CN117390195A - Knowledge traceability connecting method, system, equipment and medium based on graph editor - Google Patents
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Abstract
The invention provides a knowledge traceability connecting method, a device, equipment and a medium based on a graph editor, wherein the method comprises the following steps: the method comprises the steps of building a front-end interface through a front-end frame, obtaining tracing information data, generating a knowledge graph according to the tracing information data in a graph editor window, generating tracing segment cards corresponding to a plurality of relevant tracing segments in a tracing segment window under the condition that target entity nodes selected by click signals are determined, determining target tracing segment cards from the tracing segment cards according to association coefficients, further obtaining position information of the target entity nodes and the target tracing segment cards, carrying out connection processing on the target entity nodes and the target tracing segment cards according to the position information, further achieving an automatic tracing information connection function, solving the problem that visual interaction is lacking between the knowledge graph and the knowledge tracing information, improving the visualization capability of a knowledge graph system, and enabling a user to view the knowledge tracing information more quickly and effectively.
Description
Technical Field
The invention relates to the technical field of knowledge graphs, in particular to a knowledge traceability connecting method, a knowledge traceability connecting system, a knowledge traceability connecting device and a knowledge traceability connecting medium based on a graph editor.
Background
In recent years, knowledge graph technology is widely applied to various data management and service platforms so as to more effectively perform knowledge retrieval, so that the platform can be used as a knowledge center to integrate, manage and share knowledge assets inside and outside an enterprise, and provide integrated view of data and intelligent data service for the enterprise.
There are various kinds of visualization libraries or image libraries for creating interactive and customizable charts and data visualization, providing basic chart types and interactive functions, such as echorts and G6, etc., through which related technicians can draw and edit knowledge graph contents to complete knowledge graph development, and display knowledge tracing information related to the knowledge graph contents by setting a sliding window in the knowledge graph system alone, so as to facilitate user viewing.
However, in the actual use process, under the condition that the number of nodes in the knowledge graph is large and the number of the knowledge tracing information correspondingly displayed is large, because the knowledge graph and the knowledge tracing information are not interactively displayed on the image, the user can hardly distinguish the positions of the currently selected nodes and the corresponding knowledge tracing information, the visualization capability of the knowledge graph system is affected, and the common user can only marginally and selectively check the related knowledge tracing information after the related technician understands the knowledge tracing connection line between the graph nodes and the information manually according to the user.
Disclosure of Invention
The following is a summary of the subject matter described in detail herein. This summary is not intended to limit the scope of the claims.
The embodiment of the invention provides a knowledge tracing connecting method, electronic equipment and medium based on a graph editor, which aim to solve the technical problem that the visibility of a knowledge graph system is poor because no image is displayed interactively between a knowledge graph and knowledge tracing information in the prior art.
To achieve the above objective, a first aspect of an embodiment of the present invention provides a knowledge tracing connection method based on a graph editor, including:
building a front-end interface through a front-end framework, wherein the front-end interface comprises a graph editor window and a tracing fragment window;
acquiring tracing information data, and generating a knowledge graph in the graph editor window according to the tracing information data, wherein the knowledge graph comprises a plurality of entity nodes;
Responding to a click signal received by the graph editor window, and determining a target entity node selected by the click signal;
determining a plurality of related tracing fragments from the tracing information data according to the target entity node, and generating tracing fragment cards corresponding to the plurality of related tracing fragments in the tracing fragment window;
acquiring association coefficients of a plurality of tracing fragment cards, and determining a target tracing fragment card from the plurality of tracing fragment cards according to the association coefficients;
and acquiring the position information of the target entity node and the target tracing fragment card, and carrying out connection processing on the target entity node and the target tracing fragment card according to the position information.
In some embodiments, the entity nodes are connected by a relationship edge, and the generating a knowledge graph according to the traceability information data in the graph editor window includes:
performing feature capturing processing on the traceability information data to obtain a plurality of entity features and relation features among the entity features, and obtaining weight coefficients of the entity features in the knowledge graph;
In the graph editor window, based on an ECharts visual library, generating the entity nodes in the knowledge graph according to the entity characteristics and the weight coefficients, and generating the relationship edges in the knowledge graph according to the relationship characteristics.
In some embodiments, the generating the entity node in the knowledge-graph according to the entity feature and the weight coefficient, and the generating the relationship edge in the knowledge-graph according to the relationship feature based on the ECharts visualization library includes:
determining the node name of the entity node according to the entity characteristics;
determining the node size of the entity node according to the weight coefficient;
based on an ECharts visual library, node coordinates are distributed for the entity nodes, and the entity nodes are generated in a knowledge graph according to the node coordinates, the node names and the node sizes;
and acquiring node coordinates of the entity nodes at two ends of the relation edge according to the relation features, and generating the relation edge in a knowledge graph according to the node coordinates of the entity nodes at two ends.
In some embodiments, the tracing information data includes a plurality of tracing segments, and the determining, according to the target entity node, a plurality of relevant tracing segments from the tracing information data includes:
Acquiring connection relation information of the target entity node in the knowledge graph;
determining adjacent nodes of the target entity node according to the connection relation information, and determining relation edges between the target entity node and the adjacent nodes;
and determining the tracing segments of the entity features corresponding to the target entity node and the adjacent node as related tracing segments, and determining the tracing segments of the relationship features corresponding to the relationship edges as the related tracing segments.
In some embodiments, the obtaining the association coefficients of the plurality of the traceability segment cards and determining the target traceability segment card from the plurality of the traceability segment cards according to the association coefficients includes:
determining a relationship tracing fragment card corresponding to a plurality of relationship edges from a plurality of tracing fragment cards;
acquiring association weight coefficients of a plurality of relationship tracing fragment cards, wherein the association weight coefficients are weight coefficients of the adjacent nodes corresponding to the relationship tracing fragment cards;
determining association coefficients of a plurality of relationship traceability fragment cards according to the association weight coefficients;
and determining the relationship tracing fragment card with the association coefficient larger than a preset association threshold value as a target tracing fragment card.
In some embodiments, the location information of the target entity node includes start location information, and the location information of the target trace clip card includes end location information;
the step of acquiring the starting point position information is as follows:
the left upper corner coordinate of the front end interface is taken as an origin, click coordinate information of the click signal is obtained through an ECharts visual library, and the starting point position information is obtained according to the click coordinate information;
the step of acquiring the starting point position information is as follows:
acquiring card width information of the target traceability fragment card;
obtaining distance information between a plurality of target tracing fragment cards and the top of the tracing fragment window;
and obtaining the end position information according to the card width information and the distance information.
