Target item display method and device, computer equipment, readable storage medium and program product

Abstract

The invention relates to the technical field of data visualization, and provides a target item display method and device, computer equipment, a readable storage medium and a program product. The method comprises the following steps: in response to a click operation for one item icon of a target item map, popping up a window, and displaying a key information page of a target item corresponding to the item icon in the window; in response to a click operation for viewing a detail tag of the key information page, displaying various indexes of a target item corresponding to the item icon on the item detail page; when the numerical value of the target index in each type of indexes is abnormal, displaying an abnormal label; in response to a click operation for the abnormal tag, generating an association analysis result of an abnormal reason of the target index on the association analysis page, and displaying an optimization suggestion tag; and in response to a click operation for the optimization suggestion label, generating an optimization suggestion proposed for the abnormal reason of the target index on the optimization suggestion page. By adopting the method, the index exception handling capability can be improved.

Description

Technical Field

[0001] This application relates to the field of data visualization technology, and in particular to a method, apparatus, computer device, computer-readable storage medium, and computer program product for displaying a target project. Background Technology

[0002] To ensure the safe and stable operation of the power system, controllable costs, compliance with business regulations, and the implementation of innovations, it is necessary to conduct routine management of key power projects of power companies.

[0003] Currently, the daily management of key power projects in power companies is based on offline manual processing. It is difficult for staff at all levels to keep abreast of the operation and management of key power projects. Furthermore, the diagnosis of abnormal indicators of key power projects requires relevant staff to manually extract data and judge the cause of the abnormality, resulting in poor ability to handle abnormal indicators. Summary of the Invention

[0004] Therefore, it is necessary to provide a method, apparatus, computer device, computer-readable storage medium, and computer program product for displaying the target project, in response to the above-mentioned technical problems.

[0005] Firstly, this application provides a method for displaying a target project, including:

[0006] In response to a click on one of the project icons on the target project map, a pop-up window is displayed, showing a page of key information about the target project corresponding to the project icon.

[0007] In response to a click on the "View Details" tab of the key information page, the user is redirected to the project details page, where various metrics of the target project corresponding to the project icon are displayed.

[0008] When the value of the target indicator among the various indicators is abnormal, an abnormal label will be displayed;

[0009] In response to a click on the abnormal label, the user is redirected to the correlation analysis page, where correlation analysis results of the abnormal causes of the target indicator are generated and optimization suggestion labels are displayed.

[0010] In response to a click on the optimization suggestion label, the user is redirected to the optimization suggestion page, where optimization suggestions are generated to address the causes of the anomalies in the target metric.

[0011] In one embodiment, the correlation analysis results for generating the anomalies of the target indicator include:

[0012] If the abnormal label of the target indicator is a frequently clicked label, retrieve the associated data of the target indicator from the local cache database;

[0013] If the abnormal label of the target indicator is a non-frequent click label, obtain the associated data of the target indicator from an external system;

[0014] Based on the associated data of the target indicator, generate the association analysis results of the abnormal causes of the target indicator.

[0015] In one embodiment, obtaining the local cache database includes:

[0016] Get the number of times abnormal tags were clicked within a set historical period to identify frequently clicked tags;

[0017] Obtain relevant data on target metrics corresponding to frequently clicked tags from external systems;

[0018] The associated data is stored in a local cache database.

[0019] In one embodiment, the method further includes:

[0020] If the time to generate the correlation analysis results exceeds a preset generation time threshold, the analysis progress is calculated.

[0021] Based on the analysis progress, the estimated remaining analysis time is obtained;

[0022] The correlation analysis page displays the analysis progress and the estimated remaining analysis time.

[0023] In one embodiment, generating optimization suggestions for the causes of anomalies in the target metric includes:

[0024] Determine the user role based on the account information corresponding to the user account that performs the click operation;

[0025] Based on the relationship between user roles and suggestion requirement dimensions, determine the suggestion requirement dimensions corresponding to user roles;

[0026] Based on the suggested needs dimension corresponding to the user role, optimization suggestions are generated to address the causes of anomalies in the target metric.

[0027] In one embodiment, generating optimization suggestions for the causes of anomalies in the target metric includes:

[0028] Based on the cause of the anomaly in the target indicator, a matching historical optimization suggestion is searched in the historical optimization suggestion library; the historical optimization suggestions in the historical optimization suggestion library are those that have been verified to be effective in practice.

[0029] If a matching historical optimization suggestion exists in the historical optimization suggestion library, optimization suggestions are generated based on the matching historical optimization suggestion to address the cause of the anomaly in the target indicator.

