A bottom-up cluster map layered drilling method, device and medium

Abstract

The embodiment of the present invention discloses a bottom-up cluster map hierarchical drill-down method, device and medium. The method includes: obtaining data node information to be displayed as a cluster map; generating a single-layer visual base map according to the data node information; parsing the single class layer of each class, the single group layer of each group, and all group layers layer by layer according to the visual base map; displaying all group layers as the top layer of the cluster map; in response to a local information acquisition operation of a certain group, drilling down to display the single group layer of the certain group; in response to a local information display operation of a certain class in the certain group, drilling down to display the single class layer of the certain class. This embodiment can realize hierarchical drill-down of cluster maps, allowing users to explore the local and data distribution details of cluster maps.

Description

Technical Field

[0001] The embodiments of the present invention relate to the technical field of data visualization, and in particular to a bottom-up cluster map layered drill-down method, device and medium. Background Art

[0002] The application of geographic maps in the fields of geographic information systems (GIS), urban planning, environmental protection, etc. often requires drilling down into geographic spatial data and conducting multi-level and multi-angle analysis of geographic data.

[0003] With the rapid development of WebGIS, big data and other technologies, data visualization has become an important means of data analysis, and data clustering visualization has become an important analysis method. However, there is currently no layering function for cluster maps. Summary of the invention

[0004] The embodiments of the present invention provide a bottom-up cluster map hierarchical drill-down method, device and medium to solve the above technical problems.

[0005] In a first aspect, an embodiment of the present invention provides a bottom-up cluster map hierarchical drill-down method, comprising:

[0006] Obtaining data node information to be displayed as a cluster map, wherein the information of each node includes the node name, and the class and group to which the node belongs;

[0007] Generate a single-layer visualization base map according to the data node information, in which nodes of the same class are displayed in the same block, and blocks corresponding to the same group of classes together constitute a continuous area;

[0008] According to the visualization base map, a single class layer of each class, a single group layer of each group, and all group layers are parsed layer by layer;

[0009] Display all the group layers as the top layer of the cluster map; in response to a local information acquisition operation of a certain group, drill down to display a single group layer of the certain group; in response to a local information display operation of a certain class in the certain group, drill down to display a single class layer of the certain class.

[0010] In a second aspect, an embodiment of the present invention provides an electronic device, the electronic device comprising:

[0011] one or more processors;

[0012] a memory for storing one or more programs,

[0013] When the one or more programs are executed by the one or more processors, the one or more processors implement the bottom-up cluster map hierarchical drill-down method described in any one of the embodiments.

[0014] In a third aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the bottom-up cluster map hierarchical drill-down method described in any one of the embodiments.

[0015] The embodiment of the present invention provides a bottom-up cluster map hierarchical drill-down method, which first adds a multi-level structure and the corresponding relationship between different levels to the input data, then generates a cluster base map based on the hierarchical data, and finally performs hierarchical analysis and hierarchical mapping on the generated base map to realize the hierarchical and drill-down functions of the cluster map, which enhances the data analysis ability from the global to the local, and can explore the details of the data; multi-level analysis can help users understand the data distribution and characteristics of different levels, and can also improve the user experience. This hierarchical drill-down method is applicable to cluster map display of all data, and can perform multi-level and multi-angle analysis on the results of data cluster visualization. Users can also freely switch the display level of the map according to their needs, so as to better understand the distribution law and internal connection of the data. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 It is a flow chart of a bottom-up cluster map hierarchical drill-down method provided by an embodiment of the present invention;

[0018] Figure 2 It is a fully quantitative visualization base map provided by an embodiment of the present invention;

[0019] Figure 3 is a coloring schematic diagram before a coloring function is modified provided by an embodiment of the present invention;

[0020] Figure 4 is a schematic diagram of a top-level layer provided by an embodiment of the present invention;

[0021] Figure 5 It is a schematic diagram of an intermediate layer provided by an embodiment of the present invention;

[0022] Figure 6It is a schematic diagram of a bottom layer provided by an embodiment of the present invention;

[0023] Figure 7 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0024] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work belong to the scope of protection of the present invention.

[0025] In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", and "third" are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance.