In some embodiments, the performing connection processing on the target entity node and the target traceability segment card according to the location information includes:
determining a relationship type and a relationship strength according to the relationship features corresponding to the target traceability fragment card;
determining line color parameters according to the relation types and line form parameters according to the relation strength;
And generating connecting lines according to the starting point position information, the end point position information, the line color parameters and the line morphological parameters based on the ECharts visual library so as to perform connecting line processing.
In some embodiments, the tracing segment window includes a longitudinal sliding window located on the right side of the front end interface, and after obtaining the distance information between the plurality of target tracing segment cards and the top of the tracing segment window, the method further includes:
under the condition that the longitudinal sliding window responds to the received sliding signals and performs sliding display processing on a plurality of tracing fragment cards, obtaining longitudinal sliding distances of a plurality of tracing fragments;
adjusting the distance information according to the longitudinal sliding distance;
and obtaining the end position information of the target tracing fragment card according to the card width information and the adjusted distance information.
In some embodiments, after the generating a knowledge graph according to the traceability information data in the graph editor window, the method further includes:
responding to the editing control signal received by the graph editor window, and performing editing control processing on the knowledge graph through a graph editor functional module deployed in the graph editor window;
Wherein the editing control process includes at least one of:
scaling the knowledge graph;
adding, deleting and editing relation edges between the entity nodes and a plurality of entity nodes in the knowledge graph;
performing floating window display processing on attribute information of the entity nodes and the relation edges in the knowledge graph;
and searching the entity nodes in the knowledge graph to determine target entity nodes, and adjusting the visible range of the knowledge graph according to the position information of the target entity nodes.
To achieve the above object, a second aspect of the embodiments of the present invention provides a knowledge traceability connection system based on a graph editor, including:
the interface building module is used for building a front-end interface through a front-end framework, and the front-end interface comprises a graph editor window and a tracing fragment window;
the knowledge graph generation module is used for acquiring the traceability information data and generating a knowledge graph in the graph editor window according to the traceability information data, wherein the knowledge graph comprises a plurality of entity nodes;
the entity node determining module is used for responding to the click signal received by the graph editor window and determining a target entity node selected by the click signal;
The tracing segment determining module is used for determining a plurality of related tracing segments from the tracing information data according to the target entity node and generating tracing segment cards corresponding to the plurality of related tracing segments in the tracing segment window;
the traceability card determining module is used for acquiring the association coefficients of the plurality of traceability fragment cards and determining target traceability fragment cards from the plurality of traceability fragment cards according to the association coefficients;
and the traceability information connecting module is used for acquiring the position information of the target entity node and the target traceability fragment card and carrying out connecting processing on the target entity node and the target traceability fragment card according to the position information.
To achieve the above object, a third aspect of the embodiments of the present invention provides an electronic device, which includes a memory, a processor, where the memory stores a computer program, and the processor implements the method described in the first aspect when executing the computer program.
To achieve the above object, a fourth aspect of the embodiments of the present invention proposes a computer-readable storage medium storing a computer program which, when executed by a processor, implements the method of the first aspect.
The knowledge traceability connecting method, system, equipment and medium based on the graph editor provided by the invention are characterized in that a front-end interface is built through the front-end framework, the front-end interface comprises a graph editor window and a traceability fragment window, and it is conceivable that a user interface can be quickly and effectively created by using the front-end framework, so that development time and cost are reduced, and a user can view knowledge graph and traceability information in an integrated environment at the same time; further, acquiring traceability information data, generating a knowledge graph according to the traceability information data in the graph editor window, wherein the knowledge graph comprises a plurality of entity nodes, and conceivably, under the condition that a front-end interface is ready, the knowledge graph generated according to the real-time traceability information data state is embedded in the graph editor window, so that the user can edit and use the knowledge graph conveniently; further, in response to the click signal received by the graph editor window, determining the target entity node selected by the click signal, it is contemplated that the process of responding to the signal provides interactivity, allowing the user to select the particular entity node of interest to them by clicking; further, a plurality of relevant tracing segments are determined from the tracing information data according to the target entity node, tracing segment cards corresponding to the plurality of relevant tracing segments are generated in the tracing segment window, so that a user can intuitively see tracing information related to the selected node after preliminary screening, and the visualization capability of the knowledge graph is further enhanced; further, obtaining association coefficients of a plurality of traceability fragment cards, and determining a target traceability fragment card from the plurality of traceability fragment cards according to the association coefficients so as to achieve the effect of secondary screening, and guiding a user to view traceability information with higher association degree; further, the method and the system acquire the position information of the target entity node and the target tracing fragment card, and perform connection processing on the target entity node and the target tracing fragment card according to the position information to realize an automatic knowledge tracing connection function, wherein after a user clicks one entity node through a front end interface of the method and the system, a plurality of tracing fragments related to the node are automatically found out from tracing information data and displayed in a tracing fragment window in a card form, meanwhile, the method and the system further analyze the association coefficient between the tracing fragment cards to automatically acquire the position information of the entity node and the tracing fragment card selected by the user after determining which tracing fragment is most relevant or most important, and draw a connection to intuitively display the association between the entity node and the tracing fragment card, the automatic tracing information connection function can effectively solve the problem that the knowledge map and the knowledge tracing information lack visual interaction, improve the visualization capability of the knowledge map system, enable the user to track, verify and trace the positions of the related nodes and the related information and the positions of the related information more quickly, and view the related information, and further improve the experience of the tracing experience of the user.
Drawings
FIG. 1 is a flowchart of a knowledge traceability connection method based on a graph editor according to an embodiment of the present invention;
fig. 2 is a flowchart of step S120 in fig. 1;
fig. 3 is a flowchart of step S220 in fig. 2;
fig. 4 is a flowchart of step S140 in fig. 1;
fig. 5 is a flowchart of step S150 in fig. 1;
fig. 6 is a flowchart of acquiring the start point position information;
fig. 7 is a flowchart of step S160 in fig. 1;
FIG. 8 is an interface schematic diagram of a knowledge traceability connection system based on a graph editor according to an embodiment of the present invention;
FIG. 9 is a schematic diagram of a knowledge traceability connection system based on a graph editor according to an embodiment of the present invention;
fig. 10 is a schematic diagram of a hardware structure of an electronic device according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
It should be noted that although functional block diagrams are depicted as block diagrams, and logical sequences are shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the block diagrams in the system. The terms first, second and the like in the description and in the claims and in the above-described figures, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used herein is for the purpose of describing embodiments of the invention only and is not intended to be limiting of the invention.