[0030] Secondly, this application also provides a display device for the target project, comprising:

[0031] The key information display module is used to respond to a click operation on one of the project icons on the target project map, pop up a window, and display the key information page of the target project corresponding to the project icon in the window;

[0032] The various indicator display module is used to respond to the click operation of the view details tab on the key information page, jump to the project details page, and display various indicators of the target project corresponding to the project icon on the project details page;

[0033] The anomaly label display module is used to display an anomaly label when the value of the target indicator among the various indicators is abnormal;

[0034] The correlation analysis result generation module is used to respond to the click operation of the abnormal label, jump to the correlation analysis page, generate the correlation analysis result of the abnormal cause of the target indicator on the correlation analysis page, and display the optimization suggestion label.

[0035] The optimization suggestion generation module is used to respond to a click operation on the optimization suggestion label, jump to the optimization suggestion page, and generate optimization suggestions on the optimization suggestion page for the abnormal reasons of the target indicator.

[0036] Thirdly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the above-described method.

[0037] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, the computer program being executed by a processor using the methods described above.

[0038] Fifthly, this application also provides a computer program product. The computer program product includes a computer program that is executed by a processor using the methods described above.

[0039] The aforementioned method, apparatus, computer equipment, computer-readable storage medium, and computer program product for displaying the target project, in response to a click operation on one of the project icons on the target project map, pops up a window displaying a key information page for the target project corresponding to the project icon; in response to a click operation on the "View Details" tab of the key information page, it redirects to the project details page, displaying various indicators of the target project corresponding to the project icon; when the value of the target indicator among the various indicators is abnormal, an "Abnormal" label is displayed; in response to a click operation on the "Abnormal" label, it redirects to the "Correlation Analysis" page, generating correlation analysis results of the abnormality cause of the target indicator and displaying an "Optimization Suggestion" label; in response to a click operation on the "Optimization Suggestion" label, it redirects to the "Optimization Suggestion" page, generating optimization suggestions for the abnormality cause of the target indicator. This application displays an anomaly label when the value of a target indicator among various metrics is abnormal; in response to a click on the anomaly label, it generates a correlation analysis result of the cause of the anomaly in the correlation analysis page and displays an optimization suggestion label; in response to a click on the optimization suggestion label, it generates optimization suggestions for the cause of the anomaly in the optimization suggestion page. This enables a closed-loop, efficient flow of anomaly detection, cause analysis, and optimization suggestions, eliminating the need for manual data extraction and anomaly cause judgment. Each target indicator can obtain targeted anomaly handling support through this closed loop, thereby improving the anomaly handling capability of the indicator. Attached Figure Description

[0040] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0041] Figure 1 This is an application environment diagram of the method for displaying the target project in one embodiment;

[0042] Figure 2 This is a flowchart illustrating a method for displaying a target item in one embodiment;

[0043] Figure 3 This is a flowchart illustrating the process of generating correlation analysis results in one embodiment;

[0044] Figure 4 This is a structural block diagram of the display device for the target item in one embodiment;

[0045] Figure 5 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0046] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0047] It should be noted that the terms "comprising" and "having," and any variations thereof, as used in this application, are intended to cover non-exclusive inclusion. The term "multiple" as used in this application refers to two or more. The term "and / or" as used in this application refers to one of the solutions, or any combination of multiple solutions.

[0048] The method for displaying the target project provided in this application embodiment can be applied to, for example... Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be integrated onto server 104 or placed on the cloud or other network servers. When the value of a target indicator among various metrics is abnormal, terminal 102 displays an anomaly label; in response to a click on the anomaly label, it redirects to a correlation analysis page, where it generates correlation analysis results for the cause of the target indicator's anomaly and displays an optimization suggestion label; in response to a click on the optimization suggestion label, it redirects to an optimization suggestion page, where it generates optimization suggestions for the cause of the target indicator's anomaly. Terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, drones, low-altitude aircraft, IoT devices, and portable wearable devices. Server 104 can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.

[0049] In one exemplary embodiment, such as Figure 2 As shown, a method for displaying a target project is provided, which can be applied to... Figure 1 Taking terminal 102 as an example, the explanation includes the following steps S201 to S205. Wherein:

[0050] Step S201: In response to a click operation on one of the project icons on the target project map, a pop-up window is generated, displaying the key information page of the target project corresponding to the project icon.

[0051] Based on a high-precision electronic map of the city, a basic framework of a Geographic Information System (GIS) adapted to project monitoring is built to obtain a map of the target project. The specific steps are as follows:

[0052] Integrate spatial data such as regional division data (city-district-street / industrial park three-level boundaries), transportation network, land parcel red lines, and functional area planning to form a dual-layer foundation of vector map and image map (vector map is used for precise positioning, and image map is used for real-world reference); develop basic interactive functions such as map zooming, panning, and layer switching, and support precision switching from a city-wide macro perspective (1:50000) down to a specific project parcel (1:500), providing underlying support for project spatial positioning.