[0026] In the description of the present invention, it is also necessary to explain that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0027] As described in the background technology, although the GIS system integrates the hierarchical drill-down display function of the geographic map, the specific implementation method of this function is undisclosed and cannot be applied to the display of cluster maps. In addition, the GIS system can only display geographic information data, and the spatial position of each point in the geographic map is also fixed; while the cluster map can display the logical relationship of any data, and the position coordinates of the data points in each cluster have no fixed rules. Therefore, the hierarchical drill-down display of the cluster map is very different from the hierarchical drill-down display of the geographic map. It is urgent to propose a hierarchical drill-down method for cluster maps so that cluster maps have more powerful analysis capabilities and user experience.

[0028] Figure 11 is a flowchart of a bottom-up cluster map layered drill-down method provided by an embodiment of the present invention. The method is applicable to the case where the input data includes multi-level data relationships and is executed by an electronic device. Figure 1 As shown, the method specifically includes:

[0029] S110 , obtaining data node information to be displayed as a cluster map, wherein the information of each node includes the node name, and the class and group to which the node belongs.

[0030] There is no hierarchical relationship in general cluster maps, which only include relevant information of classes and nodes. Each node corresponds to one data, and data belonging to the same class will be displayed in the same block of the cluster map to ensure the clustering relationship between the data.

[0031] The input data of this embodiment has a hierarchical relationship, so in addition to the traditional class and node information, this embodiment also introduces group information. A group includes one or more classes, each class includes one or more nodes, and the group, class, and node can be recorded as group, cluster, and point respectively. Optionally, a node in the input data is a piece of information, and each piece of information includes the node name, the class id to which the node belongs, the group id to which the node belongs, the font style, font size and other attributes, as shown below:

[0032] node1[cluster=1,label=asn1,group=1,fontsize=8]

[0033] node2[cluster=1,label=asn2,group=1,fontsize=8] ....

[0034] node1324[cluster=6,label=asn1324 group=6,fontsize=8]

[0035] node1325[cluster=6,label=asn1325,group=6,fontsize=8] ....

[0036] node1428[cluster=7,label=asn1428,group=6,fontsize=8]

[0037] node1429[cluster=7,label=asn1429,group=6,fontsize=8]

[0038] The cluster and group in the node information are globally incremented. Each node can be an ASN number, each category can be an ASN number of a region, and each group can be an ASN number of a country.

[0039] S120. Generate a single-layer visualization base map based on the data node information. In the visualization base map, nodes of the same class are displayed in the same block, and blocks corresponding to the same group of classes together constitute a continuous area.

[0040] This step uses visualization software to generate a fully quantified visualization base map based on the input data information as the basis for parsing multi-level drill-down layers. Full quantification means that the visualization map includes all class and group information at the same time.

[0041] Optionally, the corresponding relationship between each group and each category can be parsed according to the data node information. As described above, the cluster and group ids in the node information are all globally unique, so the corresponding relationship between group and cluster can be parsed from the data node information, including the corresponding relationship between group and cluster (i.e. the class included in each group), and the corresponding relationship between cluster and group (i.e. the group included in each category). Then, the input data is clustered and displayed using visualization software, and the nodes of the same category are generated in the same block. Taking into account the multi-level relationship in the input data, the corresponding relationship between group and cluster can be used to generate the information of a group in a region during the visualization base map generation process, and finally the classes of the same group are colored with the same color using the corresponding relationship between cluster and group, and a visualization base map of a single layer is finally generated. Figure 2 An example of a fully quantitative visualization base map is shown, in which the red continuous area is grouped as 6, including 2 classes; the yellow continuous area is grouped as 7, including 3 classes; and group 1 and group 4 are also different colors.

[0042] In a specific implementation, during the visualization base map generation process, the correspondence between group and cluster can be used to create a multi-layer subgraph structure for the input data, and the visualization software automatically parses the multi-layer subgraph structure, so that the classes of the same group are generated in a continuous area. Specifically, the subgraph structure is a data structure that can be recognized and parsed by the visualization software. In the general visualization generation process, each class is defined as a single-layer subgraph structure. The visualization software parses the information in the subgraph and generates the data points of the same subgraph in the same block. This embodiment uses the subgraph structure to define multi-layer data, and the visualization software nests and parses the data structures of each layer to modify the generation effect of the visualization base map.