In recent years, knowledge graph technology is widely applied to various data management and service platforms so as to more effectively perform knowledge retrieval, so that the platform can be used as a knowledge center to integrate, manage and share knowledge assets inside and outside an enterprise, and provide integrated view of data and intelligent data service for the enterprise. There are various kinds of visualization libraries or image libraries for creating interactive and customizable charts and data visualization, providing basic chart types and interactive functions, such as echorts and G6, etc., through which related technicians can draw and edit knowledge graph contents to complete knowledge graph development, and display knowledge tracing information related to the knowledge graph contents by setting a sliding window in the knowledge graph system alone, so as to facilitate user viewing.
However, both echartits and G6 do not support the automatic connection requirement, in the actual use process, under the condition that the number of nodes in the knowledge graph is more and the number of knowledge traceability information correspondingly displayed is more, because the knowledge graph and the knowledge traceability information do not have interactive display on the image, the user can be difficult to distinguish the positions of the currently selected nodes and the corresponding knowledge traceability information, the visualization capability of the knowledge graph system is affected, and the common user can only marginally and selectively view the related knowledge traceability information after the related technician understands the knowledge traceability connection between the manually drawn graph nodes and the information according to the user.
Based on the above, the embodiment of the invention provides a knowledge tracing connecting method, electronic equipment and medium based on a graph editor, which aim to solve the technical problem that the visualization capability of a knowledge graph system is poor because of no interactive display on images between a knowledge graph and knowledge tracing information in the prior art.
In the context of the present invention, the invention is operational with numerous general purpose or special purpose computer system environments or configurations. For example: personal computers, server computers, hand-held or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like. The invention may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The invention may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices, and are not particularly limited in embodiments of the invention.
Specifically, in the embodiment of the invention, the graph editor is an important requirement for knowledge retrieval in a knowledge center, and the visual display of the knowledge traceability line of the graph in the invention can facilitate internal medical staff and related product staff to quickly understand the current knowledge reserve condition and the outward modeling of structured knowledge, and the knowledge traceability line is a relation line of graphs and knowledge source information so that a user can trace, verify and trace the source of the information.
Embodiments of the present invention are further described below with reference to the accompanying drawings.
Fig. 1 is a flowchart of a knowledge traceability connection method based on a graph editor according to an embodiment of the present invention, and the method in fig. 1 may include, but is not limited to, steps S110 to S160.
Step S110, a front-end interface is built through a front-end framework, wherein the front-end interface comprises a graph editor window and a tracing fragment window;
step S120, acquiring traceability information data, and generating a knowledge graph in a graph editor window according to the traceability information data, wherein the knowledge graph comprises a plurality of entity nodes;
step S130, responding to the click signal received by the graph editor window, and determining a target entity node selected by the click signal;
step S140, determining a plurality of relevant tracing segments from tracing information data according to the target entity node, and generating tracing segment cards corresponding to the plurality of relevant tracing segments in a tracing segment window;
step S150, obtaining association coefficients of a plurality of traceable fragment cards, and determining a target traceable fragment card from the plurality of traceable fragment cards according to the association coefficients;
and step S160, the position information of the target entity node and the target tracing fragment card is taken, and the connection processing is carried out on the target entity node and the target tracing fragment card according to the position information.
In the steps S110 to S160 illustrated in the embodiment of the present invention, a front-end interface is built through a front-end framework, where the front-end interface includes a graph editor window and a tracing fragment window, it is conceivable that, by using the front-end framework, a user interface can be quickly and effectively created, so as to reduce development time and cost, and enable a user to view knowledge graphs and tracing information in an integrated environment at the same time; further, the traceability information data is obtained, a knowledge graph is generated according to the traceability information data in the graph editor window, the knowledge graph comprises a plurality of entity nodes, and it is conceivable that the knowledge graph generated according to the real-time traceability information data state is embedded in the graph editor window under the condition that the front-end interface is ready, so that the user can edit and use the knowledge graph conveniently; further, in response to the click signal received by the graph editor window, determining the target entity node selected by the click signal, it is contemplated that the process of responding to the signal provides interactivity, allowing the user to select the particular entity node of interest to them by clicking; further, a plurality of relevant tracing segments are determined from tracing information data according to the target entity node, tracing segment cards corresponding to the plurality of relevant tracing segments are generated in a tracing segment window, so that a user can intuitively see tracing information relevant to the selected node after preliminary screening, and the visualization capability of the knowledge graph is further enhanced; further, the association coefficients of a plurality of tracing fragment cards are obtained, and a target tracing fragment card is determined from the plurality of tracing fragment cards according to the association coefficients, so that the effect of secondary screening is achieved, and a user is guided to view tracing information with higher association degree; further, the method and the system acquire the position information of the target entity node and the target tracing fragment card, perform connection processing on the target entity node and the target tracing fragment card according to the position information, and achieve an automatic knowledge tracing connection function, wherein after a user clicks one entity node through a front-end interface of the method and the system, the method and the system can automatically find out a plurality of tracing fragments related to the node from tracing information data and display the tracing fragments in a tracing fragment window in a card mode, meanwhile, the method and the system further analyze association coefficients among the tracing fragment cards, so that after determining which tracing fragment is most relevant or important, the position information of the entity node selected by the user and the tracing fragment card is automatically acquired, and a connection is drawn to intuitively display the association between the entity node selected by the user and the tracing fragment card.
In some embodiments, the method and the system have the advantages that the plurality of relevant tracing segments are determined from tracing information data according to the target entity node, tracing segment cards corresponding to the plurality of relevant tracing segments are generated in the tracing segment window, primary screening is performed, the association coefficients of the plurality of tracing segment cards are obtained, the target tracing segment cards are determined from the plurality of tracing segment cards according to the association coefficients, and secondary screening is further performed.
The above is a general description of steps S110 to S160, and steps S110 to S160 are described in detail below, respectively.
In step S110, a front-end interface is built through a front-end framework, and the front-end interface includes a graph editor window and a tracing fragment window; in some embodiments, the front end frame is a real front end frame, the real front end frame tracks page changes and performs efficient re-rendering by using a virtual DOM (Virtual DOM), and by applying interface modification to a virtual DOM, the real front end frame can perform actual DOM operations on only the part to be updated by comparing the difference between the virtual DOM and the actual DOM, so that the performance and rendering speed of an interface system are improved, for example, the speed of generating and automatically connecting a knowledge graph is improved, the system flow is improved, and particularly, the invention builds a front end page of the knowledge graph by using the front end frame (real. Js), including the display and editing of information such as nodes, edges and attributes, the interactive function of a graphic editor, and the like, and uses a visual library echartis to realize the data visual function, including the display and analysis of information such as nodes, edges and attributes, the screening and aggregation of data, and the like, so on, and the invention helps users to more intuitively understand the relationship between knowledge conveniently.