[0053] Key power projects can be referred to as target projects. For example, target projects could be demonstration projects, first-of-its-kind equipment, or innovation platforms.

[0054] For target projects such as demonstration projects, first-of-its-kind equipment, and innovation platforms, a standardized data collection and storage system is constructed, connecting with the government systems of various districts and bureaus to collect key (core) project information. A spatiotemporal database is used to store the collected key project information data, enabling the correlation and querying of spatial and attribute information. Target projects and their key information are linked to maps, including dual-layer maps, to achieve spatial display. Specifically, address resolution technology (such as calling map interfaces) can be used to convert project addresses into latitude and longitude coordinates, accurately matching them with the map's land boundary lines. For projects without explicit addresses (such as platforms within a park), manual location marking on the map is supported, and the location is linked to the park's boundary to form a target project map.

[0055] Different icons can be used to distinguish project types (e.g., building icons for demonstration projects and laboratory icons for innovation platforms); colors can be used to distinguish key planning projects (gold) from ordinary projects (blue); and dynamic icon effects can be used to display the construction status (e.g., flashing icons indicate construction in progress, gray icons indicate that construction has been suspended, and checkmark icons indicate that construction has been accepted).

[0056] When a user clicks on a project icon on the target project map, a pop-up window appears in response to the click, displaying key information about the target project. This window can be a bubble window. Key information about the target project includes: basic attributes: project name, type (distinguishing between key and ordinary projects), responsible unit, project initiation date, and planned duration; spatial information: project address, latitude and longitude coordinates, land area, and construction site boundary; dynamic information: current construction stage (initiation / construction / acceptance / operation), progress completion rate, funding, research achievements, and existing problems. Data standardization: a unified data format (e.g., date format "YYYY-MM-DD", progress unit "%)", and a unique identifier for planned projects (e.g., field "plan_type='145')" to ensure clear categorization.

[0057] In step S202, in response to the click operation of the "View Details" tab on the key information page, the user is redirected to the project details page, where various indicators of the target project corresponding to the project icon are displayed.

[0058] The key information page includes a "View Details" tab. When a user clicks the "View Details" tab on the key information page, the user is redirected to the project details page, which displays various metrics of the target project corresponding to the project icon.

[0059] Step S203: When the value of the target indicator among various indicators is abnormal, display an abnormal label.

[0060] The key indicators among various metrics can be called target indicators. These key indicators can be set by staff based on the actual situation.

[0061] When the value of a target indicator in various metrics is abnormal, an abnormal label will be displayed in the upper right corner of that target indicator.

[0062] When the values ​​of the target indicators in various metrics are normal, no abnormal labels are displayed.

[0063] In step S204, in response to the click operation on the abnormal label, the user is redirected to the correlation analysis page, where the correlation analysis results of the abnormal causes of the target indicator are generated and optimization suggestion labels are displayed.

[0064] When a user clicks the "Abnormal" label, the system redirects to the correlation analysis page in response to the click action. The correlation analysis page retrieves the correlation data for the target metric and, based on this data, generates correlation analysis results indicating the cause of the abnormality for the target metric, displaying optimization suggestion labels.

[0065] Step S205: In response to the click operation on the optimization suggestion label, the user is redirected to the optimization suggestion page, where optimization suggestions are generated to address the causes of anomalies in the target metric.

[0066] When a user clicks the "Optimization Suggestions" tab, the system redirects to the optimization suggestions page. On this page, optimization suggestions are generated based on an AI diagnostic model to pinpoint the causes of anomalies in the target metric, or based on historical optimization suggestions from a database.

[0067] In the above-mentioned method for displaying target projects, when the value of a target indicator among various metrics is abnormal, an anomaly label is displayed. In response to a click on the anomaly label, the correlation analysis results of the cause of the anomaly are generated on the correlation analysis page, and an optimization suggestion label is displayed. In response to a click on the optimization suggestion label, optimization suggestions for the cause of the anomaly are generated on the optimization suggestion page. This can achieve a closed-loop and efficient flow of anomaly perception, cause analysis, and optimization suggestions, without the need for manual data extraction and anomaly cause judgment. Each target indicator can obtain targeted anomaly handling support through this closed loop, which can improve the indicator anomaly handling capability.

[0068] In one embodiment, the correlation analysis results of the abnormal causes of the target indicator are generated, and the specific steps are as follows: Figure 3 As shown: Step S301, when the abnormal label of the target indicator is the frequently clicked label, retrieve the associated data of the target indicator from the local cache database; Step S302, when the abnormal label of the target indicator is the infrequently clicked label, retrieve the associated data of the target indicator from the external system; Step S303, based on the associated data of the target indicator, generate the association analysis results of the abnormal cause of the target indicator.

