CN112632194A - Data graphic visualization relation representation method, device, equipment and storage medium - Google Patents
Data graphic visualization relation representation method, device, equipment and storage medium Download PDFInfo
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Abstract
The invention relates to big data technology, and discloses a method for representing a graphic visualization relationship of data, which comprises the following steps: dividing an original data set into a plurality of sub data sets according to types, and sequentially setting Y-axis coordinates for elements in each sub data set according to data distribution of the original data set in a database to obtain a first data set; dividing the first data set into a source data set and a plurality of target data sets; setting X-axis coordinates for elements in the source data set and the target data set according to the relationship between the elements in the first data set to obtain a second data set; and outputting the graphic visualization relation of the original data set according to the X-axis coordinate and the Y-axis coordinate of each element in the second data set. The invention also relates to a blockchain technique, and the source data set and the target data set can be stored in a blockchain. The method and the device can improve the efficiency of the graphic visualization scheme for displaying the complex relationship.
Description
Technical Field
The invention relates to the technical field of big data, in particular to a method and a device for representing a graphic visualization relationship of data, electronic equipment and a computer readable storage medium.
Background
Currently, there are two main types of graphical visual representations of complex relationships: one is tree display and the other is chart display. When the tree is displayed, the parent-level elements and the child-level elements at the same level cannot be cross-associated, so that the specific relationship between the parent-level elements at the same level cannot be displayed. The chart shows that when the number of elements is large and the relationship is complex and various, the relationship among the elements cannot be rapidly and clearly shown.
Disclosure of Invention
The invention provides a method and a device for representing a graphic visualization relationship of data, electronic equipment and a computer readable storage medium, and mainly aims to provide a method for displaying a graphic visualization scheme of a complex relationship more efficiently.
In order to achieve the above object, the present invention provides a method for representing a graphical visualization relationship of data, including:
dividing an original data set into a plurality of sub data sets according to types, and sequentially setting Y-axis coordinates for elements in each sub data set according to data distribution of the original data set in a database to obtain a first data set;
dividing the first data set into a source data set and a plurality of target data sets;
setting X-axis coordinates for elements in the source data set and the target data set according to the relationship between the elements in the first data set to obtain a second data set;
and outputting the graphic visualization relation of the original data set according to the X-axis coordinate and the Y-axis coordinate of each element in the second data set.
Optionally, the sequentially setting Y-axis coordinates for the elements in each sub data set according to the data distribution of the original data set in the database includes:
selecting one subdata set of the subdata sets to obtain all elements contained in the subdata set;
sorting the elements of the sub data set according to the location distribution of the elements in the database;
setting Y-axis coordinates for each element in the subdata set according to the sorting result;
and selecting a next subdata set, sequencing elements in the subdata set, and setting a Y-axis coordinate according to a sequencing result.
Optionally, the dividing the first data set into a source data set and a plurality of target data sets includes:
and searching a source node in the first data set to obtain a source data set.
And searching the target nodes in the first data set according to the relationship between the source node and other elements to obtain a plurality of target data sets.
Optionally, the setting, according to a relationship between elements in the first data set, X-axis coordinates for elements in the source data set and the target data set includes:
dividing the source data set into a plurality of source data subsets according to types;
sequentially selecting one of the source data subsets;
setting X-axis coordinates for elements in the source data subset, and selecting a source node in the source data subset;
selecting a target node having a direct sub-relationship with the source node in a target data set corresponding to the source node to obtain a subclass element set;
sorting the elements in the subclass element set, and setting X-axis coordinates for the elements in the subclass element set according to a sorting result;
updating the subclass element set until the source data subset and the corresponding element of the target data set are set to be X-axis coordinates;
and judging whether each source data subset is selected completely or not until the X-axis coordinates of elements in the source data set and the target data sets are set.
Optionally, the updating the child class element set includes:
selecting a target node in the target data set, wherein the target node has a direct sub-relationship with the elements of the subclass element set, and the target node is used as an element of the subclass element set;
and sequencing the elements in the subclass element set, and setting X-axis coordinate values for the elements in the subclass element set according to a sequencing result.