In step S120, tracing information data is obtained, and a knowledge graph is generated in a graph editor window according to the tracing information data, wherein the knowledge graph includes a plurality of entity nodes;
in some embodiments, the method and the system generate the knowledge graph according to the traceability information data in the graph editor window, enable a user to more intuitively know the relation between the data while realizing the knowledge traceability connection function, so that the data understanding capability and the use efficiency of the user are improved, support the interaction functions such as amplifying, shrinking and moving the position of the knowledge graph through the graph editor window corresponding to the graph editor functional component, further improve the user experience, and compared with conventional editing software such as Lucidchart, coggle and Visio, the knowledge traceability connection scheme based on the graph editor has stronger knowledge graph construction and visualization capability, and can more conveniently construct and display complex knowledge relations.
In some embodiments, trace information data supports retrieval of data from a data source (backend API). A user interface is provided that allows a user to select a data source and configure connection parameters.
In some embodiments, the information of nodes, edges, attributes and the like of the knowledge graph is stored in a database or other data storage schemes, so that subsequent query and analysis are facilitated, and specifically, the data structure of the nodes and the connecting lines in the defined knowledge graph is as follows:
the definition array categories represents different entity categories. For example: a central entity: may be the primary or core entity of the knowledge-graph; checking: possibly some kind of examination or procedure related to the main entity.
An array nodes is defined that describes nodes in the knowledge-graph. Each node contains the following attributes: category: an index pointing to a class in the category array, e.g., class 0 represents "center entity" and class 1 represents "check"; id: a unique identifier of the node; name: the name of the node; symbol size: may represent the size or importance of a node; value: the value or weight of the node; x, y: the coordinate position of the node in the knowledge graph, wherein the symbol and the value form a positive correlation.
In summary, the attributes of the nodes include the entity class categories and the desired attributes in the description array nodes.
An array links describing the links in the knowledge-graph is defined. Since each link links two nodes, it contains the following attributes: source: the starting node ID, target of the connection: the destination node ID of the connection.
Specifically, the data structure of the nodes and the connection lines in the knowledge graph may be: "const data= { categories: [ { name: 'center entity' }, { name: 'inspection' } ] nodes: [ { category:0id:"0"name:" atrial fibrillation "symbol: 19.12381value: 28.68555x: -266.82776y:299.6904}, { category:1id:"1"name:" inspection "symbol: 2.6666666666666665value:4x: -418.08344y:446.8853} ] links [ {" source ":"0"," target ":"1 "} ], in the example given, there are two nodes: the first node represents "atrial fibrillation", belonging to the category "central entity", ID "0"; the second node represents "check", belonging to the category "check", ID "1"; there is a connection line connecting the node with the ID of "0" (atrial fibrillation) and the node with the ID of "1" (examination), and by the above method, the knowledge-graph data can be stored.
Referring to fig. 2, fig. 2 is a flowchart of step S120 in fig. 1, in some embodiments, a plurality of entity nodes are connected by a relationship edge, and generating a knowledge graph according to traceability information data in a graph editor window may include, but is not limited to, steps S210 to S220.
Step S210, performing feature capturing processing on the traceability information data to obtain a plurality of entity features and relation features among the entity features, and obtaining weight coefficients of the entity features in a knowledge graph;
step S220, in the graph editor window, based on the ECharts visual library, generating entity nodes in the knowledge graph according to the entity characteristics and the weight coefficients, and generating relationship edges in the knowledge graph according to the relationship characteristics.
In some embodiments, through the steps S210 to S220, the graph editor based on the traceability information data may generate a visual knowledge graph, and display a plurality of entity nodes and relationship edges between them, and this visual manner may present complex traceability information in a concise and intuitive manner, and may help the user better understand the relationship and importance between the information, and may help the user to browse and analyze the association relationship of the traceability data more easily.
Referring to fig. 3, fig. 3 is a flowchart of step S220 in fig. 2, in some embodiments, generating entity nodes in the knowledge-graph according to entity characteristics and weight coefficients based on the echarties visualization library, and generating relationship edges in the knowledge-graph according to relationship characteristics may include, but is not limited to, steps S310 to S340.
Step S310, determining the node name of the entity node according to the entity characteristics;
step S320, determining the node size of the entity node according to the weight coefficient;
step S330, based on the ECharts visual library, node coordinates are allocated for the entity nodes, and the entity nodes are generated in the knowledge graph according to the node coordinates, the node names and the node sizes;
and S340, acquiring node coordinates of the entity nodes at the two ends of the relation edge according to the relation features, and generating the relation edge in the knowledge graph according to the node coordinates of the entity nodes at the two ends.
In some embodiments, the node sizes of the entity nodes are determined according to the weight coefficients, wherein the weight coefficients reflect the importance degree or the relevance of the entity in the knowledge graph, so according to the sizes of the weight coefficients, different node sizes can be allocated to the entity nodes so as to highlight important entities or specific associations, and by analyzing the relationship characteristics, two entity nodes connected by the relationship edge can be determined. And generating corresponding relation edges in the knowledge graph according to the node coordinates of the entity nodes, and displaying the relation types and attributes between the nodes at two ends.
In some examples, through steps S310 to S340, the embodiment of the echarties-based visualization library may generate a knowledge graph including entity nodes and relationship edges, and display the relationships and importance between the entities in a visual manner, so that the user may intuitively understand and analyze the information in the knowledge graph. In some embodiments, when the data visualization function is implemented in the graph editor, especially when the graph is connected with the information, feature capturing is a key step, wherein feature capturing refers to extracting key information in the data and mapping the key information to the graphic elements so as to display and edit the key information in the graph editor, and through the steps S210 to S340, the invention can obtain entity features and relationship features and directly display the entity features and relationship features on nodes, edges and other elements of the graph editor so that a user can more intuitively see the entity or edge corresponding relationship corresponding to each node.
In step S130, in response to the click signal received by the graph editor window, determining a target entity node selected by the click signal;
in some embodiments, the graph editor window is capable of determining the selected target entity node from the received click signal and performing subsequent corresponding processing and operations thereon.
