of the visualized VR data may be adjusted according to the viewpoint.

Meanwhile, in another embodiment, the point of view may be freely changed by the user's manual setting, and accordingly, the user may adjust the point of view by toggling or switching the interface formed in the user terminal to view VR data at a desired location. .

After that, in another embodiment, step S1405 is further performed, so that the viewpoint of the custom VR data 11 can be maintained even when the gaze direction of the user's terminal 1 is changed according to the movement of the user's terminal 1 . .

Referring to FIG. 5 , the data visualization server 100 generates custom VR data using the user interest information of first to third users, and uses the generated custom VR data to the terminals 1 to 3 of the first to third users. 3) can be sent.

The terminals 1 to 3 of the first to third users may receive the custom VR data 11 corresponding to their point of view from the data visualization server 100 , respectively. Accordingly, the terminal 1 of the first user may view the VR data as if it were looking at the VR data from a viewpoint in a direction located according to the interest information of the terminal 1 of the first user. Since the first user's terminal 1 looks at the VR data from the viewpoint, it is possible to experience the telepresence environment in a direction where nodes, edges, and text information in the field of interest are most clearly visible and easily recognized. Similarly, the second user's terminal 2 can view the VR data as if looking at the VR data from a viewpoint in a direction located according to the interest information of the second user's terminal 2, and the third user's terminal 3 3 You can view the VR data as if you were looking at it from a viewpoint in a direction located according to the interest information of the user's terminal 3 .

Accordingly, the data visualization method according to the present disclosure provides a telepresence environment in which the user can efficiently use the data by providing VR data in a direction in which the user can easily check the field of interest in the network data. There are advantages.

6 is a flowchart for explaining another example of a partial configuration of FIG. 2 .

Referring to FIG. 6 , in the step of generating the custom VR data 11 of the first user in step S140 of FIG. 2 , steps S1407 and S1409 may be performed instead of steps S1401 to S1405 being performed.

In operation S1407, information corresponding to interest information may be determined from network data. In operation S1407, a node, an edge, and a text determined to be similar to the interest information may be determined. Accordingly, the custom VR data 11 may be generated by adjusting the VR data based on the information corresponding to the interest information in step S1409 .

In one embodiment, the custom VR data 11 may be rendered such that the network data is visualized according to the user's interest information. VR data may be adjusted so that only information corresponding to interest information is visualized by excluding information not corresponding to interest information from network data. As an example, a node corresponding to interest information may be determined from network data, and custom VR data 11 composed of nodes corresponding to interest information may be generated. As another example, an edge corresponding to information of interest is determined from network data, and custom VR data 11 composed of an edge corresponding to information of interest may be generated.

In another embodiment, the VR data may be adjusted so that information corresponding to the interest information is determined from network data and information corresponding to the interest information is emphasized. In this case, a node or an edge corresponding to the information of interest may be emphasized. In this case, the node, edge, or text may be visually distinguished from other pieces of information by emphasizing it with a color, thickness, and movement motion.

In the conventional telepresence, when the number of nodes increases in a large amount of network data, the connected edges overlap and it is difficult to distinguish them. Also, detailed links can be checked through the zoom function, but while comparing other detailed link groups at a macro level, There was a disadvantage that it was impossible to identify a specific detailed link group. However, in the data visualization method according to the present disclosure, as the custom VR data 11 is rendered so that the network data is visualized according to the user's interest information, even if a large amount of network data is rendered in telepresence, the user can easily access all information. It has the advantage of being easily identifiable.

7A to 7D are exemplary diagrams for explaining the custom VR data 11 that is differently visualized according to the user's interest information.

7A to 7D , the illustrated graph may be custom VR data 11 generated according to various embodiments of the data visualization method described with reference to FIG. 6 .

In the custom VR data 11 shown in FIG. 7A , the user's interest information may be determined as an author map composed of authors of a thesis or report. At this time, the method according to the present disclosure generates VR data based on network data, and from the generated VR data, a node including text about an author and an edge where the relationship between authors is expressed by distance and weight according to the interest information Custom VR data 11 composed of can be generated.