In order to solve the above problem, the present invention further provides an apparatus for graphically visualizing relational representation of data, the apparatus comprising:
the Y coordinate setting module is used for dividing the original data set into a plurality of sub data sets according to types, and sequentially setting Y-axis coordinates for elements in each sub data set according to the data distribution of the original data set in the database to obtain a first data set;
a data partitioning module for partitioning the first data set into a source data set and a plurality of target data sets;
an X coordinate setting module, configured to set X-axis coordinates for elements in the source data set and the target data set according to a relationship between the elements in the first data set, so as to obtain a second data set;
and the graph relation output module is used for outputting the graph visualization relation of the original data set according to the X-axis coordinate and the Y-axis coordinate of each element in the second data set.
Optionally, when sequentially setting Y-axis coordinates for elements in each sub data set according to the data distribution of the original data set in the database, the Y-coordinate setting module performs the following operations:
selecting one subdata set of the subdata sets to obtain all elements contained in the subdata set;
sorting the elements of the sub data set according to the location distribution of the elements in the database;
setting Y-axis coordinates for each element in the subdata set according to the sorting result;
and selecting a next subdata set, sequencing elements in the subdata set, and setting a Y-axis coordinate according to a sequencing result.
Optionally, the data dividing module is specifically configured to:
and searching a source node in the first data set to obtain a source data set.
And searching the target nodes in the first data set according to the relationship between the source node and other elements to obtain a plurality of target data sets.
In order to solve the above problem, the present invention also provides an electronic device, including:
a memory storing at least one instruction; and
and the processor executes the instructions stored in the memory to realize the graphical visualization relation representation method of the data.
In order to solve the above problem, the present invention further provides a computer-readable storage medium, which includes a data storage area and a program storage area, wherein the data storage area stores data, and the program storage area stores a computer program, and when the computer program is executed by a processor, the computer program implements the method for representing the graphic visualization relationship of the data.
The method comprises the steps of dividing an original data set into a plurality of sub data sets according to types, sequentially setting Y-axis coordinates for elements in each sub data set according to data distribution of the original data set in a database to obtain a first data set, and displaying specific relations among the same-level elements by utilizing Y axes distributed in the database; dividing the first data set into a source data set and a plurality of target data sets, reducing the data amount processed by a computer each time, improving the efficiency and facilitating the subsequent calculation; according to the relation between the elements in the first data set, setting X-axis coordinates for the elements in the source data set and the target data set to obtain a second data set, and when the number of the elements is large, the calculation amount can be reduced, and the working efficiency is improved; and outputting the graphic visualization relation of the original data set according to the X-axis coordinate and the Y-axis coordinate of each element in the second data set, so that the graphic visualization relation is displayed in a clearer and more intuitive way, and the user can understand the graphic visualization relation conveniently. Therefore, the method, the device and the computer readable storage medium for representing the graphic visualization relationship of the data can improve the efficiency of displaying the graphic visualization scheme of the complex relationship.
Drawings
Fig. 1 is a schematic flow chart of a method for representing graphical visualization relationships of data according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating a method for setting a Y coordinate of an element according to an embodiment of the present invention;
fig. 3 is a schematic flowchart of a data set partitioning method according to an embodiment of the present invention;
FIG. 4 is a flowchart illustrating a method for setting an X coordinate of an element according to an embodiment of the present invention;
FIG. 5 is a block diagram of an apparatus for graphical visualization of relational representation of data according to an embodiment of the present invention;
fig. 6 is a schematic internal structural diagram of an electronic device implementing a method for graphical visualization of relational representation of data according to an embodiment of the present invention;
the implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The execution subject of the graphical visualization relationship representation method for data provided by the embodiment of the present application includes, but is not limited to, at least one of electronic devices such as a server and a terminal that can be configured to execute the method provided by the embodiment of the present application. In other words, the method for graphically visualizing the relational representation of the data may be performed by software or hardware installed in the terminal device or the server device, and the software may be a block chain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like.