In some embodiments, through the method of the invention, a user can click on specific traceable knowledge by clicking on a node, send out a traceability line from the knowledge, and perform dynamic display, wherein the traceability line is ended to a traceability segment; when other knowledge (nodes) are switched, the trace line of the last knowledge (node) disappears and is synchronously switched to the trace line of the current clicking knowledge (node), one knowledge (node) is continuously clicked for multiple times, and the trace line is only displayed once and is not switched among multiple continuous clicks.
In some embodiments, through the method of the invention, a user can also check the detailed information of the node by clicking the node, and the information can comprise attribute information such as the name, author, literature name, release time, source, tracing fragment and the like of the node.
In step S140, determining a plurality of relevant tracing segments from the tracing information data according to the target entity node, and generating tracing segment cards corresponding to the plurality of relevant tracing segments in a tracing segment window;
referring to fig. 4, fig. 4 is a flowchart of step S140 in fig. 1, in some embodiments, the trace information data includes a plurality of trace segments, and determining a plurality of relevant trace segments from the trace information data according to the target entity node may include, but is not limited to, steps S410 to S430.
Step S410, obtaining connection relation information of a target entity node in a knowledge graph;
step S420, determining adjacent nodes of the target entity node according to the connection relation information, and determining relation edges between the target entity node and the adjacent nodes;
step S430, determining the tracing segments of the entity features corresponding to the target entity node and the adjacent nodes as related tracing segments, and determining the tracing segments of the relationship features corresponding to the relationship edges as related tracing segments.
In some embodiments, the steps are used for determining a plurality of related tracing segments from the tracing information data according to the target entity node, wherein the plurality of related tracing segments comprise entity characteristic tracing segments of the target entity node and adjacent nodes thereof and relationship characteristic tracing segments of relationship edges, which are helpful for acquiring information related to the target entity node, further enriching the content of the tracing data and providing more comprehensive information support and analysis basis.
In step S150, obtaining association coefficients of a plurality of tracing fragment cards, and determining a target tracing fragment card from the plurality of tracing fragment cards according to the association coefficients;
referring to fig. 5, fig. 5 is a flowchart of step S150 in fig. 1, in some embodiments, obtaining association coefficients of a plurality of traceable fragment cards, and determining a target traceable fragment card from the plurality of traceable fragment cards according to the association coefficients may include, but is not limited to, steps S510 to S540.
Step S510, determining a relationship tracing fragment card corresponding to a plurality of relationship edges from a plurality of tracing fragment cards;
step S520, obtaining association weight coefficients of a plurality of relationship tracing fragment cards, wherein the association weight coefficients are weight coefficients of adjacent nodes corresponding to the relationship tracing fragment cards;
step S530, determining association coefficients of a plurality of relationship traceability segment cards according to the association weight coefficients;
and S540, determining the relation traceability fragment card with the association coefficient larger than the preset association threshold value as the target traceability fragment card.
In some embodiments, the association weight coefficient represents the importance degree or association degree between the relationship tracing fragment card and the adjacent node, and is used for measuring the influence of the relationship tracing fragment card on the connected entity node, namely, the greater the weight coefficient of the adjacent node is, the stronger the association between the adjacent node and the selected entity node is, so that the weight coefficient of the corresponding adjacent node can be determined as the association weight coefficient of the relationship tracing fragment card, and then secondary screening is performed to determine the target tracing fragment card, and the most relevant and important tracing fragment with the relationship between the entity nodes can be screened out from a plurality of tracing fragment cards through the process, so that the content and the association information of the target tracing fragment are further enriched, the more depth and accurate tracing information can be provided, the user can more comprehensively understand the relationship between the entity nodes, and more targeted analysis and decision are supported; in addition, by setting the association threshold and the weight coefficient, customized screening and sorting can be performed, and the understanding and grasping capability of the user on the association information in the knowledge graph is improved.
In step S160, the location information of the target entity node and the target tracing fragment card is taken, and the connection processing is performed on the target entity node and the target tracing fragment card according to the location information.
In some embodiments, the components of the traceability relation connection need to be positioned absolutely, so that the screen is fully supported, and therefore, all coordinate parameters transmitted from the business side, such as the position information of the target entity node and the target traceability fragment card, are coordinates with the upper left corner of the screen as the original point position.
Referring to fig. 6, fig. 6 is a flowchart of acquiring starting point position information, and in some embodiments, the position information of the target entity node includes starting point position information, and the steps of acquiring the starting point position information are as follows: and taking the left upper corner coordinate of the front end interface as an origin, acquiring click coordinate information of the click signal through an ECharts visual library, and acquiring starting point position information according to the click coordinate information.
The position information of the target traceable fragment card includes end position information, and the step of obtaining the end position information may include, but is not limited to, steps S610 to S630.
Step S610, obtaining card width information of a target traceability fragment card;
step S620, obtaining distance information between a plurality of target tracing segment cards and the top of a tracing segment window;
Step S630, obtaining end position information according to the card width information and the distance information.
Specifically, on the premise that the upper left corner coordinate of the front end interface is taken as the original point, the top of the tracing segment window is consistent with the top coordinate of the front end interface, so that the Y-axis coordinate of the end position can be obtained according to the distance information between the target tracing segment card and the top of the tracing segment window, and the right side of the tracing segment window is consistent with the right-side coordinate of the front end interface, and the X-axis coordinate of the end position can be obtained under the condition that the card width information of the target tracing segment card is obtained.
In some embodiments, through the steps S610 to S630, the end position information of the target traceability segment card can be obtained, so as to ensure the accuracy and the visualization effect of the connection processing, and enable the user to intuitively understand the association relationship between the entity node and the traceability segment. Meanwhile, the readability and user experience of the map can be improved by considering the width and the position layout of the card.
Referring to fig. 7, fig. 7 is a flowchart of step S160 in fig. 1, and in some embodiments, the connection processing of the target entity node and the target trace clip card according to the location information may include, but is not limited to, steps S710 to S730.
Step S710, determining a relationship type and a relationship strength according to the relationship features corresponding to the target traceability fragment cards;
step S720, determining line color parameters according to the relationship types and line form parameters according to the relationship intensities;
step S730, generating connection lines based on the ECharts visualization library according to the start position information, the end position information, the line color parameters and the line morphology parameters, so as to perform connection line processing.