The custom VR data 13 shown in FIG. 7B may be determined as an institution map comprising institutions from which the user's interest information obtained data. In this case, the method according to the present disclosure generates VR data based on network data, and from the generated VR data, a node containing text about an institution and a relationship between institutions according to the interest information are expressed by distance and weight. Custom VR data 13 composed of can be generated.

In the custom VR data 15 shown in FIG. 7C , the user's interest information may be determined as a thesis map including the name or type of the thesis. In this case, the method according to the present disclosure generates VR data based on network data, and from the generated VR data, a node including a text for a thesis and an edge where the relationship between the thesis is expressed by distance and weight according to the interest information Custom VR data 15 composed of can be generated.

In the custom VR data 17 shown in FIG. 7D , a method of arranging or expressing data in the user's interest information may be included to generate custom VR data 17 that meets the user's taste. At this time, although FIG. 7D illustrates a three-dimensional bar graph format as an example, the present invention is not limited thereto, and custom VR data 17 may be generated through various data expression methods.

8 is an exemplary diagram for explaining a data visualization method according to another embodiment of the present disclosure.

Referring to FIG. 8 , the data visualization server 100 according to another embodiment of the present disclosure may generate custom VR data 11 so that a user forms a group and views the same VR data in the group. The data visualization server 100 may obtain interest information of the first user and the second user. It is determined whether the obtained interest information is similar, and when it is determined that the interest information of the first user and the second user is similar, the first user and the second user may be matched to the first group (a). In addition, if the interest information of the third user and the fourth user is compared and it is determined that they are similar, the third user and the fourth user may be matched to the second group (b). In this case, the group may form one user into a group, and the number of people in the group is not limited.

The data visualization server 100 may generate collaborative VR data to transmit the same custom VR data 11 to the first group (a). Collaborative VR data may be data that provides the same screen between users in the same group, or data in which data is synchronized between users in the same group.

The data visualization method according to the present disclosure may be performed by the data visualization server 100, and in addition to the method described in FIG. 3 , obtaining user interest information of a second user, user interest information of the first user and the second user A step of analyzing whether the interest information is similar by comparing the user interest information, and a step of matching the first user and the second user into the first group (a) when the interest information is similar may be further performed. In step S140 of FIG. 3 , when the first user's custom VR data 11 is generated, collaborative VR data that visualizes the same custom VR data 11 on the terminal 1 of the first user and the second user is generated can be

The data visualization method according to the present disclosure provides the same screen to users who are interested in a similar field, so it is possible to more simply classify and provide vast data, and to facilitate information exchange, discussion, and collaboration among users. It can provide a battle environment.

9 is an exemplary diagram for explaining collaborative VR data in which network data is modified.

Referring to FIG. 9 , the custom VR data 11 transmitted to the user's terminal 1 may be modified by the matched group. Lengths and/or weights of edges displayed in bold such as m1 and m3 may be modified by the user's terminal 1 . Alternatively, the location, text, size, etc. of the node included in m2 may be modified by the user's terminal 1 . When the custom VR data 11 is modified by the group, these modifications and changes are received by the data visualization server 100 , and the data visualization server 100 may modify the network graph based on the changes. The data visualization server 100 may reflect the modified network data to the collaborative VR data.

In another embodiment, the data visualization method may provide collaborative VR data to the user's terminal 1 while simultaneously providing global VR data showing an overall view of network data in one area of the collaborative VR data. In this case, even if the user's terminal 1 toggles the location or direction size of the collaborative VR data, the global VR data may be rendered without overlapping (avoiding) the collaborative VR data.

In another embodiment, the global VR data may be VR data before correction or collaborative VR data in which a corrected state is reflected.