[0069] The associated data for target metrics typically needs to be obtained from external systems, a process that is time-consuming, resulting in a long time to generate association analysis results. To shorten the time to generate association analysis results, this embodiment stores the associated data of target metrics corresponding to frequently clicked tags in a local cache database.

[0070] When the abnormal label of the target indicator is the frequently clicked label, it indicates that the local cache database stores the associated data of the target indicator. At this time, the associated data of the target indicator can be obtained from the local cache database. Based on the associated data of the target indicator, the association analysis results of the abnormal cause of the target indicator can be generated. There is no need to obtain the associated data from the external system, which can shorten the time for obtaining the associated data and thus shorten the time for generating the association analysis results.

[0071] If the abnormal label of the target indicator is the infrequent click label, it indicates that the local cache database does not store the associated data of the target indicator. In this case, it is necessary to obtain the associated data of the target indicator from an external system; based on the associated data of the target indicator, the association analysis results of the abnormal cause of the target indicator are generated.

[0072] In this embodiment, when the abnormal label of the target indicator is the frequently clicked label, the associated data of the target indicator is obtained from the local cache database to generate the association analysis results of the abnormal cause of the target indicator. There is no need to obtain the associated data from the external system, which can shorten the time for obtaining the associated data and thus shorten the time for generating the association analysis results.

[0073] In one embodiment, the local cache database is obtained through the following steps: obtaining the number of times abnormal tags were clicked in the past within a set historical period, and identifying frequently clicked tags; obtaining the associated data of the target indicators corresponding to the frequently clicked tags from an external system; and storing the associated data in the local cache database.

[0074] You can set the historical period and the number of clicks according to the actual situation.

[0075] It can retrieve the number of times an abnormal tag has been clicked within a set historical period. When the number of clicks on an abnormal tag within the set historical period exceeds the set number of clicks, the abnormal tag is identified as a frequently clicked tag. It can also retrieve the associated data of the target metrics corresponding to the frequently clicked tags from external systems and store it in a local cache database.

[0076] In this embodiment, the associated data of the target indicators corresponding to the frequently clicked tags are obtained from an external system and stored in a local cache database to prepare data for obtaining the associated data of the target indicators of the abnormal tags that are frequently clicked tags in the future.

[0077] In one embodiment, the method provided by this application further includes: calculating the analysis progress when the time for generating the correlation analysis result is greater than a preset generation time threshold; obtaining the estimated remaining analysis time based on the analysis progress; and displaying the analysis progress and the estimated remaining analysis time on the correlation analysis page.

[0078] When the generation of correlation analysis results takes a long time, users may mistakenly believe that a malfunction has occurred. To avoid this, if the generation time exceeds a preset generation time threshold, the analysis progress can be calculated. The overall analysis task can be broken down into quantifiable sub-steps: data preprocessing, correlation calculation, and result generation. The weight of each step can then be dynamically allocated based on the characteristics of the target project (e.g., increasing the weight of vendor data retrieval for the first-of-its-kind project, and increasing the weight of cross-pilot correlation calculation for demonstration projects). The analysis progress is calculated in real time by summing the weights of completed sub-steps and multiplying by the completion rate. A preset generation time threshold can be set according to the actual situation.

[0079] The baseline time can be adjusted based on the historical analysis of similar target projects, combined with the complexity of the current project. Then, the dynamic adjustment coefficient can be calculated based on the ratio of the actual time of the current step to the historical average. The estimated remaining time can be obtained by multiplying the baseline total time by (1 - current progress) and the adjustment coefficient.

[0080] In this embodiment, if the time to generate the correlation analysis results exceeds a preset generation time threshold, the analysis progress is calculated to obtain the estimated remaining analysis time. The analysis progress and estimated remaining analysis time are displayed on the correlation analysis page to provide accurate feedback on the analysis progress, so that users are aware of the analysis progress and estimated remaining analysis time, and to avoid users mistakenly believing that a malfunction has occurred.

[0081] In one embodiment, optimization suggestions for the causes of anomalies in the target metric are generated, and the specific steps are as follows: determine the user role based on the account information corresponding to the user account that performed the click operation; determine the suggestion requirement dimension corresponding to the user role based on the association between the user role and the suggestion requirement dimension; and generate optimization suggestions for the causes of anomalies in the target metric based on the suggestion requirement dimension corresponding to the user role.

[0082] Different user roles have different business responsibilities, priorities, and levels of project involvement, resulting in significantly different needs for optimization suggestions regarding abnormal target project metrics. To improve the accuracy of suggestions, optimization suggestions can be generated based on the suggestion needs of user roles, addressing the causes of abnormalities in target metrics.