In some embodiments, generating the connection lines based on the echartis visualization library according to the start position information, the end position information, the line color parameters, and the line morphology parameters to perform the connection line processing includes: by "const SVGNS= 'http:// www.w3.org/2000/svg'; ", define the namespace of the SVG to ensure that the browser properly parses the SVG elements; through "const sourceCoord = [ x, y ]; const targetCoord = [ [ x, y ], [ x, y ], [ x, y ] ]; "define start point coordinates (corresponding to start point position information) and end point coordinates arrays (corresponding to end point position information); by "const fragment=document.createdocumetfragment (); "create Document fragment, document fragment is a lightweight Document object, it is not a part of the true DOM tree, document object can be used for adding nodes, then add this Document fragment to the true DOM, this can improve the performance of carrying on the link processing, because many operations to DOM directly may cause many redraws and reflows; starting the loop by "for (let i=0, i < targetcode.length; i++), {.. and creates path elements using the SVG namespaces to define paths and call the function path.setattribute to set the attributes of the path elements: if the d attribute of the path is set, a curve from a starting point to an end point can be defined, and the grammar of the Bezier curve is used; calling to set the fill attribute as none, which can define that the path is not filled with any color; calling the attribute with the stroke set to define the line color of the path; the marker-end attribute is set, a mark is arranged at the end point of the indication path, an arrow is expected to be formed, the automatic connection function is completed through the steps, the adjustment of the line color parameters and the line form parameters can be realized, the change of the line style and direction is realized by automatically adjusting the thickness, the color, the arrow and the like of the line according to the attribute of the relationship, and the relationship of different types and intensities can be presented through flexible line color and form parameter control so as to reflect different relationship types and properties.
In some embodiments, when the longitudinal sliding window on the right side of the front end interface is rolled, the business side calculates the position of the tracing fragment card in real time to determine the end point of the arrow, and because the coordinate position of the node is known, the position of the node in the document object model dom can be obtained through the convertToPixel method, and because the position of the node is changed, the starting point position of the line also changes, so that when the node is clicked, the knowledge graph does not support the zoom-in and zoom-out and the movement position, and the click cancels the function of restoring after the link disappears.
Specifically, the tracing segment window comprises a longitudinal sliding window positioned on the right side of the front end interface, and after distance information between a plurality of target tracing segment cards and the top of the tracing segment window is obtained, the tracing segment window further comprises: under the condition that the longitudinal sliding window responds to the received sliding signal and performs sliding display processing on the plurality of tracing fragment cards, obtaining the longitudinal sliding distance of the plurality of tracing fragments; adjusting the distance information according to the longitudinal sliding distance; and obtaining the end position information of the target tracing fragment card according to the card width information and the adjusted distance information.
In some embodiments, after generating the knowledge-graph according to the traceability information data in the graph editor window, the method further includes: responding to the editing control signal received by the graph editor window, and performing editing control processing on the knowledge graph through a graph editor functional module deployed in the graph editor window; wherein the editing control process includes at least one of:
Scaling the knowledge graph;
adding, deleting and editing relation edges between the entity nodes and the plurality of entity nodes in the knowledge graph;
performing floating window display processing on attribute information of entity nodes and relation edges in the knowledge graph;
and searching the entity nodes in the knowledge graph to determine target entity nodes, and adjusting the visible range of the knowledge graph according to the position information of the target entity nodes.
Specifically, the editing control process performed by the graph editor function module deployed in the graph editor window may further include, but is not limited to, the following functions: firstly, a graph editor can determine knowledge elements of different types to be represented according to user requirements, and define the appearance and the attribute of nodes for each type, and compared with a conventional echartists open source framework, the graph editor is higher in automation degree and better in user experience; simultaneously, automatically generating a user-friendly graphical interface so that a user can easily create and edit nodes; secondly, allowing a user to draw connecting lines between the nodes and the traceability card and providing an automatic layout tool to ensure that the graph keeps clear and orderly appearance, supporting automatic arrangement, alignment and grouping of the nodes and the connecting lines, wherein conventional echartists only support automatic layout of the nodes and not support automatic layout of the connecting lines; in addition, a toolbar may be provided for zooming in and out nodes, full screen presentations, adding nodes and links, etc., so that a user may browse a large knowledge graph and allow the user to view historical versions of the knowledge graph to trace back the evolution of information, providing undo and redo functionality, and version comparison tools.
In some embodiments, the edit control process of knowledge graphs through graph editor function modules deployed in the graph editor window also allows users to configure the appearance of custom nodes and links through json to meet their needs and preferences. Custom options for colors, shapes, icons, etc. are provided and support importing nodes and links from external data sources to quickly build knowledge maps, allowing users to export maps into formats of images, PDFs, text, etc.
In some embodiments, through the graph editor function deployed in the graph editor window, a user may search for nodes in the graph editor by entering keywords in a search box, and the system may highlight nodes that match the keywords and move them into the visual range.
In some embodiments, through the graph editor function module deployed in the graph editor window, the user can scale the size of the graph editor using a mouse wheel, and can also move the entire graph editor by dragging the canvas, thereby helping the user to better view and operate a larger knowledge graph.
In summary, compared with the existing technical scheme using only open source echarts, the invention introduces the graph editor brought by the front end framework (act. Js), and the graph editor has the following functions of node and type definition, user-friendly graphical interface, connection creation and editing, tool bar and the like, so that the scheme of tracing the connection based on the knowledge of the graph editor can help a user to more clearly visualize and understand the source, evolution and association of information, allows the user to create, edit and manage graphical nodes on the graphical interface to represent different knowledge elements, and then uses the connection to connect the nodes to display the relationship among the nodes.
In a second aspect, referring to fig. 8, fig. 8 is a schematic diagram of a knowledge traceability connection system based on a graph editor according to an embodiment of the present invention, where the embodiment of the present invention provides a knowledge traceability connection system based on a graph editor, including: the interface building module 801 is configured to build a front-end interface through a front-end framework, where the front-end interface includes a graph editor window and a tracing fragment window; the knowledge graph generation module 802 is configured to obtain the traceability information data, and generate a knowledge graph in the graph editor window according to the traceability information data, where the knowledge graph includes a plurality of entity nodes; the entity node determining module 803 is configured to determine, in response to the click signal received by the graph editor window, a target entity node selected by the click signal; the tracing segment determining module 804 is configured to determine a plurality of relevant tracing segments from the tracing information data according to the target entity node, and generate tracing segment cards corresponding to the plurality of relevant tracing segments in a tracing segment window; the traceability card determining module 805 is configured to obtain association coefficients of a plurality of traceability fragment cards, and determine a target traceability fragment card from the plurality of traceability fragment cards according to the association coefficients; and the tracing information connection module 806 is configured to obtain the position information of the target entity node and the target tracing fragment card, and perform connection processing on the target entity node and the target tracing fragment card according to the position information.
