CN116415000A - Visual knowledge graph configuration method, device, equipment and storage medium - Google Patents
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Abstract
The application provides a configuration method, device and equipment of a visual knowledge graph and a storage medium. Relates to the technical field of knowledge maps, which comprises the following steps: acquiring a target user-defined map visualization parameter, map data to be subjected to knowledge map visualization and a target map layout, wherein the map visualization parameter comprises a node parameter, an edge parameter and a character parameter; generating a plurality of nodes and a plurality of edges according to node information and relation information among the nodes contained in the graph data, wherein each node and each edge have unique identification information; carrying out layout arrangement on a plurality of nodes and a plurality of edges according to the target map layout to obtain a generated initial visual knowledge map; rendering a plurality of nodes, a plurality of edges and characters in the initial visual knowledge graph according to graph visualization parameters to generate the visual knowledge graph. The method and the device can realize the self definition of the nodes, the edges and the characters without manually modifying the codes, increase the patterns of the visual knowledge graph and improve the visual effect.
Description
Technical Field
The present disclosure relates to the technical field of knowledge graphs, and in particular, to a method, an apparatus, a device, and a storage medium for configuring a visual knowledge graph.
Background
Knowledge Graph (KG) is to visually display Knowledge and the interrelationship between them by means of a visualization technology, wherein entities are used as nodes in the Graph, and semantic relations between entities are used as edges of the Graph. The knowledge graph breaks data isolation, is convenient for machine learning data and knowledge reasoning, thereby discovering deep knowledge and relations and providing support for intelligent search, intelligent question-answering, recommendation and intelligent decision. In the related art, the knowledge graph visualization method is generally displayed by using middleware such as echart and d3, but once the pattern of the graph is rendered, the pattern is single and fixed and cannot be modified, and even if the color of the node is only required to be modified, a developer is required to manually modify the code, so that the knowledge graph visualization method is very unfriendly to users.
Disclosure of Invention
The application provides a configuration method, device, equipment and storage medium of a visual knowledge graph, which are used for solving the problem that a pattern of a rendered graph cannot be singly fixed and modified in the prior art.
In a first aspect, the present application provides a method for configuring a visual knowledge graph, including: acquiring a target user-defined map visualization parameter, map data to be subjected to knowledge map visualization and a target map layout, wherein the map visualization parameter comprises a node parameter, an edge parameter and a character parameter; generating a plurality of nodes and a plurality of edges according to node information and relation information among the nodes contained in the graph data, wherein each node and each edge have unique identification information; carrying out layout arrangement on a plurality of nodes and a plurality of edges according to the target map layout to obtain a generated initial visual knowledge map; rendering a plurality of nodes, a plurality of edges and characters in the initial visual knowledge graph according to graph visualization parameters to generate the visual knowledge graph.
In some embodiments, after generating the visual knowledge-graph, further comprising: displaying the visual knowledge graph on a target page; and acquiring the display state of the visual knowledge graph on the target page, and adjusting the visual knowledge graph according to the display state.
In some embodiments, obtaining a display state of the visual knowledge-graph on the target page, and adjusting the visual knowledge-graph according to the display state includes: acquiring node concentration of a visual knowledge graph on a target page as a first node concentration; determining at least one target node in the visual knowledge-graph in response to the first node concentration being greater than a preset concentration threshold; and merging all descendant nodes subordinate to the target node to generate a virtual node.
In some embodiments, the configuration method of the visual knowledge graph further includes: and in response to monitoring the clicking operation on any virtual node, expanding a plurality of descendant nodes corresponding to the virtual node to be displayed on a target page.
In some embodiments, determining at least one target node in the visual knowledge-graph comprises: displaying the visual knowledge graph on a target page according to a preset second node concentration; acquiring all nodes displayed in a target page as candidate nodes; acquiring all nodes exceeding a target page as exceeding nodes; and taking the candidate node with the common edge with any exceeding node as a target node.
In some embodiments, a method of obtaining a target atlas layout includes: unifying the formats of the graph data to generate target graph data; acquiring basic attributes of target graph data; a target atlas layout is determined from the plurality of candidate atlas layouts based on the cardinal attribute.