The data visualization method of the present disclosure has an effect that, as a user cooperates to modify network data, incomplete network data or network data lacking information can be efficiently corrected through collaboration to be refined or completed into network data with improved quality there is

In another embodiment, in the data visualization method, the modification of network data may be separately visualized in the terminals of the first user and the second user. In this case, the collaborative VR data shown to the first user may be converted into the collaborative VR data shown to the second user according to the request of the first user to mutually confirm the modifications between the first user and the second user. In another embodiment, messages and annotations on modifications made may be shared between the first user and the second user.

In the data visualization method, when the modified network data is reflected in the collaboration VR data, the time when the modified network data is reflected in the collaboration VR data may be different. In an embodiment, after the modification of the network data of the first user is finally completed, the modified network data may be reflected in the collaborative VR data visualized by the second user. In another embodiment, the modified graph network of the first user may be reflected in real time in the collaborative VR data visualized by the second user.

In the data visualization method, when the modified network data is reflected in the collaborative VR data, the modified information for each group may be reflected. In one embodiment, the modification of the second group (b) other than the first group (a) It may be blocked by the request of the first group (a) from being reflected in the collaborative VR data visualized by the user of the first group (a).

In another embodiment, the network data modified by the second group (b) other than the first group (a) may be reflected in the collaborative VR data of the first group (a) in real time.

In this case, by comparing the network data modified by the first group (a) and the second group (b), if the modifications conflict, a warning about the collision may be transmitted to the first and second groups (b).

The data visualization method according to the present disclosure has an advantage in that network data does not collide and collaboration can be effectively performed even when collaboration is performed simultaneously by the above-described configuration.

The methods according to the embodiments of the present invention described so far may be performed by executing a computer program embodied as computer readable code. The computer program may be transmitted from the first computing device to the second computing device through a network such as the Internet and installed in the second computing device, thereby being used in the second computing device. The first computing device and the second computing device include all of a server device, a physical server belonging to a server pool for a cloud service, and a stationary computing device such as a desktop PC.

The computer program may be stored in a recording medium such as a DVD-ROM or a flash memory device. Hereinafter, a hardware configuration of the data visualization server 100 according to another embodiment of the present invention will be described with reference to FIG. 10 .

10 is a hardware configuration diagram of the data visualization server 100 according to another embodiment of the present disclosure.

Referring to FIG. 10 , the data visualization server 100 according to another embodiment of the present invention includes one or more processors 110 , a graph network database 151 executed by the processor 110 , and a data visualization program 152 . It may include a memory 120 for loading (Load), a bus 130, a network interface 140, and a storage 150 for storing a graph network database 151 and a data visualization program 152. Here, only the components related to the embodiment of the present invention are shown in FIG. 10 . Accordingly, a person skilled in the art to which the present invention pertains can know that other general-purpose components other than the components shown in FIG. 10 may be further included.

The processor 110 controls the overall operation of each component of the data visualization server 100 . The processor 110 includes a central processing unit (CPU), a micro processor unit (MPU), a micro controller unit (MCU), a graphic processing unit (GPU), or any type of processor well known in the art. can be In addition, the processor 110 may perform an operation on at least one application or program for executing the method according to the embodiments of the present invention. Here, the data visualization server 100 illustrated in FIG. 10 is illustrated as including one processor 110 , but is not limited thereto and may include a plurality of processors.

The memory 120 stores various data, commands and/or information. The memory 120 may load the graph network database 151 and the data visualization program 152 from the storage 150 to execute the method/operation according to various embodiments of the present disclosure. When the graph network database 151 and the data visualization program 152 are loaded into the memory 120 , the processor 110 executes one or more instructions 121 and 122 constituting the data visualization program 152 to thereby load the graph. The data visualization method/operation of the application program can be performed using the network database. The memory 120 may be implemented as a volatile memory such as RAM, but the technical scope of the present invention is not limited thereto.

The bus 130 provides a communication function between components of the data visualization server 100 . The bus 130 may be implemented as various types of buses, such as an address bus, a data bus, and a control bus.

The network interface 140 supports wired/wireless Internet communication of the data visualization server 100 . In addition, the network interface 140 may support various communication methods other than Internet communication. To this end, the network interface 140 may be configured to include a communication module well known in the art. In some embodiments, the network interface 140 may be omitted.