[0083] Specifically, based on the account information corresponding to the user account performing the click operation, including the account's preset role identifier, scope of responsibilities and permissions, and project participation dimensions (such as operation and maintenance permissions, research permissions, and management permissions), the user's role (operation and maintenance implementation role, research and analysis role, or management decision-making role) can be determined. Based on the characteristics of the target project and the business objectives of each user role, the suggested requirement dimensions corresponding to different user roles can be clarified, forming a correlation between user roles and suggested requirement dimensions. Based on the correlation between user roles and suggested requirement dimensions, the suggested requirement dimensions corresponding to each user role can be determined to generate optimization suggestions targeting the causes of anomalies in the target metrics.

[0084] In this embodiment, the user role is determined based on the account information corresponding to the user account that performs the click operation; the suggestion requirement dimension corresponding to the user role is determined based on the correlation between the user role and the suggestion requirement dimension, so as to generate optimization suggestions for the abnormal reasons of the target indicator. This can ensure that the optimization suggestions are highly consistent with the needs of the user role and improve the accuracy of the suggestions.

[0085] In one embodiment, optimization suggestions are generated based on the causes of anomalies in the target metric. The specific steps are as follows: based on the causes of anomalies in the target metric, a matching historical optimization suggestion is searched in the historical optimization suggestion library; the historical optimization suggestions in the historical optimization suggestion library are historical optimization suggestions that have been verified to be effective in practice; if a matching historical optimization suggestion exists in the historical optimization suggestion library, optimization suggestions are generated based on the matching historical optimization suggestion to address the causes of anomalies in the target metric.

[0086] Historical optimization suggestions that have been proven effective and generated within a set historical time period can be associated with their corresponding historical anomaly causes and stored in the historical optimization suggestion library.

[0087] The similarity analysis can be performed between the abnormal causes of the target indicator and each historical abnormal cause in the historical optimization suggestion library. When the similarity between the abnormal cause of the target indicator and one of the historical abnormal causes in the historical optimization suggestion library is higher than the similarity threshold, the historical optimization suggestion associated with that historical abnormal cause is identified as the historical optimization suggestion that matches the abnormal cause of the target indicator.

[0088] If a matching historical optimization suggestion exists in the historical optimization suggestion library, optimization suggestions are generated based on the matching historical optimization suggestions to address the causes of anomalies in the target indicator.

[0089] If no matching historical optimization suggestion exists in the historical optimization suggestion library, optimization suggestions are generated based on the artificial intelligence diagnostic model to address the causes of anomalies in the target indicator.

[0090] In this embodiment, if a matching historical optimization suggestion exists in the historical optimization suggestion library, optimization suggestions are generated based on the matching historical optimization suggestions that have been verified to be effective in practice, which can improve the accuracy and practicality of the optimization suggestions.

[0091] The method for displaying target projects provided in this application is applied to a target project display system. In an exemplary embodiment, the target project display system is specifically in the form of a single map (science and technology innovation map). Based on the visualization map, the target project is displayed visually, supporting layered penetration to view details, distinguishing between key projects and ordinary projects, and realizing a single map display of the highlights of the target project.

[0092] The specific steps for building the demonstration system for this target project are as follows:

[0093] Step 1: Construct a map with two layers:

[0094] Based on a high-precision electronic map of the city, a basic framework of a Geographic Information System (GIS) adapted to project monitoring is built to obtain a map of the target project. The specific steps are as follows:

[0095] Integrate spatial data such as regional division data (city-district-street / industrial park three-level boundaries), transportation network, land parcel red lines, and functional area planning to form a dual-layer foundation of vector map and image map (vector map is used for precise positioning, and image map is used for real-world reference); develop basic interactive functions such as map zooming, panning, and layer switching, and support precision switching from a city-wide macro perspective (1:50000) down to a specific project parcel (1:500), providing underlying support for project spatial positioning.

[0096] Key information for target projects includes: Basic attributes: project name, type (distinguishing between key planning projects and ordinary projects), responsible unit, project initiation date, and planned duration; Spatial information: specific project address, latitude and longitude coordinates, land area, and construction site boundary; Dynamic information: current construction stage (initiation / construction / acceptance / operation), progress completion rate, funding, research achievements, and existing problems. Data standardization: unified data format (e.g., date format "YYYY-MM-DD", progress unit "%"), and adding unique identifiers for planned projects (e.g., field "plan_type='145'") to ensure clear classification.

[0097] Step 2: Establish a target project database and classification system:

[0098] Key power projects can be referred to as target projects. For example, target projects could be demonstration projects, first-of-its-kind equipment, or innovation platforms.

[0099] For target projects such as demonstration projects, first-of-its-kind equipment, and innovation platforms, a standardized data collection and storage system is constructed to connect with the government affairs systems of various districts and bureaus to collect key (core) information of the projects; a spatiotemporal database is used to store the collected key information data of the projects, so as to realize the correlation query of spatial information and attribute information.