In a second aspect, the present application provides a configuration apparatus for a visual knowledge graph, including: the acquisition module is used for acquiring the user-defined map visualization parameters of the target user, the map data to be subjected to the knowledge map visualization and the target map layout, wherein the map visualization parameters comprise node parameters, side parameters and character parameters; the generating module is used for generating a plurality of nodes and a plurality of edges according to node information and relation information among the nodes contained in the graph data, wherein each node and each edge have unique identification information; the layout module is used for carrying out layout arrangement on a plurality of nodes and a plurality of edges according to the target map layout to obtain a generated initial visual knowledge map; and the rendering module is used for rendering a plurality of nodes, a plurality of edges and characters in the initial visual knowledge graph according to the graph visualization parameters to generate the visual knowledge graph.
In some embodiments, the configuration device of the visual knowledge graph further includes: the display module is used for displaying the visual knowledge graph on the target page; the adjustment module is used for acquiring the display state of the visual knowledge graph on the target page and adjusting the visual knowledge graph according to the display state.
In some embodiments, the adjustment module is further to: acquiring node concentration of a visual knowledge graph on a target page as a first node concentration; determining at least one target node in the visual knowledge-graph in response to the first node concentration being greater than a preset concentration threshold; and merging all descendant nodes subordinate to the target node to generate a virtual node.
In some embodiments, the adjustment module is further to: and in response to monitoring the clicking operation on any virtual node, expanding a plurality of descendant nodes corresponding to the virtual node to be displayed on a target page.
In some embodiments, the adjustment module is further to: displaying the visual knowledge graph on a target page according to a preset second node concentration; acquiring all nodes displayed in a target page as candidate nodes; acquiring all nodes exceeding a target page as exceeding nodes; and taking the candidate node with the common edge with any exceeding node as a target node.
In some embodiments, the acquisition module is further to: unifying the formats of the graph data to generate target graph data; acquiring basic attributes of target graph data; a target atlas layout is determined from the plurality of candidate atlas layouts based on the cardinal attribute.
In a third aspect, the present application provides an electronic device, comprising: a processor, a memory communicatively coupled to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement the method of configuring the visual knowledge-graph as previously described.
In a fourth aspect, a computer readable storage medium is provided, which when stored with computer executable instructions for implementing a method of configuring a visual knowledge graph as before when executed by a processor.
In a fifth aspect, a computer program product is provided, comprising computer programs/instructions, characterized in that the computer programs/instructions, when executed by a processor, implement a method of configuring a visual knowledge graph as before.
The configuration method, the device, the equipment and the storage medium for the visual knowledge graph have the beneficial effects that: according to the method and the device, the user definition of the nodes, the edges and the characters can be realized without manually modifying codes according to the user-defined map visualization parameters, the patterns of the visual knowledge maps are increased, and the visual effect of the knowledge maps is improved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application.
Fig. 1 is an exemplary implementation of a method for configuring a visual knowledge graph according to an embodiment of the present application;
FIG. 2 (a) is a schematic diagram of a balance map layout shown in the present application;
FIG. 2 (b) is a schematic diagram of a block diagram layout shown in the present application;
FIG. 2 (c) is a schematic diagram of a logic diagram layout shown in the present application;
FIG. 2 (d) is a schematic diagram of a dendrogram layout shown in the present application;
FIG. 2 (e) is a schematic diagram of a timeline layout as shown herein;
FIG. 2 (f) is a schematic illustration of a circular diagram layout shown in the present application;
fig. 3 is an exemplary implementation of a method for configuring a visual knowledge graph according to an embodiment of the present application;
fig. 4 is an exemplary implementation of a method for configuring a visual knowledge graph according to an embodiment of the present application; the method comprises the steps of carrying out a first treatment on the surface of the
Fig. 5 is a schematic diagram of a configuration device of a visual knowledge graph according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Specific embodiments thereof have been shown by way of example in the drawings and will herein be described in more detail. These drawings and the written description are not intended to limit the scope of the inventive concepts in any way, but to illustrate the concepts of the present application to those skilled in the art by reference to specific embodiments.
Detailed Description
Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples are not representative of all implementations consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with some aspects of the present application as detailed in the accompanying claims.
Term interpretation: knowledge Graph (KG) is to visually display Knowledge and the interrelationship between them by means of a visualization technology, wherein entities are used as nodes in the Graph, semantic relations between the entities are used as edges of the Graph, and the Knowledge Graph is essentially a semantic network. The knowledge graph breaks data isolation, is convenient for machine learning data and knowledge reasoning, thereby discovering deep knowledge and relations and providing support for intelligent search, intelligent question-answering, recommendation and intelligent decision.
