A What-You-See-Is-What-You-Get Graph Data Construction Method

Abstract

The present invention discloses a method for constructing what-you-see-is-what-you-get graph data, which abstracts the composition logic into several independent components. Each component is abstracted as a single node task in a task flow canvas, and each node task is set with the same input and output data structure. Each node task in the task flow is executed sequentially in order. When there are branches in the task flow, they are executed in parallel. The present invention supports constructing a graph schema in a visual and interactive manner. The visual composition function provides a dataset access and editing panel, and through the canvas tool and the configuration panel, nodes and edge structures are quickly selected and configured from the business data of the dataset, so as to construct an association graph required by the business. After the graph schema is visually constructed, graph data can be generated based on the business data corresponding to the dataset for direct use by the graph model. The visual composition function also supports the construction of both isomorphic graphs and heterogeneous graphs.

Description

Technical Field

[0001] The present invention relates to the technical field of graphic data processing, and in particular to a what-you-see-is-what-you-get graphic data construction method. Background Art

[0002] In recent years, AI technology has developed rapidly. A major shortcoming of traditional AI technology is that it only uses individual attribute information and is difficult to learn the association information between individuals. Graph AI technology realizes the effective utilization of association information by introducing the ability of graphs. At the same time, combined with the expression ability of graphs, it is more accurate, intuitive, comprehensive, and logical than traditional AI technology. In order to use the capabilities of Graph AI, it is first necessary to construct a traditional dataset with associations between each other into a graph dataset.

[0003] Most existing graph database software can only manage existing and constructed graph data. Usually, some scripts or graph database query statements are also used to directly create nodes and edges. However, this operation method has a relatively high threshold for users. It is necessary to master some basic programming knowledge or a certain amount of graph query syntax knowledge. Summary of the Invention

[0004] Aiming at the problem of the relatively high operation threshold of the existing technology, the present invention proposes a what-you-see-is-what-you-get graphic data construction method, which enables users to quickly construct the required graph dataset from the dataset through some simple configurations in a simple and visual interactive manner.

[0005] The technical solution adopted by the present invention is as follows:

[0006] A what-you-see-is-what-you-get graphic data construction method abstracts the composition logic into several independent components. Each component is abstracted as a single node task in a task flow canvas, and each node task is set with the same input and output data structures; each node task in the task flow is executed sequentially in order, and when there are branches in the task flow, they are executed in parallel.

[0007] Furthermore, the composition logic is encapsulated into independent components, and data flow during the composition process is achieved through related operations, and the related operations include dragging and connecting.

[0008] Furthermore, during the composition process, the composition task status is updated in real time to display the current task progress.

[0009] Furthermore, the component is provided with a plurality of data input interfaces and a data output interface. The data input interfaces are used to input datasets, and the data output interface is used to output the graph dataset after successful composition.

[0010] Further, the number of the data input interfaces can be increased or decreased to dynamically increase or decrease the input data.

[0011] Further, the editing of the graph schema information is configured through the structure of the dynamic canvas, and the graph structure information visually displayed through the UI represents the schema information of the graph data.

[0012] Further, when editing nodes and edges, the schema information of the input data set is automatically associated.

[0013] Further, after the graph data is successfully constructed, the currently constructed graph data set can be queried on the current graph data through a form or a Cypher statement.

[0014] Further, the method for querying through a form is as follows: select and set query conditions to construct a query request logically corresponding to a Cypher statement for querying.

[0015] Further, the query results can configure the title fields and colors according to the node type and edge type, and configure different colors according to the conditions of a single attribute.

[0016] The beneficial effects of the present invention are as follows:

[0017] (1) The present invention abstracts the graph composition logic into several independent components, each component is abstracted as a single node task in a task flow canvas, and each node task is set with the same input and output data structures; each node task in the task flow is executed sequentially in order, and when there are branches in the task flow, they are executed in parallel, which can accelerate the execution speed of the entire task flow.

[0018] (2) The present invention supports constructing a graph schema in a visual and interactive manner. The visual graph composition function provides a data set access and editing panel, and quickly selects and configures the node and edge structures from the business data of the data set through the canvas tool and the configuration panel, so as to construct an associated graph required by the business. After the graph Schema is visually constructed, graph data can be generated based on the business data corresponding to the data set for direct use by the graph model. The visual graph composition function also supports the construction of both isomorphic graphs and heterogeneous graphs. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 is a schematic diagram of the components and their corresponding menu columns of an embodiment of the present invention.

[0020] Figure 2 is a schematic diagram of form query of an embodiment of the present invention.

[0021] Figure 3 is a schematic diagram of the graph composition components and their input data sets of an embodiment of the present invention.

[0022] Figure 4 It is a schematic diagram of node information configuration according to an embodiment of the present invention.