The storage 150 may non-temporarily store the graph network database 151 and the data visualization program 152 . When an application program is executed and manipulated through the data visualization server 100 , the storage 150 may store various data for the application program executed according to the execution and manipulation. For example, the storage 150 may store information on the executed application program, operation information on the application program, and information on the user who requests the execution of the application program.

The storage 150 is a non-volatile memory such as a read only memory (ROM), an erasable programmable ROM (EPROM), an electrically erasable programmable ROM (EEPROM), a flash memory, a hard disk, a removable disk, or well in the art to which the present invention pertains. It may be configured to include any known computer-readable recording medium.

The data visualization program 152 may include one or more instructions 121 and 122 that, when loaded into the memory 120 , cause the processor 110 to perform methods/operations according to various embodiments of the present disclosure. That is, the processor 110 may perform the method/operation according to various embodiments of the present disclosure by executing the one or more instructions 121 and 122 .

In an embodiment, the data visualization program 152 includes an instruction for obtaining network data composed of a node and an edge connecting between nodes, an instruction for obtaining user interest information of the first user, and VR data in which the network data is visualized An instruction for generating the custom VR data 11 of the first user by adjusting the VR data to reflect the user interest information of the first user, and the custom VR data 11 of the first user to the first user It may include an instruction to transmit to the terminal (1) of.

So far, various embodiments of the present invention and effects according to the embodiments have been described with reference to FIGS. 1 to 10 . Effects according to the technical spirit of the present invention are not limited to the above-mentioned effects, and other effects not mentioned will be clearly understood by those skilled in the art from the following description.

Although the embodiments of the present invention have been described above with reference to the accompanying drawings, those of ordinary skill in the art to which the present invention pertains can realize that the present invention can be embodied in other specific forms without changing the technical spirit or essential features. can understand Therefore, it should be understood that the embodiments described above are illustrative in all respects and not restrictive.

Claims (20)