Fig. 1 is an exemplary embodiment of a method for configuring a visual knowledge graph, as shown in fig. 1, and includes the following steps:
s101, acquiring a target user-defined map visualization parameter, map data to be subjected to knowledge map visualization and a target map layout, wherein the map visualization parameter comprises a node parameter, an edge parameter and a character parameter.
And acquiring a target user-defined map visualization parameter, wherein the map visualization parameter comprises a node parameter, an edge parameter and a character parameter.
For example, in the present application, a palette may be provided to enable a user to customize the map visualization parameters, where the node parameters may include node parameters such as a color of a node, a size of the node, and transparency of the node; the edge parameters may include edge parameters such as color of the edge, length of the edge, thickness of the edge, etc.; the text parameters may include text parameters such as the color of the text, the font of the text, the size of the text, and the like. Alternatively, the colors may be stored in a 16-ary representation, with node radius size, edge length and thickness all stored in pixels or centimeters.
The drawing data to be subjected to the knowledge graph visualization is obtained, and the drawing data can be structural data of a certain university, such as data of a educational administration place, a student meeting and the like, or data of actors, directors, episodes and the like of a certain television show by way of example.
A target map layout is obtained, wherein the target map layout includes, but is not limited to, at least one of a balance map, a structure map, a tree map, a logic map, a time axis, a circle map, and the like.
S102, generating a plurality of nodes and a plurality of edges according to node information and relation information among the nodes contained in the graph data, wherein each node and each edge have unique identification information.
And generating a plurality of nodes and a plurality of edges according to node information and relation information among the nodes contained in the graph data, wherein each node and each edge have unique identification information.
Wherein a node is an entity and an edge represents a relationship between two entities.
And S103, carrying out layout arrangement on a plurality of nodes and a plurality of edges according to the target map layout to obtain the generated initial visual knowledge map.
And carrying out layout arrangement on a plurality of nodes and a plurality of edges according to the selected target map layout to obtain the generated initial visual knowledge map.
And S104, rendering a plurality of nodes, a plurality of edges and characters in the initial visual knowledge graph according to the graph visualization parameters to generate the visual knowledge graph.
Rendering a plurality of nodes, a plurality of edges and characters in the obtained initial visual knowledge graph according to graph visualization parameters to generate the visual knowledge graph.
The embodiment of the application provides a configuration method of a visual knowledge graph, which comprises the steps of obtaining a graph visualization parameter customized by a target user, graph data to be subjected to knowledge graph visualization and a target graph layout, wherein the graph visualization parameter comprises a node parameter, an edge parameter and a character parameter; generating a plurality of nodes and a plurality of edges according to node information and relation information among the nodes contained in the graph data, wherein each node and each edge have unique identification information; carrying out layout arrangement on a plurality of nodes and a plurality of edges according to the target map layout to obtain a generated initial visual knowledge map; rendering a plurality of nodes, a plurality of edges and characters in the initial visual knowledge graph according to graph visualization parameters to generate the visual knowledge graph. According to the method and the device, the user definition of the nodes, the edges and the characters can be realized without manually modifying codes according to the user-defined map visualization parameters, the patterns of the visual knowledge maps are increased, and the visual effect of the knowledge maps is improved.
In some embodiments, a method of obtaining a target atlas layout includes: and unifying formats of the map data, generating target map data, acquiring basic attributes of the target map data, and determining a target map layout from a plurality of candidate map layouts according to the basic attributes.
The candidate map layout may include a balance map, a structure map, a tree map, a logic map, a time axis, and a circle map. For example, if the basic attribute of the target graph data indicates that there is a time axis in the target graph data, the time axis layout may be selected as the target graph layout.
The following is a simple illustration of a partial candidate atlas layout:
fig. 2 (a) is a schematic diagram of a balanced graph layout shown in the present application, fig. 2 (b) is a schematic diagram of a block diagram layout shown in the present application, fig. 2 (c) is a schematic diagram of a logic graph layout shown in the present application, fig. 2 (d) is a schematic diagram of a tree graph layout shown in the present application, fig. 2 (e) is a schematic diagram of a time axis layout shown in the present application, and fig. 2 (f) is a schematic diagram of a circular graph layout shown in the present application.
Furthermore, in the application, when the browser compatibility problem is encountered, incompatible attributes or functions can be obtained, the browser compatibility problem is solved by using a way of realizing the original js or different css attributes, different browser display differences are compatible, and the visual effect of the knowledge graph is improved.