[0100] Step 3: Develop target project spatial matching and visualization annotation functions:

[0101] The target project and its key information are linked to a map with two layers to achieve spatial display. Specifically, the project address can be converted into latitude and longitude coordinates through address resolution technology (such as calling a map interface) and accurately matched with the map's land boundary line; for projects without a clear address (such as platforms within a park), manual positioning on the map is supported and linked to the park's boundary to form a target project map.

[0102] Visual labeling: Different icons can be used to distinguish project types (e.g., building icons for demonstration projects, laboratory icons for innovation platforms); colors can be used to distinguish key planning projects (gold) from ordinary projects (blue); and dynamic icon effects can be used to display construction status (e.g., flashing icons indicate construction in progress, gray icons indicate suspension, and checkmark icons indicate acceptance).

[0103] Step 4: Design a multi-level, jump-based information architecture:

[0104] Construct the information display logic based on the macro-meta-micro level:

[0105] First layer (map overview layer): Clicking on the project icon on the target project map will bring up a pop-up window, which displays the key information page of the target project corresponding to the project icon. The key information page can display key information such as the project name, type, responsible unit, and current progress of the target project.

[0106] The second layer (project details layer): Clicking the "View Details" tab on the key information page in the window will redirect you to the project details page, which displays various metrics of the target project corresponding to the project icon.

[0107] The third layer (deep navigation layer): On the project details page, when the value of the target indicator among various metrics is abnormal, an error label is displayed. The key indicators among these indicators can be referred to as target indicators. These key indicators can be set by staff based on actual conditions.

[0108] Clicking the "Abnormal" label redirects to the correlation analysis page. This page retrieves the correlation data for the target metric and generates correlation analysis results indicating the cause of the abnormality, displaying an optimization suggestion label. Clicking the "Optimization Suggestion" label redirects to the optimization suggestions page, where optimization suggestions are generated based on the cause of the target metric's abnormality.

[0109] For example, if the "Regional Industrial Chain Supporting Score" indicator falls outside the normal range, an anomaly label will automatically appear. Clicking on this label will redirect to a correlation analysis page, where you can obtain the correlation data for the "Regional Industrial Chain Supporting Score" indicator. Based on this data, a correlation analysis will be performed to determine the cause of the anomaly, generating the correlation analysis results and displaying optimization suggestion labels. For instance, the correlation analysis result for the anomaly of the "Regional Industrial Chain Supporting Score" indicator could be the absence of a certain type of supporting enterprise within the region (e.g., "lack of high-end mold suppliers").

[0110] Clicking the "Optimization Suggestions" tab will redirect you to the Optimization Suggestions page, where optimization suggestions will be generated based on the reasons for the anomalies in the target metric. For example, an optimization suggestion could be to connect with a list of potential mold manufacturers in the Yangtze River Delta region.

[0111] In addition, the interactive features of various indicators can be enhanced. For example, intelligent status indicators can be added, and the colors of various indicators can be dynamically adjusted according to data changes (e.g., if the R&D investment intensity decreases by more than 10% year-on-year, the background color of the indicator will turn orange); data freshness indicators can be added (e.g., updated 10 minutes ago, not updated in 24 hours), and clicking on them can show the data source system (e.g., connected to the xx R&D statistics platform).

[0112] In addition, the order of various indicators can be dynamically adjusted according to the click frequency (high-frequency tags are placed at the top).

[0113] In the above, the dynamic tagging system for target metrics is no longer an isolated data display, but rather an intelligent hub for "metric monitoring - problem identification - decision optimization." Each tag serves as both a data entry point and a starting point for analysis, enabling users to quickly access the core issues causing target metric anomalies within three clicks and obtain optimization suggestions within four clicks, providing precise data support for users with different roles.

[0114] Step 5: Develop target project screening and statistical analysis functions:

[0115] Supports multi-dimensional queries and macro-level analysis, enhancing panoramic monitoring capabilities:

[0116] Filtering function: Set filter conditions on the target project map interface (project type, construction status, region, whether it is a key planning project, etc.). After clicking filter, the target project map will only display target projects that meet the conditions (such as displaying all key planning projects in the city that are under construction).

[0117] Statistics Dashboard: Set up a statistics panel on the right side of the target project map to automatically calculate and display statistics.

[0118] Regional distribution: Percentage of target projects in each district and density of key planned projects (number of projects per square kilometer);

[0119] Status distribution: Number of projects in each construction stage (e.g., 60% under construction, 20% under acceptance);

[0120] Trend indicators: the number of new projects started in the past 6 months, the average progress completion rate of key planned projects, etc.

[0121] Jump Linkage: Clicking on a data point in the statistics dashboard (e.g., 25% of projects in District xx) will automatically locate the target project map to the corresponding area and highlight all projects in that area, achieving two-way penetration of statistical data and spatial distribution.