Referring to fig. 1, a flowchart of a rating method based on an algorithm model according to an embodiment of the present invention is shown. In this embodiment, the method for representing the graphical visualization relationship of data includes:
and S1, dividing the original data set into a plurality of sub data sets according to types, and sequentially setting Y-axis coordinates for elements in each sub data set according to the data distribution of the original data set in the database to obtain a first data set.
In the embodiment of the present invention, the original data set includes many elements and association relationships between the elements. Preferably, in this embodiment of the present invention, the raw data set may be obtained from a preset database. Wherein the database is a graphical database that stores structured data on a network (mathematically called a graph) rather than in tables, storing elements and relationships between elements, such as the neo4j database.
Preferably, the embodiment of the present invention obtains the original data set from a preset database by the following method:
connecting the database through a built-in interface which is constructed in advance;
and inquiring in the database according to preset data screening conditions to obtain the original data set.
Further, in the embodiment of the present invention, the original data set is divided by types through the pre-constructed data processing packet, data of the same type in the original data set is aggregated to obtain a plurality of sub data sets, and the amount of data that needs to be processed by the computer system at a time is reduced.
Preferably, the data processing package is a NumPy-based tool that incorporates a large number of libraries and some standard data models to efficiently manipulate large data sets.
In detail, referring to fig. 2, the sequentially setting Y-axis coordinates for the elements in each sub data set according to the data distribution of the original data set in the database includes:
s21, sequentially selecting one of the sub data sets to obtain all elements contained in the sub data set;
s22, sorting the elements of the sub data set according to the position distribution of the elements in the database;
s23, setting a Y-axis coordinate for each element in the sub-data set according to the sorting result, for example, the Y-axis coordinate of the element arranged at the first position may be set to 1, and the Y-axis coordinates of the following elements are sequentially added with 1;
and S24, judging whether each sub data set is selected completely, returning to the step S21 until each sub data set is selected completely and each element in each sub data set is provided with a Y-axis coordinate, and executing S25 to combine all sub data sets to obtain a first data set.
Wherein the sorting of the elements of the sub data set according to the location distribution of the elements in the database is performed sequentially according to the high-low condition of the locations of the elements in the database.
In the embodiment of the invention, the Y coordinate value of the element in the first data set is positively correlated according to the position distribution in the database.
And S2, dividing the first data set into a source data set and a plurality of target data sets.
In detail, referring to fig. 3, the S2 includes:
s30, searching a source node in the first data set to obtain a source data set;
s31, searching the target nodes in the first data set according to the relationship between the source nodes and other elements to obtain a plurality of target data sets.
The source node is an element of the first data set which does not have a parent element except the source node, and if the element is in family relation, the first person on the family tree is the source node; the target node is other elements except the source node in all elements contained in one relationship; the source data set comprises a plurality of source nodes, and each target data set comprises a plurality of target nodes which are associated with one source node. The source node set and the target data set are relatively large in data size, and the blockchain has high throughput, can process a large amount of data at a time, and can be stored in nodes of the blockchain.
Preferably, in the embodiment of the present invention, the source node and the target node in the first data set are searched through a preset data processing packet.
And S3, setting X-axis coordinates for the elements in the source data set and the target data set according to the relationship between the elements in the first data set, and obtaining a second data set.
In detail, referring to fig. 4, the S3 includes:
s41, dividing the source data set into a plurality of source data subsets according to types;
s42, sequentially selecting one of the source data subsets;
s43, setting X-axis coordinates for elements in the source data subset, and selecting a source node in the source data subset;
s44, selecting a target node having a direct sub-relationship with the source node in a target data set corresponding to the source node to obtain a subclass element set;
s45, sorting the elements in the subclass element set, and setting X-axis coordinates for the elements in the subclass element set according to a sorting result;
s46, updating the subclass element set until the X-axis coordinates of the elements of the source data subset and the corresponding target data set are set;
s47, determining whether each of the source data subsets has been selected, and returning to S42 until the X-axis coordinates of the elements in the source data set and the target data sets are set, and obtaining and outputting a second data set in S48.