Referring to fig. 9, fig. 9 is an interface schematic diagram of a knowledge traceability connection system based on a graph editor according to an embodiment of the invention; the title builds a front-end interface 900 through a front-end framework, wherein the front-end interface 900 comprises a graph editor window 910 and a tracing fragment window 920; the graph editor window 910 generates a knowledge graph according to the traceability information data and includes a plurality of entity nodes, the traceability fragment window 920 includes a related traceability fragment and a target traceability fragment card (for example, 921 to 923 in the graph), the target traceability fragment card includes specific traceability information (for example, 1 to 3 in the specific traceability information), in addition, the graph editor window 910 includes a graph editor toolbar 911, and a plurality of functional cases exist in the graph editor toolbar 911.
Acquiring traceability information data, and generating a knowledge graph in a graph editor window according to the traceability information data, wherein the knowledge graph comprises a plurality of entity nodes;
responding to the click signal received by the graph editor window, and determining a target entity node selected by the click signal;
determining a plurality of relevant tracing fragments from tracing information data according to a target entity node, and generating tracing fragment cards corresponding to the plurality of relevant tracing fragments in a tracing fragment window;
acquiring association coefficients of a plurality of tracing fragment cards, and determining a target tracing fragment card from the plurality of tracing fragment cards according to the association coefficients;
and acquiring the position information of the target entity node and the target tracing fragment card, and carrying out connection processing on the target entity node and the target tracing fragment card according to the position information.
In a third aspect, an embodiment of the present invention further provides an electronic device, including: the system comprises a memory, a processor, a program stored on the memory and capable of running on the processor, and a data bus for realizing connection communication between the processor and the memory, wherein the program realizes the knowledge traceability connection method based on the graph editor when being executed by the processor. The electronic equipment can be any intelligent terminal including a tablet personal computer, a vehicle-mounted computer and the like.
Referring to fig. 10, fig. 10 is a schematic hardware structure of an electronic device according to an embodiment of the present invention, where the electronic device includes:
the processor 1001 may be implemented by using a general-purpose CPU (central processing unit), a microprocessor, an application-specific integrated circuit (ApplicationSpecificIntegratedCircuit, ASIC), or one or more integrated circuits, etc. to execute related programs to implement the technical solution provided by the embodiments of the present invention;
the memory 1002 may be implemented in the form of read-only memory (ReadOnlyMemory, ROM), static storage, dynamic storage, or random access memory (RandomAccessMemory, RAM). The memory 1002 may store an operating system and other application programs, and when the technical solution provided in the embodiments of the present disclosure is implemented by software or firmware, relevant program codes are stored in the memory 1002, and the processor 1001 invokes a graph-editor-based knowledge traceability connection method for executing the embodiments of the present disclosure;
an input/output interface 1003 for implementing information input and output;
the communication interface 1004 is configured to implement communication interaction between the present device and other devices, and may implement communication in a wired manner (e.g. USB, network cable, etc.), or may implement communication in a wireless manner (e.g. mobile network, WIFI, bluetooth, etc.);
A bus 1005 for transferring information between the various components of the device (e.g., the processor 1001, memory 1002, input/output interface 1003, and communication interface 1004);
wherein the processor 1001, the memory 1002, the input/output interface 1003, and the communication interface 1004 realize communication connection between each other inside the device through the bus 1005.
In a fourth aspect, an embodiment of the present invention further provides a computer readable storage medium, where one or more programs are stored, and the one or more programs may be executed by one or more processors, so as to implement the graph-editor-based knowledge traceability connection method.
The memory, as a non-transitory computer readable storage medium, may be used to store non-transitory software programs as well as non-transitory computer executable programs. In addition, the memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory optionally includes memory remotely located relative to the processor, the remote memory being connectable to the processor through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
In summary, compared with the prior art, the knowledge traceability connection scheme based on the graph editor provided by the invention can be used for constructing a front-end interface through a front-end framework, acquiring traceability information data, generating a knowledge graph according to the traceability information data in a graph editor window, generating traceability fragment cards corresponding to a plurality of related traceability fragments in a traceability fragment window under the condition that target entity nodes selected by click signals are determined, determining target traceability fragment cards from the plurality of traceability fragment cards according to association coefficients, further acquiring the position information of the target entity nodes and the target traceability fragment cards, carrying out connection processing on the target entity nodes and the target traceability fragment cards according to the position information, further realizing an automatic traceability information connection function, solving the problem of lack of visual interaction between the knowledge graph and the knowledge traceability information, and improving the visualization capability of a knowledge graph system, so that a user can more quickly and effectively view the knowledge traceability information.
The embodiments described in the embodiments of the present invention are for more clearly describing the technical solutions of the embodiments of the present invention, and do not constitute a limitation on the technical solutions provided by the embodiments of the present invention, and those skilled in the art can know that, with the evolution of technology and the appearance of new application scenarios, the technical solutions provided by the embodiments of the present invention are equally applicable to similar technical problems.
It will be appreciated by those skilled in the art that the solutions shown in fig. 1 to 8 do not constitute a limitation of the embodiments of the present invention, and may include more or fewer steps than shown, or may combine certain steps, or different steps.
The terms "first," "second," "third," "fourth," and the like in the description of the invention and in the above figures, if any, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Those of ordinary skill in the art will appreciate that all or some of the steps of the methods disclosed above, corresponding systems, may be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer readable storage media (or non-transitory media) and communication media (or transitory media). The term computer-readable storage medium includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information, such as computer-readable instructions, data structures, program modules or other data, as known to those skilled in the art. Computer-readable storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer. Furthermore, as is well known to those of ordinary skill in the art, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media.
The preferred embodiments of the present invention have been described above with reference to the accompanying drawings, and are not thereby limiting the scope of the claims of the embodiments of the present invention. Any modifications, equivalent substitutions and improvements made by those skilled in the art without departing from the scope and spirit of the embodiments of the present invention shall fall within the scope of the claims of the embodiments of the present invention.
Claims (12)
1. The knowledge traceability connecting method based on the graph editor is characterized by comprising the following steps of:
building a front-end interface through a front-end framework, wherein the front-end interface comprises a graph editor window and a tracing fragment window;
acquiring tracing information data, and generating a knowledge graph in the graph editor window according to the tracing information data, wherein the knowledge graph comprises a plurality of entity nodes;
responding to a click signal received by the graph editor window, and determining a target entity node selected by the click signal;
determining a plurality of related tracing fragments from the tracing information data according to the target entity node, and generating tracing fragment cards corresponding to the plurality of related tracing fragments in the tracing fragment window;
acquiring association coefficients of a plurality of tracing fragment cards, and determining a target tracing fragment card from the plurality of tracing fragment cards according to the association coefficients;
And acquiring the position information of the target entity node and the target tracing fragment card, and carrying out connection processing on the target entity node and the target tracing fragment card according to the position information.