[0122] Step Six: Establish a dynamic data update mechanism:

[0123] Ensure the real-time availability of target project map information to support dynamic monitoring:

[0124] Automatic synchronization: Establish data interfaces with the government affairs systems of various district bureaus, automatically capture dynamic data of target projects (such as progress updates and fund arrivals) every morning at midnight, and update the target project database;

[0125] Manual data entry: For projects that are not yet connected to the government system, a back-end data entry portal will be opened, and the responsible unit will update the information regularly (supporting materials, such as scanned copies of progress reports, are required).

[0126] Anomaly alert: When data updates are interrupted (e.g., due to a system failure in a district or bureau) or when target project information has not been updated for more than 30 days, an alert will be sent to the administrator to ensure data timeliness.

[0127] Step 7: Deploy the system and configure access control:

[0128] Complete system launch and security management:

[0129] System Deployment: Deploy the target project map to the cloud platform, supporting web access and mobile adaptation, ensuring convenient viewing on multiple terminals;

[0130] Permission configuration: Permissions are assigned based on user roles (e.g., city-level administrators can view projects in the city and edit data, district-level users can only view projects in their own district and have no editing permissions, and enterprise users can only view projects they are involved in).

[0131] Operation logs: Record all user queries, redirects, and edits to form audit logs, ensuring data security and traceability.

[0132] Through the above steps, the target project display system can achieve multi-level jumps from geographic space to all elements of the project, which not only meets the needs of macro monitoring (such as the layout of key projects in the city's planning) but also supports micro-detail tracking (such as the reasons for the delay in the progress of a target project). It can achieve the monitoring goal of viewing the target project in a panoramic view with one map and seeing the entire chain with one click.

[0133] The target project display system provided in this embodiment can intuitively present the spatial distribution and construction status of the target project, achieving a single-image display of the project's highlights and improving the convenience and visualization of panoramic monitoring. The dynamic tagging system for target indicators is no longer an isolated data display, but rather an intelligent hub for "indicator monitoring - problem identification - decision optimization." Each tag is both a data entry point and a starting point for analysis, enabling users to quickly access the core issues causing target indicator anomalies within three clicks and obtain optimization suggestions within four clicks, providing precise data support for users with different roles.

[0134] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps. It is understood that the steps in different embodiments can be freely combined as needed, and all non-contradictory solutions formed by such combinations are within the scope of protection of this application.

[0135] Based on the same inventive concept, this application also provides a display device for implementing the above-described display method for the target item. The solution provided by this device is similar to the implementation described in the above method; therefore, the specific limitations in one or more embodiments of the display device for the target item provided below can be found in the limitations of the display method for the target item described above, and will not be repeated here.

[0136] In one exemplary embodiment, such as Figure 4 As shown, a display device for a target project is provided, wherein:

[0137] The key information display module 401 is used to respond to a click operation on one of the project icons on the target project map, pop up a window, and display the key information page of the target project corresponding to the project icon in the window;

[0138] The various indicator display module 402 is used to respond to the click operation of the view details tab of the key information page, jump to the project details page, and display various indicators of the target project corresponding to the project icon on the project details page;

[0139] The anomaly label display module 403 is used to display an anomaly label when the value of the target indicator among the various indicators is abnormal.

[0140] The correlation analysis result generation module 404 is used to respond to the click operation on the abnormal label, jump to the correlation analysis page, generate the correlation analysis result of the abnormal cause of the target indicator on the correlation analysis page, and display the optimization suggestion label.

[0141] The optimization suggestion generation module 405 is used to respond to a click operation on the optimization suggestion label, jump to the optimization suggestion page, and generate optimization suggestions on the optimization suggestion page for the abnormal reasons of the target indicator.

[0142] In one embodiment, the association analysis result generation module 404 is further configured to: obtain association data of the target indicator from a local cache database when the abnormal label of the target indicator is a frequently clicked label; obtain association data of the target indicator from an external system when the abnormal label of the target indicator is a non-frequently clicked label; and generate an association analysis result of the abnormal cause of the target indicator based on the association data of the target indicator.

[0143] In one embodiment, the device further includes a local cache database acquisition module, configured to: acquire the number of times an abnormal tag has been clicked in a set historical period, and determine the frequently clicked tags; acquire the associated data of the target indicators corresponding to the frequently clicked tags from an external system; and store the associated data in the local cache database.

[0144] In one embodiment, the device further includes a progress time display module, used to: calculate the analysis progress when the time for generating the correlation analysis result is greater than a preset generation time threshold; obtain the estimated remaining analysis time based on the analysis progress; and display the analysis progress and the estimated remaining analysis time on the correlation analysis page.