Further, the updating the child class element set includes: selecting a target node in the target data set, wherein the target node has a direct sub-relationship with the elements of the subclass element set, and the target node is used as an element of the subclass element set; and sequencing the elements in the subclass element set, and setting X-axis coordinate values for the elements in the subclass element set according to a sequencing result.
Preferably, the embodiment of the present invention sets the X-axis coordinate for the element in the source data subset according to the position distribution of the element in the database; the elements in the child class element set are sorted according to the priority of the association relationship between each element and the parent class element to which the element belongs.
In the embodiment of the present invention, the source data set and the elements of the plurality of target data sets are merged to obtain a second data set, and both the X-axis coordinate and the Y-axis coordinate of the elements in the second data set are generated.
And S4, outputting the graphic visualization relation of the original data set according to the X-axis coordinate and the Y-axis coordinate of each element in the second data set.
In detail, according to the X-axis coordinate and the Y-axis coordinate of each element in the second data set, each element is displayed in a preset coordinate system as a graphic mark of a dot, and the association relationship between each element is connected with each element as a graphic mark of a solid line, so as to form a graphic visualization relationship of the original data set, and output the graphic visualization relationship.
The method comprises the steps of dividing an original data set into a plurality of sub data sets according to types, sequentially setting Y-axis coordinates for elements in each sub data set according to data distribution of the original data set in a database to obtain a first data set, and displaying specific relations among the same-level elements by utilizing Y axes distributed in the database; dividing the first data set into a source data set and a plurality of target data sets, reducing the data amount processed by a computer each time, improving the efficiency and facilitating the subsequent calculation; according to the relation between the elements in the first data set, setting X-axis coordinates for the elements in the source data set and the target data set to obtain a second data set, and when the number of the elements is large, the calculation amount can be reduced, and the working efficiency is improved; and outputting the graphic visualization relation of the original data set according to the X-axis coordinate and the Y-axis coordinate of each element in the second data set, so that the graphic visualization relation is displayed in a clearer and more intuitive way, and the user can understand the graphic visualization relation conveniently. Therefore, the method, the device and the computer readable storage medium for representing the graphic visualization relationship of the data can improve the efficiency of displaying the graphic visualization scheme of the complex relationship.
FIG. 5 is a functional block diagram of the data graphical visualization relationship representation apparatus according to the present invention.
The graphical visualization relationship representation apparatus 100 of data according to the present invention can be installed in an electronic device. According to the realized functions, the data graph visualization relation representation device can comprise a Y coordinate setting module 101, a data dividing module 102, an X coordinate setting module 103 and a graph relation output module 104. A module according to the present invention, which may also be referred to as a unit, refers to a series of computer program segments that can be executed by a processor of an electronic device and that can perform a fixed function, and that are stored in a memory of the electronic device.
In the present embodiment, the functions regarding the respective modules/units are as follows:
the Y coordinate setting module 101 is configured to divide an original data set into a plurality of sub data sets according to types, and sequentially set Y-axis coordinates for elements in each sub data set according to data distribution of the original data set in a database to obtain a first data set;
the data dividing module 102 is configured to divide the first data set into a source data set and a plurality of target data sets;
the X coordinate setting module 103 is configured to set X-axis coordinates for the elements in the source data set and the target data set according to a relationship between the elements in the first data set, so as to obtain a second data set;
the graph relationship output module 104 is configured to output a graph visualization relationship of the original data set according to the X-axis coordinate and the Y-axis coordinate of each element in the second data set.
In detail, the specific implementation steps of each module of the data graphical visualization relation representation device are as follows:
the Y coordinate setting module 101 is configured to divide an original data set into a plurality of sub data sets according to types, and sequentially set Y-axis coordinates for elements in each sub data set according to data distribution of the original data set in a database, so as to obtain a first data set.