Fig. 3 is an exemplary embodiment of a method for configuring a visual knowledge graph, as shown in fig. 3, and includes the following steps:
s301, acquiring a target user-defined map visualization parameter, map data to be subjected to knowledge map visualization and a target map layout, wherein the map visualization parameter comprises a node parameter, an edge parameter and a character parameter.
S302, generating a plurality of nodes and a plurality of edges according to node information and relation information among the nodes contained in the graph data, wherein each node and each edge have unique identification information.
S303, carrying out layout arrangement on a plurality of nodes and a plurality of edges according to the target map layout to obtain the generated initial visual knowledge map.
And S304, rendering a plurality of nodes, a plurality of edges and characters in the initial visual knowledge graph according to the graph visualization parameters to generate the visual knowledge graph.
For the specific implementation of steps S301 to S304, reference may be made to the specific description of the relevant parts in the above embodiments, and the detailed description will not be repeated here.
And S305, displaying the visual knowledge graph on the target page.
And displaying the obtained visual knowledge graph on a target page. The target page refers to a page for displaying the visual knowledge graph.
Optionally, the target page may be a mobile phone page, a tablet page, a computer page, etc.
S306, acquiring the display state of the visual knowledge graph on the target page, and adjusting the visual knowledge graph according to the display state.
It is easy to understand that when the number of display nodes on the target page is too large, the screen size is limited, so that the whole visual knowledge graph is densely displayed, the visual effect is poor, in order to avoid the situation, in the application, the node density of the visual knowledge graph on the target page is obtained as the first node density, if the first node density is larger than a preset density threshold, at least one target node in the visual knowledge graph is determined, and all descendant nodes subordinate to the target node are combined to the target node, so that a virtual node is generated. Alternatively, the virtual nodes may be shown in dashed lines. And the node or relationship name of the virtual node is displayed on the virtual node. Alternatively, the node concentration may be the ratio of the total number of nodes to the total screen size.
When at least one target node in the visual knowledge graph is determined, the visual knowledge graph can be displayed on the target page according to a preset second node concentration, all nodes displayed in the target page are obtained to serve as candidate nodes, all nodes exceeding the target page are obtained to serve as exceeding nodes, and the candidate nodes with common edges with any exceeding node serve as target nodes.
Further, if the clicking operation on any virtual node is monitored, a plurality of descendant nodes corresponding to the virtual node are unfolded to be displayed on the target page.
According to the method and the device, the user definition of the nodes, the edges and the characters can be realized without manually modifying codes according to the user-defined map visualization parameters, the patterns of the visual knowledge map are increased, the visual knowledge map is adjusted according to the display state, the visual knowledge map is more suitable for the size of the current viewport, and the visual effect of the knowledge map is improved.
Fig. 4 is an exemplary embodiment of a method for configuring a visual knowledge graph, as shown in fig. 4, and includes the following steps:
providing a palette to realize user-defined map visualization parameters through a style unit, wherein the node parameters can comprise node parameters such as node color, node size, node transparency and the like; the edge parameters may include edge parameters such as color of the edge, length of the edge, thickness of the edge, etc.; the text parameters may include text parameters such as the color of the text, the font of the text, the size of the text, and the like. Alternatively, the colors may be stored in a 16-ary representation, with node radius size, edge length and thickness all stored in pixels or centimeters. The self-defined map visualization parameters are stored in a caching unit in a json object.
And providing a balance map layout, a structure map layout, a tree map layout, a logic map layout, a time axis layout, a circular map layout and other candidate map layouts through a layout unit, selecting one layout from a plurality of candidate map layouts as a target map layout, and storing the target map layout in a cache unit.
And through the caching unit, user-defined map visualization parameters and map data are realized by using a single-chain table, the table head always stores default configuration, and then the user-defined map visualization parameters are cached in sequence, so that map visualization rendering is quickened.
And the data processing unit is used for unifying the graph data obtained from the graph database request and is compatible with the data format difference of different visual middleware.