[0145] In one embodiment, the optimization suggestion generation module 405 is further configured to: determine the user role based on the account information corresponding to the user account that performed the click operation; determine the suggestion requirement dimension corresponding to the user role based on the association between the user role and the suggestion requirement dimension; and generate optimization suggestions for the abnormal causes of the target indicator based on the suggestion requirement dimension corresponding to the user role.

[0146] In one embodiment, the optimization suggestion generation module 405 is further configured to: search for matching historical optimization suggestions in the historical optimization suggestion library based on the cause of the anomaly of the target indicator; the historical optimization suggestions in the historical optimization suggestion library are historical optimization suggestions that have been verified to be effective in practice; and, if there is a matching historical optimization suggestion in the historical optimization suggestion library, generate optimization suggestions based on the matching historical optimization suggestions for the cause of the anomaly of the target indicator.

[0147] Each module in the demonstration device of the aforementioned target project can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0148] In one exemplary embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 5As shown, the computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage medium. The database stores data for embodiments of the target project demonstration method. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network connection. When the computer program is executed by the processor, it implements a target project demonstration method.

[0149] Those skilled in the art will understand that Figure 5 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0150] In one embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above method embodiments.

[0151] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the steps in the above method embodiments.

[0152] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0153] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0154] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0155] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0156] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for displaying a target project, characterized in that, The method includes: In response to a click on one of the project icons on the target project map, a pop-up window is displayed, showing a page of key information about the target project corresponding to the project icon. In response to a click on the "View Details" tab of the key information page, the user is redirected to the project details page, where various metrics of the target project corresponding to the project icon are displayed. When the value of the target indicator among the various indicators is abnormal, an abnormal label will be displayed; In response to a click on the abnormal label, the user is redirected to the correlation analysis page, where correlation analysis results of the abnormal causes of the target indicator are generated and optimization suggestion labels are displayed. In response to a click on the optimization suggestion label, the user is redirected to the optimization suggestion page, where optimization suggestions are generated to address the causes of the anomalies in the target metric.

2. The method according to claim 1, characterized in that, The correlation analysis results for generating the anomalies of the target indicator include: If the abnormal label of the target indicator is a frequently clicked label, retrieve the associated data of the target indicator from the local cache database; If the abnormal label of the target indicator is a non-frequent click label, obtain the associated data of the target indicator from an external system; Based on the associated data of the target indicator, generate the association analysis results of the abnormal causes of the target indicator.

3. The method according to claim 2, characterized in that, Retrieve the local cache database, including: Get the number of times abnormal tags were clicked within a set historical period to identify frequently clicked tags; Obtain relevant data on target metrics corresponding to frequently clicked tags from external systems; The associated data is stored in a local cache database.

4. The method according to claim 1, characterized in that, The method further includes: If the time to generate the correlation analysis results exceeds a preset generation time threshold, the analysis progress is calculated. Based on the analysis progress, the estimated remaining analysis time is obtained; The correlation analysis page displays the analysis progress and the estimated remaining analysis time.

5. The method according to claim 1, characterized in that, The generation of optimization suggestions for the causes of anomalies in the target metric includes: Determine the user role based on the account information corresponding to the user account that performs the click operation; Based on the relationship between user roles and suggestion requirement dimensions, determine the suggestion requirement dimensions corresponding to user roles; Based on the suggested needs dimension corresponding to the user role, optimization suggestions are generated to address the causes of anomalies in the target metric.

6. The method according to claim 1, characterized in that, The generation of optimization suggestions for the causes of anomalies in the target metric includes: Based on the cause of the anomaly in the target indicator, a matching historical optimization suggestion is searched in the historical optimization suggestion library; the historical optimization suggestions in the historical optimization suggestion library are those that have been verified to be effective in practice. If a matching historical optimization suggestion exists in the historical optimization suggestion library, optimization suggestions are generated based on the matching historical optimization suggestion to address the cause of the anomaly in the target indicator.

7. A display device for a target project, characterized in that, The device includes: The key information display module is used to respond to a click operation on one of the project icons on the target project map, pop up a window, and display the key information page of the target project corresponding to the project icon in the window; The various indicator display module is used to respond to the click operation of the view details tab on the key information page, jump to the project details page, and display various indicators of the target project corresponding to the project icon on the project details page; The anomaly label display module is used to display an anomaly label when the value of the target indicator among the various indicators is abnormal; The correlation analysis result generation module is used to respond to the click operation of the abnormal label, jump to the correlation analysis page, generate the correlation analysis result of the abnormality cause of the target indicator on the correlation analysis page, and display the optimization suggestion label. The optimization suggestion generation module is used to respond to a click operation on the optimization suggestion label, jump to the optimization suggestion page, and generate optimization suggestions on the optimization suggestion page for the abnormal reasons of the target indicator.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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