[0023] Figure 5 It is a schematic diagram of edge information configuration according to an embodiment of the present invention.

[0024] Figure 6 It is a schematic diagram of conditional query according to an embodiment of the present invention.

[0025] Figure 7 It is a schematic diagram of statement query according to an embodiment of the present invention. Detailed implementation manners

[0026] For a clearer understanding of the technical features, objectives, and effects of the present invention, the specific implementation manners of the present invention are now described. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention, that is, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0027] This embodiment provides a what-you-see-is-what-you-get graph data construction method, which abstracts the graphing logic into several independent components. Each component is abstracted as a single node task in a task flow canvas, and each node task is set with the same input and output data structures; each node task in the task flow is executed sequentially in order, and when there are branches in the task flow, they are executed in parallel.

[0028] This embodiment encapsulates the graphing logic into independent components, and realizes the data flow in the graphing process through simple operations such as dragging and connecting lines. During the graphing process, the graphing task status will be updated in real time to display the current task progress. As Figure 1 shown, this component is provided with a data input interface and a data output interface, where the data input interface is used to input a data set, and the data output interface is used to output the graph data set after successful graphing. Preferably, the number of the data input interfaces can be increased or decreased to realize dynamically increasing or decreasing the input data.

[0029] In this embodiment, the editing of the graph schema information also uses a structure similar to a dynamic canvas for configuration, and can intuitively represent the schema information of the graph data through the graph structure information displayed by the UI. When editing nodes and edges, the schema information of the input data set is automatically associated. It is also relatively easy to directly deduce the final schema information of the upcoming generated graph through the configuration information.

[0030] Preferably, after the graph data is successfully constructed, the currently constructed graph data set can be queried on the current graph data through a form or Cypher statement. As Figure 2 shown, the method of querying through a form is as follows: select and set query conditions to construct a query request that logically corresponds to a Cypher statement for querying, thus providing a simpler and more direct query UI for some users who are not familiar with Cypher syntax.

[0031] Preferably, in order to make the graph exploration results more intuitive and closer to the business logic, the title fields and colors can be configured according to the node type and edge type, and different colors can also be configured according to the conditions of a single attribute.

[0032] Specifically, the actual implementation process of the graph data construction method in this embodiment can be as follows:

[0033] 1. As Figure 3 shown, use a node data set and an edge data set as input and output respectively to construct a workflow;

[0034] 2. As Figure 4 and Figure 5 shown, configure the graph composition components and configure them through the structure of an intuitive graph association relationship during the component configuration process;

[0035] 3. As Figure 6 and Figure 7 shown, after the graph composition is completed, data exploration can be directly performed on the current graph data set, or the current graph data can be queried using Cypher statements.

[0036] The above is only the preferred embodiment of the present invention. It should be understood that the present invention is not limited to the form disclosed herein, should not be regarded as excluding other embodiments, but can be used in various other combinations, modifications and environments, and can be changed within the scope of the concept described herein through the above teachings or the technology or knowledge in related fields. And the changes and variations made by those skilled in the art that do not depart from the spirit and scope of the present invention should all be within the protection scope of the appended claims of the present invention.

Claims

1. A what-you-see-is-what-you-get graph data construction method, characterized in that, Abstract the composition logic into several independent components, and abstract each component into a single node task in a task flow canvas. Each node task is set with the same input and output data structures; each node task in the task flow is executed sequentially in order, and when there are branches in the task flow, they are executed in parallel; The composition logic is encapsulated into independent components, and the data flow during the composition process is realized through related operations, and the related operations include dragging and connecting lines; During the composition process, the composition task status is updated in real time to display the current task progress; The component is provided with multiple data input interfaces and one data output interface. The data input interface is used to input data sets, and the data output interface is used to output the graph data set after successful composition; The editing of the graph schema information is configured through the structure of the dynamic canvas, and the schema information of the graph data is intuitively represented by the graph structure information displayed through the UI.

2. The what-you-see-is-what-you-get map data construction method according to claim 1, characterized in that The number of the data input interfaces can be increased or decreased to realize dynamically increasing or decreasing the input data.

3. The what-you-see-is-what-you-get map data construction method according to claim 1, wherein When editing nodes and edges, automatically associate the schema information of the input data set.

4. The what-you-see-is-what-you-get graphic data construction method according to any one of claims 1-3, characterized in that After the graph data is successfully constructed, it is possible to query the currently constructed graph data set on the current graph data by means of a form or a Cypher statement.

5. The what-you-see-is-what-you-get map data construction method according to claim 4, characterized in that, The method for querying by means of a form is: select and set query conditions to construct a query request that is logically corresponding to the Cypher statement for querying.

6. The what-you-see-is-what-you-get map data construction method according to claim 4, wherein The query results can configure the title fields and colors according to the node type and edge type, and configure different colors according to the conditions of a single attribute.

Images