The data processing module is mainly responsible for processing graph data, taking node type and edge type as 3-level examples, and the graph data is json format data, and the specific format is as follows:
Graph：{
Id:g1
Type:gt1，
and (3) Nodes: [ { id: n1, name: node 1, type1 … }, { id: n2, name: node 2, type2 … }, { id: n3, name: node 3, type3} ]
Edge: [ { id: e1, name: edge 1, fn: n1, tn: n1, type1 … }, { id: e2, name: edge 2, fn: n1, tn: n2, type2 … }, { id: e3, name: edge 3, fn: n1, tn: n3, type3 … })
}
Graph is json object of the whole knowledge Graph, id is unique identification of the knowledge Graph, type is Type of the knowledge Graph, and corresponds to one of a plurality of candidate Graph layouts, if other is represented by a layout Graph provided by other components.
Nodes is node data, id is node unique identification, and the method is not repeatable.
Edge is edge data, id is unique identification of edge, and is not repeatable. type is the type of edge, and illustratively, the relationship type of an edge is divided into three categories: "lg: mg: sg" format. lg is the major category, mg is the medium category, sg is the minor category. Such as: campus relationship: alumni: college alumni. Campus relationship is a major class, alumni relationship is a middle class, and alumni relationship is a minor class.
Through the display unit, when the processing nodes are too many, the whole knowledge graph is densely displayed, and the problem of poor visual effect and the problem of browser compatibility are solved. The display module is mainly responsible for displaying the visual knowledge graph, and determines the optimal display number and mode of the current target page according to the size of the current screen target page and the style setting and target graph layout of nodes and edges in the graph visual parameters configured by a user. In the application, when the browser compatibility problem is encountered, incompatible attributes or functions can be obtained, the browser compatibility problem is solved by using a way of realizing the original js or different css attributes, different browser display differences are compatible, and the visual effect of the knowledge graph is improved.
The five-large-unit comprehensive construction configurable knowledge graph visualization tool provided by the embodiment of the application realizes efficient and rapid use of a user and rapid configuration generation of a large screen, avoids a traditional complicated rendering method, greatly shortens the online time of a project, and reduces the development workload.
The embodiment of the application provides a configuration method of a visual knowledge graph, which comprises the steps of obtaining a graph visualization parameter customized by a target user, graph data to be subjected to knowledge graph visualization and a target graph layout, wherein the graph visualization parameter comprises a node parameter, an edge parameter and a character parameter; generating a plurality of nodes and a plurality of edges according to node information and relation information among the nodes contained in the graph data, wherein each node and each edge have unique identification information; carrying out layout arrangement on a plurality of nodes and a plurality of edges according to the target map layout to obtain a generated initial visual knowledge map; rendering a plurality of nodes, a plurality of edges and characters in the initial visual knowledge graph according to graph visualization parameters to generate the visual knowledge graph. According to the method and the device, the user definition of the nodes, the edges and the characters can be realized without manually modifying codes according to the user-defined map visualization parameters, the patterns of the visual knowledge maps are increased, and the visual effect of the knowledge maps is improved.
Fig. 5 is a schematic diagram of a configuration apparatus for a visual knowledge graph, which is shown in fig. 5, and the configuration apparatus 500 for a visual knowledge graph includes an obtaining module 501, a generating module 502, a layout module 503, and a rendering module 504, where:
the obtaining module 501 is configured to obtain a target user-defined graph visualization parameter, graph data to be subjected to knowledge graph visualization, and a target graph layout, where the graph visualization parameter includes a node parameter, an edge parameter, and a text parameter;
a generating module 502, configured to generate a plurality of nodes and a plurality of edges according to node information and relationship information between nodes included in the graph data, where each node and each edge has unique identification information;
a layout module 503, configured to perform layout arrangement on a plurality of nodes and a plurality of edges according to a target map layout, and obtain a generated initial visual knowledge map;
and the rendering module 504 is configured to render the plurality of nodes, the plurality of edges and the text in the initial visual knowledge-graph according to the graph visualization parameters, so as to generate the visual knowledge-graph.
According to the configuration device of the visual knowledge graph, the definition of the nodes, the edges and the characters can be realized without manually modifying codes according to the graph visual parameters defined by the user, the patterns of the visual knowledge graph are increased, and the visual effect of the knowledge graph is improved.
In some embodiments, the configuration apparatus 500 for visualizing a knowledge graph further includes: the display module 505 is configured to display the visual knowledge graph on a target page; the adjustment module 506 is configured to obtain a display state of the visual knowledge graph on the target page, and adjust the visual knowledge graph according to the display state.