In the embodiment of the present invention, the original data set includes many elements and association relationships between the elements. Preferably, in this embodiment of the present invention, the raw data set may be obtained from a preset database. Wherein the database is a graphical database that stores structured data on a network (mathematically called a graph) rather than in tables, storing elements and relationships between elements, such as the neo4j database.
Preferably, the embodiment of the present invention obtains the original data set from a preset database by:
connecting the database through a built-in interface which is constructed in advance;
and inquiring in the database according to preset data screening conditions to obtain the original data set.
Further, in the embodiment of the present invention, the original data set is divided by types through the pre-constructed data processing packet, data of the same type in the original data set is aggregated to obtain a plurality of sub data sets, and the amount of data that needs to be processed by the computer system at a time is reduced.
Preferably, the data processing package is a NumPy-based tool that incorporates a large number of libraries and some standard data models to efficiently manipulate large data sets.
In detail, the sequentially setting Y-axis coordinates for the elements in each sub data set according to the data distribution of the original data set in the database includes:
sequentially selecting one of the sub data sets to obtain all elements contained in the sub data set;
sorting the elements of the sub data set according to the location distribution of the elements in the database;
setting a Y-axis coordinate for each element in the sub-data set according to the sorting result, for example, the Y-axis coordinate of the element ranked at the first position may be set to 1, and the Y-axis coordinates of the following elements are sequentially added with 1;
and judging whether each sub data set is selected completely, selecting the next sub data set until each sub data set is selected completely, setting Y-axis coordinates for each element in each sub data set, and combining all sub data sets to obtain a first data set.
Wherein the sorting of the elements of the sub data set according to the location distribution of the elements in the database is performed sequentially according to the high-low condition of the locations of the elements in the database.
In the embodiment of the invention, the Y coordinate value of the element in the first data set is positively correlated according to the position distribution in the database.
The data dividing module 102 is configured to divide the first data set into a source data set and a plurality of target data sets.
In detail, the data partitioning module specifically performs the following operations:
searching a source node in the first data set to obtain a source data set;
and searching the target nodes in the first data set according to the relationship between the source node and other elements to obtain a plurality of target data sets.
The source node is an element of the first data set which does not have a parent element except the source node, and if the element is in family relation, the first person on the family tree is the source node; the target node is other elements except the source node in all elements contained in one relationship; the source data set comprises a plurality of source nodes, and each target data set comprises a plurality of target nodes which are associated with one source node. The source node set and the target data set are relatively large in data size, and the blockchain has high throughput, can process a large amount of data at a time, and can be stored in nodes of the blockchain.
Preferably, in the embodiment of the present invention, the source node and the target node in the first data set are searched through a preset data processing packet.
The X coordinate setting module 103 is configured to set an X axis coordinate for the elements in the source data set and the target data set according to a relationship between the elements in the first data set, so as to obtain a second data set.
In detail, the X coordinate setting module is specifically configured to:
dividing the source data set into a plurality of source data subsets according to types;
sequentially selecting one of the source data subsets;
setting X-axis coordinates for elements in the source data subset, and selecting a source node in the source data subset;
selecting a target node having a direct sub-relationship with the source node in a target data set corresponding to the source node to obtain a subclass element set;
sorting the elements in the subclass element set, and setting X-axis coordinates for the elements in the subclass element set according to a sorting result;
updating the subclass element set until the source data subset and the corresponding element of the target data set are set to be X-axis coordinates;
and judging whether each source data subset is selected completely, and selecting the next source data subset until a second data set is obtained and output when the X-axis coordinates of the elements in the source data set and the target data sets are set.
Further, the updating the child class element set includes: selecting a target node in the target data set, wherein the target node has a direct sub-relationship with the elements of the subclass element set, and the target node is used as an element of the subclass element set; and sequencing the elements in the subclass element set, and setting X-axis coordinate values for the elements in the subclass element set according to a sequencing result.