[0043] Optionally, first create a subgraph structure for each data class, and define each data node of the same class into the corresponding subgraph structure. Then, create a subgraph structure for each group, and define the subgraph structures of each class in the same group into the corresponding subgraph structure according to the classes included in each group in the corresponding relationship. For the convenience of distinction and description, the subgraph structure corresponding to each class is referred to as a secondary subgraph structure in this embodiment, and the subgraph structure corresponding to each group is referred to as a primary subgraph structure, and the two-level subgraph structures are identified by different IDs. Specifically, after creating a primary subgraph structure for each group, each primary subgraph structure is globally numbered according to the group ID; then, according to the classes included in each group in the corresponding relationship, the secondary subgraph structures of each class in the same group are locally numbered within the group, and the global number of the same group and the local number of each class together constitute the complete number of each secondary subgraph structure, and each secondary subgraph structure is defined into the primary subgraph structure of the same group. Exemplarily, the final data structure is as follows:

[0044] When the group number is 1, the data structure is:

[0045]

[0046]

[0047] The first digit of the subgraph number is the group id, which is the global number. The second digit is the local number of each type in the group. In a group, the local number starts from 1 and increases. The cluster and group ids in the node information are all globally increasing. For example, when the group number is 7, the outermost first-level subgraph will be subgraph 7, the second-level subgraphs are subgraph 7_1, 7_2 and 7_3, the cluster ids are 8, 9, 10, and the group id = 7.

[0048] Based on the above data structure, when parsing each first-level subgraph structure, the visualization software will perform intra-layer nested analysis on the second-level subgraph structure, thereby generating the classes of the same group in a continuous area.

[0049] After the continuous area is generated, the coloring stage of the visualization base map is entered. According to the display requirements of hierarchical drill-down, this embodiment makes the following modifications to the open source visualization software: In the color calculation of the visualization coloring function, the class id is mapped to the group id according to the group to which each class in the corresponding relationship belongs, thereby changing the color calculation method of the coloring function using the continuously increasing id of the class to the method of using the continuously increasing id of the group. When the visualization software runs the modified coloring function, it will perform color calculations based on the group id, thereby coloring the classes in the same group with the same color. Specifically, when the visualization software performs color calculations based on the continuously increasing id of the group, the group id value is assigned to the three channels of R\G\B of the three primary colors of RGB, and converted into a hexadecimal color code for coloring configuration. In order to more intuitively reflect the significance of modifying the coloring function, Figure 3 The cluster map before the coloring function is modified is shown. It can be seen that before the coloring function is modified, the blocks of each type belonging to the same group have different colors and cannot reflect the group information. After the modification, Figure 2 In the figure, each block in the same group (such as group 7) is displayed in the same color, and different classes are distinguished by boundary lines within the group, which better shows the multi-layer characteristics of clustering data.

[0050] S130. According to the visualization base map, analyze the single class layer of each class, the single group layer of each group, and all the group layers layer by layer.

[0051] As mentioned above, the visualization base map includes fully quantified class information and group information. However, in the field of visualization technology, a layer usually only displays data with the same meaning (i.e., the same level), and does not display all data with different meanings. Therefore, this step performs layered analysis on the visualization base map, so that the data of different layers are in corresponding dimensions, which is convenient for users to explore the details of the data.

[0052] Optionally, the cluster map can be divided into three layers according to the relationship in the data: the bottom layer is a single cluster information layer, referred to as a single class layer; the middle layer is a single group information layer, referred to as a single group layer, and a single group information is the aggregation of multiple cluster information; the top layer is a layer where all group information is aggregated, called all group layers. In a specific implementation, the process of parsing the single class layers of each category, the single group layers of each group, and all group layers layer by layer according to the visualization base map may include the following steps:

[0053] Step 1: Display each class of blocks in the visualization base map separately to obtain a single class layer for each class. Specifically, first parse all cluster information to parse the underlying single cluster information layer, including all nodes and node coordinates of a single class, as well as the boundary coordinates of a single class, and store the cluster and cluster block boundaries in the form of a dictionary, recorded as cluster_boundary.