In some embodiments, the adjustment module 506 is further configured to: acquiring node concentration of a visual knowledge graph on a target page as a first node concentration; determining at least one target node in the visual knowledge-graph in response to the first node concentration being greater than a preset concentration threshold; and merging all descendant nodes subordinate to the target node to generate a virtual node.
In some embodiments, the adjustment module 506 is further configured to: and in response to monitoring the clicking operation on any virtual node, expanding a plurality of descendant nodes corresponding to the virtual node to be displayed on a target page.
In some embodiments, the adjustment module 506 is further configured to: displaying the visual knowledge graph on a target page according to a preset second node concentration; acquiring all nodes displayed in a target page as candidate nodes; acquiring all nodes exceeding a target page as exceeding nodes; and taking the candidate node with the common edge with any exceeding node as a target node.
In some embodiments, the obtaining module 501 is further configured to: unifying the formats of the graph data to generate target graph data; acquiring basic attributes of target graph data; a target atlas layout is determined from the plurality of candidate atlas layouts based on the cardinal attribute.
Fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present application. As shown in fig. 6, the electronic device may include: a transceiver 61, a processor 62, a memory 63.
The processor 62 executes computer-executable instructions stored in memory, causing the processor 62 to perform the aspects of the embodiments described above. The processor 62 may be a general-purpose processor including a central processing unit CPU, a network processor (network processor, NP), etc.; but may also be a digital signal processor DSP, an application specific integrated circuit ASIC, a field programmable gate array FPGA or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component.
The memory 63 is connected to the processor 62 via a system bus and communicates with each other, and the memory 63 is adapted to store computer program instructions.
The transceiver 61 may be configured to obtain a target user-defined graph visualization parameter, graph data to be subjected to knowledge graph visualization, and a target graph layout, where the graph visualization parameter includes a node parameter, an edge parameter, and a text parameter; generating a plurality of nodes and a plurality of edges according to node information and relation information among the nodes contained in the graph data, wherein each node and each edge have unique identification information; carrying out layout arrangement on a plurality of nodes and a plurality of edges according to the target map layout to obtain a generated initial visual knowledge map; rendering a plurality of nodes, a plurality of edges and characters in the initial visual knowledge graph according to graph visualization parameters to generate the visual knowledge graph.
The system bus may be a peripheral component interconnect standard (peripheral component interconnect, PCI) bus or an extended industry standard architecture (extended industry standard architecture, EISA) bus, among others. The system bus may be classified into an address bus, a data bus, a control bus, and the like. For ease of illustration, the figures are shown with only one bold line, but not with only one bus or one type of bus. The transceiver is used to enable communication between the database access device and other computers (e.g., clients, read-write libraries, and read-only libraries). The memory may include random access memory (random access memory, RAM) and may also include non-volatile memory (non-volatile memory).
The electronic device provided in the embodiment of the present application may be a terminal device in the above embodiment.
The embodiment of the application also provides a chip for running the instruction, and the chip is used for executing the technical scheme of the configuration method of the visual knowledge graph in the embodiment.
The embodiment of the application also provides a computer readable storage medium, wherein computer instructions are stored in the computer readable storage medium, and when the computer instructions run on a computer, the computer is caused to execute the configuration method of the visual knowledge graph of the embodiment.
The embodiment of the application also provides a computer program product, which comprises a computer program, wherein the computer program is stored in a computer readable storage medium, the computer program can be read from the computer readable storage medium by at least one processor, and the configuration method of the visual knowledge graph in the embodiment can be realized when the computer program is executed by the at least one processor.
Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the application following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the application pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the application being indicated by the following claims.
It is to be understood that the present application is not limited to the precise arrangements and instrumentalities shown in the drawings, which have been described above, and that various modifications and changes may be effected without departing from the scope thereof. The scope of the application is limited only by the appended claims.
Claims (15)
1. The configuration method of the visual knowledge graph is characterized by comprising the following steps of:
acquiring a target user-defined map visualization parameter, map data to be subjected to knowledge map visualization and a target map layout, wherein the map visualization parameter comprises a node parameter, an edge parameter and a character parameter;
generating a plurality of nodes and a plurality of edges according to node information and relation information among the nodes contained in the graph data, wherein each node and each edge have unique identification information;
carrying out layout arrangement on the plurality of nodes and the plurality of edges according to the target map layout to obtain a generated initial visual knowledge map;
rendering the nodes, the edges and the characters in the initial visual knowledge graph according to the graph visualization parameters to generate the visual knowledge graph.