Preferably, the embodiment of the present invention sets the X-axis coordinate for the element in the source data subset according to the position distribution of the element in the database; the elements in the child class element set are sorted according to the priority of the association relationship between each element and the parent class element to which the element belongs.
In the embodiment of the present invention, the source data set and the elements of the plurality of target data sets are merged to obtain a second data set, and both the X-axis coordinate and the Y-axis coordinate of the elements in the second data set are generated.
The graph relationship output module 104 is configured to output a graph visualization relationship of the original data set according to the X-axis coordinate and the Y-axis coordinate of each element in the second data set.
In detail, according to the X-axis coordinate and the Y-axis coordinate of each element in the second data set, each element is displayed in a preset coordinate system as a graphic mark of a dot, and the association relationship between each element is connected with each element as a graphic mark of a solid line, so as to form a graphic visualization relationship of the original data set, and output the graphic visualization relationship.
Fig. 6 is a schematic structural diagram of an electronic device implementing a method for representing data in a graphical visualization relationship according to the present invention.
The electronic device 1 may comprise a processor 10, a memory 11 and a bus, and may further comprise a computer program, such as a graphical visualization relational representation program 12 of data, stored in the memory 11 and executable on the processor 10.
The memory 11 includes at least one type of readable storage medium, which includes flash memory, removable hard disk, multimedia card, card-type memory (e.g., SD or DX memory, etc.), magnetic memory, magnetic disk, optical disk, etc. The memory 11 may in some embodiments be an internal storage unit of the electronic device 1, such as a removable hard disk of the electronic device 1. The memory 11 may also be an external storage device of the electronic device 1 in other embodiments, such as a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the electronic device 1. Further, the memory 11 may also include both an internal storage unit and an external storage device of the electronic device 1. The memory 11 may be used not only to store application software installed in the electronic device 1 and various types of data, such as codes of the graphic visualization relation representation program 12 of the data, but also to temporarily store data that has been output or is to be output.
The processor 10 may be composed of an integrated circuit in some embodiments, for example, a single packaged integrated circuit, or may be composed of a plurality of integrated circuits packaged with the same or different functions, including one or more Central Processing Units (CPUs), microprocessors, digital Processing chips, graphics processors, and combinations of various control chips. The processor 10 is a Control Unit (Control Unit) of the electronic device, connects various components of the electronic device by using various interfaces and lines, and executes various functions and processes data of the electronic device 1 by running or executing programs or modules (for example, a program for performing graphic visualization of data, etc.) stored in the memory 11 and calling data stored in the memory 11.
The bus may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. The bus is arranged to enable connection communication between the memory 11 and at least one processor 10 or the like.
Fig. 6 only shows an electronic device with components, and it will be understood by a person skilled in the art that the structure shown in fig. 6 does not constitute a limitation of the electronic device 1, and may comprise fewer or more components than shown, or a combination of certain components, or a different arrangement of components.
For example, although not shown, the electronic device 1 may further include a power supply (such as a battery) for supplying power to each component, and preferably, the power supply may be logically connected to the at least one processor 10 through a power management device, so as to implement functions of charge management, discharge management, power consumption management, and the like through the power management device. The power supply may also include any component of one or more dc or ac power sources, recharging devices, power failure detection circuitry, power converters or inverters, power status indicators, and the like. The electronic device 1 may further include various sensors, a bluetooth module, a Wi-Fi module, and the like, which are not described herein again.
Further, the electronic device 1 may further include a network interface, and optionally, the network interface may include a wired interface and/or a wireless interface (such as a WI-FI interface, a bluetooth interface, etc.), which are generally used for establishing a communication connection between the electronic device 1 and other electronic devices.
Optionally, the electronic device 1 may further comprise a user interface, which may be a Display (Display), an input unit (such as a Keyboard), and optionally a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, or the like. The display, which may also be referred to as a display screen or display unit, is suitable for displaying information processed in the electronic device 1 and for displaying a visualized user interface, among other things.
It is to be understood that the described embodiments are for purposes of illustration only and that the scope of the appended claims is not limited to such structures.