[0054] Step 2: According to the classes included in each group, the class blocks belonging to the same group are displayed simultaneously, and the boundaries of each block are retained to form a single group layer; at the same time, the boundaries of each block are removed, and only the outermost boundaries of the continuous area formed by each block are retained to obtain the merged area of ​​the same group. The single group layer and the merged area of ​​each group are saved separately. Specifically, through the correspondence between group and cluster, the information of multiple clusters corresponding to a group is aggregated to form a single group information layer in the middle layer, recorded as group_cluster; then the aggregated information of a group is merged to generate an overall group information. Among them, aggregation refers to displaying multiple areas (or blocks) at the same time, retaining the boundaries of each area (or block); and merging is to integrate multiple areas (or blocks), and finally only retain the outermost boundaries of multiple areas (or blocks). Optionally, the union function in polygons can be used for merging.

[0055] Step 3: Display the merged areas of each group at the same time to obtain all group layers. That is, aggregate all the merged group information to form the top-level all group information layer, and the layer boundary is recorded as group_boundary.

[0056] S140, displaying all the group layers as the top layer of the cluster map; in response to a local information acquisition operation of a certain group, drilling down to display a single group layer of the certain group; in response to a local information display operation of a certain class in the certain group, drilling down to display a single class layer of the certain class.

[0057] The above three layers are analyzed from bottom to top, but for users, what they care about is the operation. After the hierarchical analysis, the data needs to be hierarchically mapped in a top-down order. Specifically, the top layer, that is, the information layer of all groups, is directly displayed to the user. Specifically, group_boundary = {groupid1:union_boundary1, groupid2:union_boundary2, ....}. When it is necessary to obtain local information of a certain group, it will drill down to the middle layer. The middle layer is the information of a single group. Because it is an aggregated method, group_cluster = {groupid1:{clusterid1:boundary1, clusterid2:boundary2, clusterid3:boundary3, ....}}. If you need to continue to obtain a certain cluster information, drill down to the bottom layer of the graph. The bottom layer is a single cluster information, cluster_boundary = {clusterid3:boundary3}. Through the above top-down hierarchical mapping, the map drill-down function can be realized, which is convenient for users to obtain detailed information of the data.

[0058] For example, after the hierarchical analysis and hierarchical mapping of the full base map, the same dimension information will be displayed on the same layer. Figure 4 When the user selects area 7, the middle layer can be seen, as shown in Figure 5 When the user selects the area 7-1 in the middle layer, the user enters the bottom layer, as shown in Figure 6 shown.

[0059] In summary, this embodiment provides a bottom-up cluster map hierarchical drill-down method, which first adds a multi-level structure and the corresponding relationship between different levels to the input data, then generates a cluster base map based on the layered data, and finally performs layered analysis and layered mapping on the generated base map to achieve the layering and drill-down functions of the cluster map, from the global to the local, enhancing the data analysis capabilities and being able to explore the details of the data; performing multi-level analysis can help users understand the data distribution and characteristics of different levels, and can also improve the user experience. This layered drill-down method is applicable to cluster map display of all data, and can perform multi-level and multi-angle analysis on the results of data cluster visualization. Users can also freely switch the display level of the map according to their needs, so as to better understand the distribution patterns and internal connections of the data.

[0060] Figure 7 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention is shown in FIG. Figure 7As shown, the device includes a processor 60, a memory 61, an input device 62 and an output device 63; the number of processors 60 in the device can be one or more. Figure 7 A processor 60 is taken as an example; the processor 60, the memory 61, the input device 62 and the output device 63 in the device can be connected by a bus or other means. Figure 7 The example of connecting through bus is taken in the following.

[0061] The memory 61, as a computer-readable storage medium, can be used to store software programs, computer executable programs and modules, such as program instructions / modules corresponding to the bottom-up cluster map hierarchical drill-down method in the embodiment of the present invention. The processor 60 executes various functional applications and data processing of the device by running the software programs, instructions and modules stored in the memory 61, that is, realizing the above-mentioned bottom-up cluster map hierarchical drill-down method.

[0062] The memory 61 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system and at least one application required for a function; the data storage area may store data created according to the use of the terminal, etc. In addition, the memory 61 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some instances, the memory 61 may further include a memory remotely arranged relative to the processor 60, and these remote memories may be connected to the device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0063] The input device 62 may be used to receive input digital or character information and generate key signal input related to user settings and function control of the device. The output device 63 may include a display device such as a display screen.