A method performed by a computing device, comprising:
obtaining network data consisting of a node and an edge connecting the nodes;
obtaining user interest information of the first user;
generating VR data in which the network data is visualized;
generating custom VR data of the first user by adjusting the VR data to reflect user interest information of the first user;
transmitting the custom VR data of the first user to the terminal of the first user;
obtaining user interest information of a second user;
analyzing whether the interest information is similar by comparing the user interest information of the first user with the user interest information of the second user; and
matching the first user and the second user as a first group when the interest information is similar
including,
The step of generating the custom VR data of the first user comprises:
generating collaborative VR data for visualizing the same custom VR data on terminals of the first user and the second user;
Data visualization methods. According to claim 1,
The step of obtaining user interest information of the first user includes:
classifying interest information by clustering information included in the network data;
providing a list of the classified interest information;
Including the step of selecting the interest information of the first user from the list,
Data visualization methods. According to claim 1,
The step of generating the custom VR data of the first user comprises:
determining a viewpoint at which a node and an edge for the interest information are visible on the visualized VR data; and
Comprising the step of adjusting the rendering direction of the VR data visualized according to the viewpoint,
Data visualization methods. 4. The method of claim 3,
Adjusting the rendering direction of the VR data visualized according to the viewpoint comprises:
Comprising the step of maintaining the viewpoint of the custom VR data even when the gaze direction of the terminal of the first user is changed according to the movement of the terminal of the first user,
Data visualization methods. According to claim 1,
The step of generating the custom VR data of the first user comprises:
determining information corresponding to the interest information from the network data;
and adjusting the VR data so that only information corresponding to the interest information is visualized by excluding information not corresponding to the interest information from the network data,
Data visualization methods. 6. The method of claim 5,
The step of adjusting the VR data so that only the information corresponding to the information of interest is visualized,
Determining a node corresponding to the interest information from the network data, and generating custom VR data composed of nodes corresponding to the interest information,
Data visualization methods. 6. The method of claim 5,
The step of adjusting the VR data so that only the information corresponding to the information of interest is visualized,
Determining an edge corresponding to the interest information in the network data, and generating custom VR data composed of an edge corresponding to the interest information,
Data visualization methods. According to claim 1,
The step of generating the custom VR data of the first user comprises:
determining information corresponding to the interest information from the network data;
including adjusting the VR data so that information corresponding to the information of interest is emphasized,
Data visualization methods. 9. The method of claim 8,
The step of adjusting the VR data so that only the information corresponding to the information of interest is visualized,
Including the step of emphasizing a node or edge corresponding to the information of interest,
Data visualization methods. delete According to claim 1,
The step of generating the collaborative VR data includes:
modifying the network data by a user included in the first group;
Including the step of reflecting the modified network data to the collaborative VR data,
Data visualization methods. 12. The method of claim 11,
The step of modifying the network data,
separately visualizing the modification of the network data to the first user and the second user; and
converting the collaborative VR data shown to the first user into the collaborative VR data shown to the second user according to the request of the first user to mutually confirm the modifications between the first user and the second user ,
Data visualization methods. 13. The method of claim 12,
The step of modifying the network data,
Including the step of sharing a message and an annotation on the matter to be modified between the first user and the second user,
Data visualization methods. 12. The method of claim 11,
The step of reflecting the modified network data to the collaborative VR data includes:
After the first user's modification of the network data is finally completed, reflecting the modified network data to the collaborative VR data visualized by the second user,
Data visualization methods. 12. The method of claim 11,
The step of reflecting the modified network data to the collaborative VR data includes:
Comprising the step of reflecting in real time the modified graph network of the first user to the collaborative VR data visualized by the second user,
Data visualization methods. 12. The method of claim 11,
The step of reflecting the modified network data to the collaborative VR data includes:
Blocking, at the request of the first group, that modifications of a second group other than the first group are reflected in collaborative VR data visualized by users of the first group,
Data visualization methods. 12. The method of claim 11,
The step of reflecting the modified network data to the collaborative VR data includes:
Including the step of reflecting in real time the network data modified by the second group other than the first group to the collaborative VR data of the first group,
Data visualization methods. 12. The method of claim 11,
The step of reflecting the modified network data to the collaborative VR data includes:
Comparing the network data modified by the first group and the second group, and notifying the first and second groups of a warning about the conflict if the modifications conflict with each other;
Data visualization methods. processor;
network interface;
Memory; and
a computer program loaded into the memory and executed by the processor;
The computer program is
an instruction for obtaining network data composed of a node and an edge connecting the nodes;
instructions for obtaining user interest information of the first user;
instructions for generating VR data in which the network data is visualized;
instructions for generating custom VR data of the first user by adjusting the VR data to reflect the user interest information of the first user;
instructions for transmitting the custom VR data of the first user to the terminal of the first user;
instructions for obtaining user interest information of a second user;
instructions for analyzing whether the interest information is similar by comparing the user interest information of the first user with the user interest information of the second user; and
and instructions for matching the first user and the second user as a first group when the interest information is similar;
The instructions for generating custom VR data of the first user include:
Including instructions for generating collaborative VR data for visualizing the same custom VR data on terminals of the first user and the second user,
Data visualization server. combined with a computing device,
obtaining network data consisting of a node and an edge connecting the nodes;
obtaining user interest information of the first user;
generating VR data in which the network data is visualized;
generating custom VR data of the first user by adjusting the VR data to reflect user interest information of the first user;
transmitting the custom VR data of the first user to the terminal of the first user;
obtaining user interest information of a second user;
analyzing whether the interest information is similar by comparing the user interest information of the first user with the user interest information of the second user; and
matching the first user and the second user as a first group when the interest information is similar
including,
The step of generating the custom VR data of the first user comprises:
stored in a computer-readable recording medium to execute the step of generating collaborative VR data that visualizes the same custom VR data on terminals of the first user and the second user;
computer program.

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