2. The graph editor-based knowledge traceability connection method of claim 1, wherein a plurality of the entity nodes are connected by a relationship edge, the generating a knowledge graph according to the traceability information data in the graph editor window comprises:
performing feature capturing processing on the traceability information data to obtain a plurality of entity features and relation features among the entity features, and obtaining weight coefficients of the entity features in the knowledge graph;
in the graph editor window, based on an ECharts visual library, generating the entity nodes in the knowledge graph according to the entity characteristics and the weight coefficients, and generating the relationship edges in the knowledge graph according to the relationship characteristics.
3. The graph editor-based knowledge traceability wiring method of claim 2 wherein the generating the entity nodes in the knowledge-graph from the entity features and the weight coefficients and the generating the relationship edges in the knowledge-graph from the relationship features based on the echorts-based visualization library comprises:
Determining the node name of the entity node according to the entity characteristics;
determining the node size of the entity node according to the weight coefficient;
based on an ECharts visual library, node coordinates are distributed for the entity nodes, and the entity nodes are generated in a knowledge graph according to the node coordinates, the node names and the node sizes;
and acquiring node coordinates of the entity nodes at two ends of the relation edge according to the relation features, and generating the relation edge in a knowledge graph according to the node coordinates of the entity nodes at two ends.
4. The graph editor-based knowledge traceability connection method of claim 2, wherein the traceability information data includes a plurality of traceability fragments, and the determining, according to the target entity node, a plurality of related traceability fragments from the traceability information data includes:
acquiring connection relation information of the target entity node in the knowledge graph;
determining adjacent nodes of the target entity node according to the connection relation information, and determining relation edges between the target entity node and the adjacent nodes;
and determining the tracing segments of the entity features corresponding to the target entity node and the adjacent node as related tracing segments, and determining the tracing segments of the relationship features corresponding to the relationship edges as the related tracing segments.
5. The knowledge traceability link method based on a graph editor of claim 4, wherein the obtaining the association coefficients of the plurality of traceability segment cards and determining the target traceability segment card from the plurality of traceability segment cards according to the association coefficients comprises:
determining a relationship tracing fragment card corresponding to a plurality of relationship edges from a plurality of tracing fragment cards;
acquiring association weight coefficients of a plurality of relationship tracing fragment cards, wherein the association weight coefficients are weight coefficients of the adjacent nodes corresponding to the relationship tracing fragment cards;
determining association coefficients of a plurality of relationship traceability fragment cards according to the association weight coefficients;
and determining the relationship tracing fragment card with the association coefficient larger than a preset association threshold value as a target tracing fragment card.
6. The graph-editor-based knowledge traceability link method of claim 1 wherein the location information of the target entity node includes start location information and the location information of the target traceability segment card includes end location information;
the step of acquiring the starting point position information is as follows:
The left upper corner coordinate of the front end interface is taken as an origin, click coordinate information of the click signal is obtained through an ECharts visual library, and the starting point position information is obtained according to the click coordinate information;
the step of acquiring the starting point position information is as follows:
acquiring card width information of the target traceability fragment card;
obtaining distance information between a plurality of target tracing fragment cards and the top of the tracing fragment window;
and obtaining the end position information according to the card width information and the distance information.
7. The knowledge traceability link method based on a graph editor according to claim 6, wherein the link processing of the target entity node and the target traceability segment card according to the location information includes:
determining a relationship type and a relationship strength according to the relationship features corresponding to the target traceability fragment card;
determining line color parameters according to the relation types and line form parameters according to the relation strength;
and generating connecting lines according to the starting point position information, the end point position information, the line color parameters and the line morphological parameters based on the ECharts visual library so as to perform connecting line processing.
8. The knowledge traceability connection method based on a graph editor of claim 6, wherein the traceability segment window includes a longitudinal sliding window located on the right side of the front end interface, and further comprising, after the obtaining the distance information between the plurality of target traceability segment cards and the top of the traceability segment window:
under the condition that the longitudinal sliding window responds to the received sliding signals and performs sliding display processing on a plurality of tracing fragment cards, obtaining longitudinal sliding distances of a plurality of tracing fragments;
adjusting the distance information according to the longitudinal sliding distance;
and obtaining the end position information of the target tracing fragment card according to the card width information and the adjusted distance information.
9. The graph editor-based knowledge traceability connection method of claim 1, further comprising, after the generating a knowledge graph in the graph editor window according to the traceability information data:
responding to the editing control signal received by the graph editor window, and performing editing control processing on the knowledge graph through a graph editor functional module deployed in the graph editor window;
Wherein the editing control process includes at least one of:
scaling the knowledge graph;
adding, deleting and editing relation edges between the entity nodes and a plurality of entity nodes in the knowledge graph;
performing floating window display processing on attribute information of the entity nodes and the relation edges in the knowledge graph;
and searching the entity nodes in the knowledge graph to determine target entity nodes, and adjusting the visible range of the knowledge graph according to the position information of the target entity nodes.
10. The knowledge traceability connecting line system based on the graph editor is characterized by comprising:
the interface building module is used for building a front-end interface through a front-end framework, and the front-end interface comprises a graph editor window and a tracing fragment window;
the knowledge graph generation module is used for acquiring the traceability information data and generating a knowledge graph in the graph editor window according to the traceability information data, wherein the knowledge graph comprises a plurality of entity nodes;
the entity node determining module is used for responding to the click signal received by the graph editor window and determining a target entity node selected by the click signal;
The tracing segment determining module is used for determining a plurality of related tracing segments from the tracing information data according to the target entity node and generating tracing segment cards corresponding to the plurality of related tracing segments in the tracing segment window;
the traceability card determining module is used for acquiring the association coefficients of the plurality of traceability fragment cards and determining target traceability fragment cards from the plurality of traceability fragment cards according to the association coefficients;
and the traceability information connecting module is used for acquiring the position information of the target entity node and the target traceability fragment card and carrying out connecting processing on the target entity node and the target traceability fragment card according to the position information.
11. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the graph editor-based knowledge traceability wiring method of any of claims 1 to 9 when the computer program is executed by the processor.
12. A computer readable storage medium, storing a computer program which, when executed by a processor, implements the graph editor-based knowledge traceability wiring method of any of claims 1 to 9.
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