[0064] An embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the bottom-up cluster map hierarchical drill-down method of any embodiment is implemented.

[0065] The computer storage medium of the embodiment of the present invention can adopt any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to, a system, device or device of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, a device or a device or used in combination with it.

[0066] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0067] The program code embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0068] Computer program code for performing the operations of the present invention may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as C or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0069] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the technical solutions of the embodiments of the present invention.

Claims

1. A bottom-up cluster map layered drill-down method, characterized in that: include: Obtaining data node information to be displayed as a cluster map, wherein the information of each node includes the node name, and the class and group to which the node belongs; According to the data node information, the corresponding relationship between each group and each class is parsed; through cluster visualization, the nodes of the same class are generated in the same block of the visualization map; using the subgraph data structure in the visualization software, a second-level subgraph structure is created for each data class, and each data node of the same class is defined in the corresponding second-level subgraph structure; a first-level subgraph structure is created for each group, and according to the classes included in each group in the corresponding relationship, the second-level subgraph structure of each class in the same group is defined in the corresponding first-level subgraph structure; the visualization software automatically parses each first-level subgraph structure and the second-level subgraph structure, and generates the classes of the same group in a continuous area; according to the groups to which each class belongs in the corresponding relationship, the classes of the same group are colored with the same color to obtain a single-layer visualization base map; according to the visualization base map, the single class layer of each class, the single group layer of each group, and all group layers are parsed layer by layer; Display all the group layers as the top layer of the cluster map; in response to a local information acquisition operation of a certain group, drill down to display a single group layer of the certain group; in response to a local information display operation of a certain class in the certain group, drill down to display a single class layer of the certain class.

2. The method according to claim 1, characterized in that The first-level subgraph structure is created for each group, and according to the classes included in each group in the corresponding relationship, the second-level subgraph structures of each class in the same group are defined in the corresponding first-level subgraph structure, including: Create a first-level subgraph structure for each group, and globally number each first-level subgraph structure according to the group id; According to the classes included in each group in the corresponding relationship, the second-level subgraph structures of each class in the same group are locally numbered within the group, and the global number of the same group and the local number of each class together constitute the complete number of each second-level subgraph structure, and each second-level subgraph structure is defined within the first-level subgraph structure of the same group.

3. The method according to claim 1, characterized in that The coloring of classes in the same group with the same color according to the groups to which the classes in the corresponding relationship belong includes: In the color calculation of the visualization coloring function, the class id is mapped to the group id to which it belongs according to the group to which each class belongs in the corresponding relationship; Change the color calculation method from using the class ID to using the group ID; The modified coloring function is run by the visualization software to color the classes in the same group with the same color.

4. The method according to claim 1, characterized in that: According to the visualization base map, the single class layer of each class, the single group layer of each group, and all the group layers are parsed layer by layer, including: The blocks of each category in the visualization base map are displayed separately to obtain a single class layer of each category; According to the classes included in each group, the class blocks belonging to the same group are displayed simultaneously, and the boundaries of each block are retained to form a single group layer; the boundaries of each block are removed, and only the outermost boundaries of the continuous area formed by each block are retained to obtain the merged area of ​​the same group; Display the merged areas of each group at the same time to obtain all group layers.

5. The method according to claim 4, characterized in that The process of removing the boundaries of each block and retaining only the outermost boundaries of the continuous area formed by each block includes: The union function in polygon is used to operate the polygon boundaries of each block to obtain the outermost boundary of the continuous area formed by each block.

6. The method according to claim 1, characterized in that In response to the local information acquisition operation of a certain group, drilling down to display a single group layer of the certain group includes: in response to a click operation on a local area of ​​a certain group in the top layer, drilling down to display a single group layer of the certain group; Correspondingly, in response to the local information display operation of a certain class in the certain group, drilling down to display the single class layer of the certain class includes: in response to a click operation on the local area of ​​a certain class in the single group layer, drilling down to display the single class layer of the certain class.

7. An electronic device, characterized in that: include: one or more processors; a memory for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the bottom-up cluster map hierarchical drill-down method described in any one of claims 1-6.

8. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the program is executed by a processor, the bottom-up cluster map hierarchical drill-down method described in any one of claims 1-6 is implemented.

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