2. The method of claim 1, wherein after generating the visual knowledge-graph, further comprising:
displaying the visual knowledge graph on a target page;
and acquiring the display state of the visual knowledge graph on the target page, and adjusting the visual knowledge graph according to the display state.
3. The method according to claim 2, wherein the obtaining the display state of the visual knowledge-graph on the target page and adjusting the visual knowledge-graph according to the display state includes:
acquiring node concentration of the visual knowledge graph on the target page as a first node concentration;
determining at least one target node in the visual knowledge graph in response to the first node concentration being greater than a preset concentration threshold;
and merging all descendant nodes subordinate to the target node to generate a virtual node.
4. A method according to claim 3, characterized in that the method further comprises:
and responding to the detection of clicking operation on any virtual node, and expanding a plurality of descendant nodes corresponding to the virtual node to be displayed on the target page.
5. A method according to claim 3, wherein said determining at least one target node in the visual knowledge-graph comprises:
displaying the visual knowledge graph on the target page according to a preset second node concentration;
acquiring all nodes displayed in the target page as candidate nodes;
acquiring all nodes exceeding the target page as exceeding nodes;
and taking the candidate node with the common edge with any exceeding node as the target node.
6. The method according to claim 1, wherein the target map layout obtaining method includes:
unifying the formats of the map data to generate target map data;
acquiring basic attributes of the target graph data;
and determining the target map layout from a plurality of candidate map layouts according to the basic attribute.
7. A visual knowledge graph configuration device, comprising:
the acquisition module is used for acquiring the user-defined map visualization parameters of the target user, the map data to be subjected to knowledge map visualization and the target map layout, wherein the map visualization parameters comprise node parameters, side parameters and character parameters;
the generating module is used for generating a plurality of nodes and a plurality of edges according to node information and relationship information among the nodes contained in the graph data, wherein each node and each edge have unique identification information;
the layout module is used for carrying out layout arrangement on the plurality of nodes and the plurality of edges according to the target map layout to obtain a generated initial visual knowledge map;
and the rendering module is used for rendering the nodes, the edges and the characters in the initial visual knowledge graph according to the graph visualization parameters to generate the visual knowledge graph.
8. The apparatus of claim 7, wherein the apparatus further comprises:
the display module is used for displaying the visual knowledge graph on a target page;
the adjustment module is used for acquiring the display state of the visual knowledge graph on the target page and adjusting the visual knowledge graph according to the display state.
9. The apparatus of claim 8, wherein the adjustment module is further configured to:
acquiring node concentration of the visual knowledge graph on the target page as a first node concentration;
determining at least one target node in the visual knowledge graph in response to the first node concentration being greater than a preset concentration threshold;
and merging all descendant nodes subordinate to the target node to generate a virtual node.
10. The apparatus of claim 9, wherein the adjustment module is further configured to:
and responding to the detection of clicking operation on any virtual node, and expanding a plurality of descendant nodes corresponding to the virtual node to be displayed on the target page.
11. The apparatus of claim 9, wherein the adjustment module is further configured to:
displaying the visual knowledge graph on the target page according to a preset second node concentration;
acquiring all nodes displayed in the target page as candidate nodes;
acquiring all nodes exceeding the target page as exceeding nodes;
and taking the candidate node with the common edge with any exceeding node as the target node.
12. The apparatus of claim 7, wherein the acquisition module is further configured to:
unifying the formats of the map data to generate target map data;
acquiring basic attributes of the target graph data;
and determining the target map layout from a plurality of candidate map layouts according to the basic attribute.
13. An electronic device, comprising: a processor, and a memory communicatively coupled to the processor;
the memory stores computer-executable instructions;
the processor executes computer-executable instructions stored in the memory to implement the method of any one of claims 1-6.
14. A computer readable storage medium having stored therein computer executable instructions which when executed by a processor are adapted to carry out the method of any one of claims 1-6.
15. A computer program product comprising a computer program which, when executed by a processor, implements the method of any of claims 1-6.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117033420A (en) * | 2023-10-09 | 2023-11-10 | 之江实验室 | Visual display method and device for entity data under same concept of knowledge graph |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117033420A (en) * | 2023-10-09 | 2023-11-10 | 之江实验室 | Visual display method and device for entity data under same concept of knowledge graph |
| CN117033420B (en) * | 2023-10-09 | 2024-01-09 | 之江实验室 | Visual display method and device for entity data under same concept of knowledge graph |
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