The graphical visualization relationship representation program 12 of the data stored by the memory 11 in the electronic device 1 is a combination of a plurality of instructions that, when executed in the processor 10, may implement:
dividing an original data set into a plurality of sub data sets according to types, and sequentially setting Y-axis coordinates for elements in each sub data set according to data distribution of the original data set in a database to obtain a first data set;
dividing the first data set into a source data set and a plurality of target data sets;
setting X-axis coordinates for elements in the source data set and the target data set according to the relationship between the elements in the first data set to obtain a second data set;
and outputting the graphic visualization relation of the original data set according to the X-axis coordinate and the Y-axis coordinate of each element in the second data set.
Further, the integrated modules/units of the electronic device 1, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. The computer-readable medium may include: any entity or device capable of carrying said computer program code, recording medium, U-disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM).
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus, device and method can be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is only one logical functional division, and other divisions may be realized in practice.
The modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
In addition, functional modules in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional module.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof.
The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any accompanying claims should not be construed as limiting the claim concerned.
Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or means recited in the system claims may also be implemented by one unit or means in software or hardware. The terms second, etc. are used to denote names, but not any particular order.
Finally, it should be noted that the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims (10)
1. A method for graphical visualization of relational representation of data, the method comprising:
dividing an original data set into a plurality of sub data sets according to types, and sequentially setting Y-axis coordinates for elements in each sub data set according to data distribution of the original data set in a database to obtain a first data set;
dividing the first data set into a source data set and a plurality of target data sets;
setting X-axis coordinates for elements in the source data set and the target data set according to the relationship between the elements in the first data set to obtain a second data set;
and outputting the graphic visualization relation of the original data set according to the X-axis coordinate and the Y-axis coordinate of each element in the second data set.
2. The method for graphical visualization of relational representation of data according to claim 1, wherein the sequentially setting Y-axis coordinates for the elements in each of the sub-datasets based on the data distribution of the original dataset in the database comprises:
selecting one subdata set of the subdata sets to obtain all elements contained in the subdata set;
sorting the elements of the sub data set according to the location distribution of the elements in the database;
setting Y-axis coordinates for each element in the subdata set according to the sorting result;
and selecting a next subdata set, sequencing elements in the subdata set, and setting a Y-axis coordinate according to a sequencing result.
3. The method for graphical visualization relational representation of data according to claim 1, wherein the dividing the first data set into a source data set and a plurality of target data sets comprises:
and searching a source node in the first data set to obtain a source data set.
And searching the target nodes in the first data set according to the relationship between the source node and other elements to obtain a plurality of target data sets.
4. The method for graphical visualization of relational representation of data according to claim 1, wherein the setting of X-axis coordinates for elements in the source and target data sets based on relationships between elements in the first data set comprises:
dividing the source data set into a plurality of source data subsets according to types;
sequentially selecting one of the source data subsets;
setting X-axis coordinates for elements in the source data subset, and selecting a source node in the source data subset;
selecting a target node having a direct sub-relationship with the source node in a target data set corresponding to the source node to obtain a subclass element set;
sorting the elements in the subclass element set, and setting X-axis coordinates for the elements in the subclass element set according to a sorting result;
updating the subclass element set until the source data subset and the corresponding element of the target data set are set to be X-axis coordinates;
and judging whether each source data subset is selected completely or not until the X-axis coordinates of elements in the source data set and the target data sets are set.
5. The method for graphical visual relational representation of data according to claim 4 wherein said updating of said set of child class elements comprises:
selecting a target node in the target data set, wherein the target node has a direct sub-relationship with the elements of the subclass element set, and the target node is used as an element of the subclass element set;
and sequencing the elements in the subclass element set, and setting X-axis coordinate values for the elements in the subclass element set according to a sequencing result.
6. An apparatus for graphical visual relational representation of data, the apparatus comprising:
the Y coordinate setting module is used for dividing the original data set into a plurality of sub data sets according to types, and sequentially setting Y-axis coordinates for elements in each sub data set according to the data distribution of the original data set in the database to obtain a first data set;
a data partitioning module for partitioning the first data set into a source data set and a plurality of target data sets;
an X coordinate setting module, configured to set X-axis coordinates for elements in the source data set and the target data set according to a relationship between the elements in the first data set, so as to obtain a second data set;
and the graph relation output module is used for outputting the graph visualization relation of the original data set according to the X-axis coordinate and the Y-axis coordinate of each element in the second data set.
7. The apparatus for graphical visual relational representation of data according to claim 6, wherein the Y-coordinate setting module, when sequentially setting Y-axis coordinates for elements in each of the sub-datasets based on the data distribution of the original dataset in the database, performs the following operations:
selecting one subdata set of the subdata sets to obtain all elements contained in the subdata set;
sorting the elements of the sub data set according to the location distribution of the elements in the database;
setting Y-axis coordinates for each element in the subdata set according to the sorting result;
and selecting a next subdata set, sequencing elements in the subdata set, and setting a Y-axis coordinate according to a sequencing result.
8. The apparatus for graphical visualization of relational representation of data of claim 6, wherein the data partitioning module is specifically configured to:
and searching a source node in the first data set to obtain a source data set.
And searching the target nodes in the first data set according to the relationship between the source node and other elements to obtain a plurality of target data sets.
9. An electronic device, characterized in that the electronic device comprises:
a memory storing at least one instruction; and
a processor executing instructions stored in the memory to perform a method of graphical visual relational representation of data according to any of claims 1 to 5.
10. A computer-readable storage medium comprising a data storage area for storing data and a program storage area for storing a computer program, wherein the computer program, when executed by a processor, implements a method for graphical visual relational representation of data according to any one of claims 1 to 5.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103049580A (en) * | 2013-01-17 | 2013-04-17 | 北京工商大学 | Method and device for visualization of layering data |
| CN105378797A (en) * | 2013-05-31 | 2016-03-02 | 惠普发展公司，有限责任合伙企业 | Three dimensional data visualization |
| CN107357846A (en) * | 2017-06-26 | 2017-11-17 | 北京金堤科技有限公司 | The methods of exhibiting and device of relation map |
| US10656779B1 (en) * | 2018-09-10 | 2020-05-19 | Tableau Software, Inc. | Filtering popup secondary data visualizations according to selected data from primary data visualizations |
| CN111932147A (en) * | 2020-09-02 | 2020-11-13 | 平安国际智慧城市科技股份有限公司 | Visualization method and device for overall index, electronic equipment and storage medium |
| CN112148932A (en) * | 2020-10-12 | 2020-12-29 | 平安科技（深圳）有限公司 | Visualization method, system, computer device and storage medium |
-
2020
- 2020-12-30 CN CN202011625423.4A patent/CN112632194B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103049580A (en) * | 2013-01-17 | 2013-04-17 | 北京工商大学 | Method and device for visualization of layering data |
| CN105378797A (en) * | 2013-05-31 | 2016-03-02 | 惠普发展公司，有限责任合伙企业 | Three dimensional data visualization |
| CN107357846A (en) * | 2017-06-26 | 2017-11-17 | 北京金堤科技有限公司 | The methods of exhibiting and device of relation map |
| US10656779B1 (en) * | 2018-09-10 | 2020-05-19 | Tableau Software, Inc. | Filtering popup secondary data visualizations according to selected data from primary data visualizations |
| CN111932147A (en) * | 2020-09-02 | 2020-11-13 | 平安国际智慧城市科技股份有限公司 | Visualization method and device for overall index, electronic equipment and storage medium |
| CN112148932A (en) * | 2020-10-12 | 2020-12-29 | 平安科技（深圳）有限公司 | Visualization method, system, computer device and storage medium |
Non-Patent Citations (1)
| Title |
|---|
| 王利鹏等: ""基于本体可视化的关联数据集表达"", 《科研信息化技术与应用》 * |
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